Accelerat ing t he world's research.
Advanced Strength and Conditioning Luca Brunetti
Cite this paper
Downloaded fromAcademia.edu
Get the citation in MLA, APA, or Chicago styles
Related papers
Download a PDF Pack of t he best relat ed papers
St rengt h and Condit ioning for Muay T hai At hlet es MUAY Hélio Pereira Banhos Hélio Pereira Banhos Coaching Sprint ing: Expert Coaches’ Percept ion of Resist ance Based Training Richard Bolger Periodizat ion for Mixed Mart ial Art s Pat rick Olbrich
Advanced Strength and Conditioning
Becoming an effective strength and conditioning practitioner requires the development of a professional skills set and a thorough understanding of the scientific basis of best practice. Aimed at advanced students and beginning practitioners, this book explores the latest scientific evidence and applies it to exercise selection and programming choices across the full range of functional areas in strength and conditioning, from strength and power to speed and agility. With coverage of data analysis and performance feedback, both vital skills for the contemporary strength and conditioning coach, this concise but sophisticated textbook is the perfect bridge from introductory study to effective professional practice. Written by experts with experience in a wide variety of sports, its chapters are enhanced by extensive illustrations and address key topics such as: • • • • •
fitness testing and data analysis developing strength and power motor skill acquisition and development strategies for competition priming monitoring training load, fatigue and recovery.
Advanced Strength and Conditioning: An Evidence-based Approach is a valuable resource for all advanced students and practitioners of strength and conditioning and fitness training. Anthony Turner is the Director of postgraduate programmes at the London Sport Institute, Middlesex University London, UK, where he is also the Programme Leader for the MSc in strength and conditioning. Anthony consults with the British Military, Queens Park Rangers Football Club, Saracens Rugby Club and various Olympic and Paralympic athletes. He was also the head of physical preparation for British Fencing between the London and Rio Olympics. Anthony is accredited (with distinction) with the National Strength and Conditioning Association and the UK Strength and Conditioning Association (UKSCA), and was awarded the 2015 UKSCA coach of the year for education and research. Anthony has published over 60 peer-reviewed journal articles, is an associate editor for the Strength and Conditioning Journal, and completed his PhD examining physical preparation in Olympic fencing. Paul Comfort is Programme Leader for the MSc in strength and conditioning at the University of Salford, UK. He has applied experience across a variety of team sports and is currently consulting with numerous professional sports teams within the Greater Manchester area. Paul is a founding member of the UKSCA, where he is also an editorial board member for the Professional Strength and Conditioning Journal and joint editor of its Professional Insights column. He has published over
100 peer-reviewed journal articles along with numerous book chapters, and is a senior associate editor for the Journal of Strength and Conditioning Research.
Advanced Strength and Conditioning An Evidence-based Approach
Edited by Anthony Turner and Paul Comfort
First published 2018 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 711 Third Avenue, New York, NY 10017 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2018 selection and editorial matter, Anthony Turner and Paul Comfort; individual chapters, the contributors The right of Anthony Turner and Paul Comfort to be identified as the authors of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record for this book has been requested ISBN: 978-1-138-68735-6 (hbk) ISBN: 978-1-138-68736-3 (pbk) ISBN: 978-1-315-54234-8 (ebk) Typeset in Berling and Futura by Keystroke, Neville Lodge, Tettenhall, Wolverhampton
Contents
List of figures List of tables List of contributors List of abbreviations 1 Strength and conditioning: Coach or scientist? Perry Stewart, Paul Comfort and Anthony Turner PART 1 Developing your athlete 2 Developing muscular strength and power Timothy J. Suchomel and Paul Comfort 3 Stretch-shortening cycle and muscle-tendon stiffness John J. McMahon 4 Endocrinology and resistance training Anthony Turner and Christian Cook 5 Training aerobic fitness Alex Bliss and Rob Harley 6 Repeat sprint ability and the role of high-intensity interval training Anthony Turner and David Bishop 7 Concurrent training Richard Clarke, Rodrigo Aspe and Jonathan Hughes PART 2 Programming and monitoring for your athlete 8 Periodisation Anthony Turner and Paul Comfort 9 Workload monitoring and athlete management Tim J. Gabbett
10 Priming match-day performance: Strategies for team sports players Mark Russell, Natalie Williams and Liam P. Kilduff 11
Strategies to enhance athlete recovery Emma co*ckburn and Phill Bell
12 Fitness testing and data analysis John J. McMahon, Paul Comfort and Anthony Turner PART 3 Coaching your athlete 13 Movement screening: An integrated approach to assessing movement quality Chris Bishop 14 Technical demands of strength training Timothy J. Suchomel and Paul Comfort 15 Weightlifting for sports performance Timothy J. Suchomel and Paul Comfort 16 Plyometric training Christopher J. Sole 17 Training change of direction and agility Sophia Nimphius 18 Speed and acceleration training Pedro Jiménez-Reyes, Bret Contreras and Jean-Benoît Morin 19 Applied coaching science Nick Winkelman Index
Figures
1.1 1.2 2.1 2.2 2.3 2.4 2.5 2.6 2.7 3.1 3.2 3.3 3.4 3.5 3.6 5.1 5.2 7.1 8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 8.10
Considerations for a modern day S&C coach before commencing a working relationship with an athlete The multi-faceted nature of strength and conditioning Comparison of force, power, RFD and movement time between stronger and weaker athletes during a countermovement jump Medial gastrocnemius (MG) fascicle length and MG pennation angle (θ), as measured between the superficial and deep MG aponeuroses Four sarcomeres in parallel Four sarcomeres in series Example emphasis change during a periodised training programme (phase potentiation) Back squat exercise using variable resistance with chains Bench press exercise using variable resistance with elastic bands An example of an object that obeys Hooke’s Law and the equation to calculate stiffness (k), where ∆F = change in force and ∆x = change in length An example of the torsional spring model and how it corresponds to the human body An example of the joint moment-joint angular displacement relationship during loaded flexion and extension An example of how joint touchdown angles influence leg and joint stiffness values An example of the spring-mass model and how it corresponds to the human body A schematic diagram illustrating how the leg(s) change from being more compliant to more stiff for a range of stretch-shortening cycle tasks A three intensity zone model based on the identification of ventilatory or blood lactate thresholds Example blood lactate response to incrementally increasing running speed with corresponding training zones and physiological markers The recommended decision making process during periods of concurrent Training The inverse relationship between volume and intensity Soon ripe, soon rotten The 3:1 loading paradigm, illustrating the increase and then dissipation of excessive fatigue The general adaptation syndrome The stimulus-fatigue-recovery-adaptation concept The Fitness-Fatigue paradigm Athlete preparedness based on the specific form of fatigue The principle of diminishing returns Basic model of periodisation entailing little variation and relatively flat workloads The traditional, undulating approach to the design of periodised training
8.11 8.12 8.13 9.1 9.2 9.3 9.4 9.5 9.6 9.7 9.8 10.1 10.2 11.1 12.1 12.2 13.1 13.2 13.3 13.4 13.5 13.6 13.7 13.8 13.9 13.10 13.11 13.12 13.13 13.14 13.15 14.1 14.2 15.1 15.2 15.3 15.4 15.5
The conjugate sequence system pioneered by Yuri Verkhoshansky (1986) Schematic representation of the three principle tapering strategies Schematic representation of the 2-phase taper Biological adaptation through cycles of loading and recovery Biological maladaptation through cycles of excessive loading and/or inadequate recovery Well-being continuum Relationship between training load, training phase, and likelihood of injury in elite rugby league players Incidence of new and recurrent injuries before (2006-2007) and after (2008-2009) the introduction of an injury prediction model designed to reduce training load-related injuries The acute:chronic workload ratio and likelihood of injury Relationship between maximal velocity running and likelihood of injury Combined effect of chronic load history and maximal velocity exposure on injury risk A theoretical outline of the typical activities performed in the 12 hours before an away match (with overnight hotel stay) with a 20:00 hour kick-off (0 hour) A theoretical model of organising the pre-match period to supplement the practices currently employed with the performance enhancing strategies outlined in the chapter Timing of recovery strategy aims, underpinned by foundations of optimal sleep and nutrition Example of correctly identifying the unweighting, braking and propulsive phases of a countermovement jump force-time curve by overlaying the velocity-time curve Example of conducting a temporal phase analysis of relative power-time curves produced by more and less powerful athletes Overhead squat (anterior view) Overhead squat (lateral view) Overhead squat (posterior view) External rotation of the feet Knee valgus Excessive forward lean Lower back arching Lower back rounding Arms fall forward Single leg squat Knee valgus Hip hike Hip drop Inward trunk rotation Outward trunk rotation Scenario requiring weightlifting alternatives for the snatch Scenario requiring weightlifting alternatives for the hang power clean Hook grip – thumb wraps under the bar with the fingers wrapped around the thumb and bar Starting position for the snatch (left) and clean (right) The end of the first pull for the snatch (left) and clean (right) Mid-thigh (power) position side view for the snatch (left) and oblique view for the clean (right) Second pull of the snatch (left) and clean (right)
15.6 15.7 15.8 15.9 15.10 15.11 15.12 15.13 15.14 15.15 15.16 16.1 16.2 16.3 16.4 16.5 16.6 17.1 17.2 17.3 17.4 17.5 18.1 18.2 19.1
Catch position of the snatch (left) and clean (right) Power snatch (left) and power clean (right) catch positions Recovery position for the snatch (left) and clean (right) Starting position for a jerk variation Completion of the dip phase of the jerk The drive phase of the jerk Split jerk receiving position Power jerk receiving position Jerk recovery Theoretical force-velocity (power) curve with respect to weightlifting derivatives Sequenced progressions of speed and strength-power development with the weightlifting derivatives that may be used within each phase (a) Mechanical and (b) n euro physiological models of stretch-shortening cycle potentiation Illustrates the force-time histories of a bilateral ankle hop and a drop jump from 40 centimeters Illustration of a generic periodization model where the target training adaptation is impulsive ability or “explosiveness” Displays a generic example of how PT may be programed during a general preparation or strength-endurance mesocycle(s) Displays a generic example of how PT may be programed during a basic or maximum strength mesocycle(s) Displays a generic example of how PT may be programed during a mesocycle(s) where the primary training focus is developing impulsive ability or “explosiveness” Example of force-time curve of the plant phase of a 45° COD and a stance phase of a maximal velocity sprint Example assessment of COD and physical capacity Qualitative assessment of COD performance during a 180° COD Proposed change of direction development model Example program from needs analysis through to long-term planning for subsequent blocks of training Ratio of forces (RF) and index of force orientation (DRF) Force-velocity-power profile of Usain Bolt’s world record Newell (1986) interacting constraints model
Tables 1.1 2.1 2.2 3.1 4.1 4.2 5.1 5.2 6.1 6.2 6.3 8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 9.1 11.1 13.1 13.2 13.3 13.4 13.5 13.6 13.7 14.1 14.2 15.1 16.1 17.1 17.2
The definition and correspondence of scientific area to the roles of a typical S&C coach Architectural adaptations in response to different training stimuli Relative power outputs for male athletes during various exercises A summary of studies which have determined the effects of training interventions on global lower limb stiffness measures Individual studies examining the priming of testosterone via non-physical interventions such as videos, feedback and peer assessment Individual studies examining load, rest and hormones on hypertrophy and strength Operational definitions for frequently encountered terms Table of training zones and cues that can be used by athletes and coaches to estimate their current zone Effective training systems to enhance aerobic fitness Interval distances for high-intensity interval training using MAS High-intensity interval training based on each energy system The principle phases and sub-phases of periodisation Exercise deletion and representation Example sessions used as part of a basic periodised model Two example strength sessions and two example power sessions, which can be implemented as part of an intermediate periodised programme A practical example for applying and adapting the conjugate system Example microcycle completed as part of a non-traditional periodisation strategy Summary of performance gains following a taper Effect of training variables on the effect size of taper-induced performance adaptations An example of the acute:chronic workload ratio calculation using weekly rolling averages Practical recommendations for the use of various recovery interventions Suggested instructions for the overhead squat assessment Suggested instructions for the single leg squat assessment Injury rates by cycle length in marine officers with differing FMS scores Operational definitions for the modified LESS sheet The Landing Error Scoring System (LESS) score sheet for the modified version of the LESS Grading criteria for the tuck jump assessment Proposed gold, silver, and bronze screening packages Rest interval length to achieve specific training goals Cluster set rest interval length to achieve specific training goals Reported relative kinetic variables across power clean derivatives Examples of common plyometric training exercises Ground contact times during various angles of change of direction Example classification of existing change of direction speed and agility tests
Contributors Rodrigo Aspe is the Academic Course Leader for the undergraduate strength and conditioning programme at the University of Gloucestershire. He obtained an MSc in strength and conditioning from the University of Edinburgh and is an accredited strength and conditioning coach with the UK Strength and Conditioning Association (UKSCA). His research interests are very much applied, and he has published articles in the Journal of Strength and Conditioning Research. Prior to academia he worked with Aberdeen Grammar Rugby in the Scottish BT Premiership and at the north-east satellite centre for Scottish Hockey. He is still an applied coach at the University of Gloucestershire for the Talented Athlete Scholarship Scheme. Phill Bell is a principal scientist at the GSK Human Performance Lab where he combines elite athlete scientific support with applied exercise physiology research. In respect of scientific support, Phill has worked with athletes in a wide range of sports including several Olympians and world champions. With regards to research, he has authored a number of peer-reviewed journal articles with particular expertise in modalities to accelerate recovery from strenuous exercise. Prior to joining the GSK Human Performance Lab, Phill spent time as a lecturer in exercise physiology at Nottingham Trent University. He completed his PhD at Northumbria University in exercise physiology in 2015, focussing on a nutritional supplement for accelerating recovery from exercise. Chris Bishop is a Strength and Conditioning Coach at the London Sport Institute, Middlesex University where he is also the Programme Leader for the MSc in strength and conditioning. Prior to his career in academia, Chris spent five years as the lead S&C coach for a private physiotherapy company in the UK where he delivered S&C services predominantly to youth athletes across a wide range of sports. His experiences working with a variety of athletes alongside medical and healthcare professionals prompted his interest in movement screening, which he sees as a key method for individualising athlete program design. David Bishop has 20 years of experience as both a researcher and an applied sport scientist working with elite athletes. In the three years prior to the 2000 Sydney Olympics, he worked with Australian hockey, water polo, netball, beach volleyball and kayak teams. Professor Bishop has also gained invaluable experience consulting with professional teams such as the Fremantle Football Club. He is the inaugural research leader (sport science) at ISEAL and oversees world-class research focusing on improving the sporting performance of individual athletes and teams. In particular, he is internationally renowned for his research concerning team-sport performance, with a particular focus on repeated-sprint ability (RSA), the optimisation of training, and the effects of muscle pH on performance and fatigue. Professor Bishop has more than 200 peer-reviewed articles and six book chapters in the area of human movement and sport science. Professor Bishop is also the former president of Exercise and Sport Science Australia, and assistant editor of Medicine and Science in
Sports and Exercise. Alex Bliss, Msc, ASCC, BASES, CSCi is currently a Lecturer in Strength and Conditioning Science at St Mary’s University, Twickenham. He was previously Senior Sport and Exercise Scientist at the University of Brighton, managing the Sport and Exercise Science Consultancy Unit. He is an accredited strength and conditioning coach through the UKSCA, a BASES-accredited physiologist, and chartered scientist through the Science Council. Alex has coached high-performance athletes in a range of sports, both professional and amateur. He worked as a regional physiologist for six years for England Athletics, providing athlete laboratory assessment and coach guidance and support. He is currently reading for a PhD in concurrent training in middle-distance athletes. Richard Clarke is the Academic Course Leader for the undergraduate strength and conditioning programme at The University of Gloucestershire. After completing an undergraduate degree in strength and conditioning and becoming a UKSCA accredited strength and conditioning coach, he continued at the University of Gloucestershire to study for an MSc in the topic. Prior to his academic role, he worked with Gloucester Rugby and the Bristol Academy of Sport. Rich now acts as a Talented Athlete Scholarship Scheme Practitioner and also coaches high performing youth athletes through the Athlete Academy, Gloucester. His interests include coaching science, coach development and speed and agility training. Emma co*ckburn is a Lecturer in sport and exercise physiology at Newcastle University. Prior to joining Newcastle University, Emma was a Senior Lecturer at both Middlesex and Northumbria University. She completed her PhD in sport and exercise physiology in 2010, focussing on the effect of acute milk-based carbohydrate/protein supplementation on the attenuation of exercise-induced muscle damage. Emma’s research area focusses on the physiological stress to exercise and the modification of the acute and chronic response, specifically focussing on nutritional supplements, and cold and hot water immersion. She is currently supervising three PhD students investigating this area. Bret Contreras received a PhD in sports science from Auckland University of Technology in New Zealand and a CSCS certification from the NSCA. He is widely regarded to be the world’s foremost authority on glute training. He is the author of Bodyweight Strength Training Anatomy, the co-author of Strong Curves, the co-founder of Strength & Conditioning Research Review, the inventor of Hip Thruster and the founder of Strong by Bret. Christian Cook is a Research Professor in sport performance science at the University of Canberra Research Institute for Sport and Exercise in Canberra, Australia, and a technical consultant to the Australian Institute of Sport. In addition, he holds honorary positions at Bangor University, Wales, and Imperial College London. He has worked in elite performance sport for the last 30 years, including involvement in Rugby World Cups, America’s Cup yachting and both the summer and winter Olympics. Tim J. Gabbett has over 20 years of experience working as an applied sport scientist with athletes and coaches from a wide range of sports. He holds a PhD in human physiology (2000) and has completed a second PhD in the ‘Applied Science of Professional Football’ (2011), with special reference to physical demands, injury prevention and skill acquisition. Tim has worked with elite
international athletes over several Commonwealth Games and Olympic Games cycles. He continues to work as a coaching and sport science consultant for several high performance teams around the world. Tim has published over 200 peer-reviewed articles and has presented at more than 200 national and international conferences. He is committed to providing ‘real world’ support for coaches and athletes. To contact Tim visit www.gabbettperformance.com. Rob Harley, Mphil, is a Principal Lecturer in sport and exercise science at the University of Brighton. He worked as a BASES accredited sports scientist and strength and conditioning coach for over 20 years with the Great Britain and England basketball teams, the England U21 and U17 netball squads, the England U19 and U15 cricket squads and the Sussex County cricket team. He is a lifelong runner and won the Beachy Head marathon in 2012. He has developed a variety of strength and conditioning and physiology modules and is currently developing an MSc in strength and conditioning to run alongside the University of Brighton’s MSc in applied sport physiology. Jonathan Hughes is the academic course leader for the MSc strength and conditioning programme at the University of Gloucestershire. He is an accredited strength and conditioning coach (ASCC) with the UKSCA. Jonathan’s experience covers a variety of sporting backgrounds from rugby to barefoot water-skiing, and he is currently providing the strength and conditioning delivery to elite sports scholars at an independent school. Jonathan’s PhD research focussed on the metabolic changes in muscle following eccentric training. He currently leads a programme of research investigating the impact of chronic and acute fatigue on injury risk in elite youth athletes. He has published in international peer-reviewed journals and has presented his work at both national and international conferences. Pedro Jiménez-Reyes is Lecturer at the Faculty of Sport of the Catholic University of San Antonio (Murcia, Spain). He obtained a Track & Field Coach National Diploma in 2010 and obtained his PhD in high performance in sport in 2010 at the University of Pablo de Olavide (Seville, Spain). Dr Jiménez-Reyes’s field of research is mainly human exercise and sport physiology and performance, with application in the field of sport training, and a specific interest in maximal power movements (sprint, jumps). He has published several peer-reviewed journal articles since 2010. He trains elite athletes and collaborates and plays a consultant role with elite sprinters and team sports in Spain. Liam P. Kilduff obtained his PhD from the University of Glasgow. He has worked for the last 15 years as an applied researcher in performance science at Swansea University where his research interests focus mainly on elite athlete preparation strategies. He currently works with a number of summer and winter Olympic sports along with professional rugby and football teams. He has published in excess of 100 research papers and also sits on the editorial board of two sport science related journals. He has recently worked with Sport Wales to establish the Welsh Institute of Performance Science (WIPS) which aims to further develop sport science in Wales, train future sport scientists, enhance the application of science in Welsh sports and increase collaboration between Welsh sport, academia and business. Professor Kilduff is the director of WIPS and chairs its research steering group. John J. McMahon, PhD, CSCS*D, ASCC, PGCAP, FHEA, is a Lecturer in sports biomechanics and strength and conditioning at the University of Salford. John received is PhD in sports biomechanics
from Salford in 2015 following his research into the influence of modulating dynamic muscle-tendon stiffness on stretch-shortening cycle function. John has also been an accredited strength and conditioning coach with both the National and United Kingdom Strength and Conditioning Associations since 2010. John has co-authored 35 peer-reviewed journal articles/conference presentations relating to athletic performance monitoring and development. John is currently researching alternative methods of analysing vertical jump performance to better inform training priorities and adaptation. Jean-Benoît Morin is Full Professor at the Faculty of Sport Sciences of the Université Côte d’Azur (Nice, France). He obtained a Track & Field Coach National Diploma in 1998 and obtained his PhD in human locomotion and performance in 2004 at the University of Saint-Etienne, France. Professor Morin’s field of research is mainly human locomotion and performance, with specific interest in running biomechanics and maximal power movements (sprint, jumps). He has published over 100 peer-review journal articles since 2002, and collaborates and plays a consultant role with elite sprinters and team-sports players all over the world. Sophia Nimphius, PhD, PCAS-E, ASpS2, CSCS*D, is an Associate Professor in the School of Medical and Health Sciences at Edith Cowan University. She is the sport science manager at the Hurley Surfing Australia High Performance Centre and manages high performance services for Softball Western Australia. She is a recognised pro-scheme accredited coach elite with the Australian Strength and Conditioning Association (ASCA) and is also a current board member. In addition, she is a Level 2 accredited sports scientist and high performance manager with Exercise and Sports Science Australia and a certified strength and conditioning specialist with the National Strength and Conditioning Association. Mark Russell is a Reader in performance nutrition and applied exercise physiology at Leeds Trinity University. Mark’s areas of expertise focus around applied exercise physiology, sport nutrition and related ergogenic aids and strength and conditioning. Mark’s current research interests focus primarily on the physiology of intermittent exercise and interventions to promote improvements in performance in team-sports athletes. As a result of this research, Mark has published over 50 peerreviewed articles, presented at international conferences and led multiple industry-funded contract research projects from inception to completion. Mark also works with a range of professional rugby and football teams and has consulted to AFC Bournemouth, Newcastle United Football Club, Sunderland Association Football Club, Welsh National Rugby Union Squad, Wigan Warriors Rugby League Football Club and Swansea City Association Football Club. Mark was also the National Lead for Applied Exercise Physiology with UK Deaf Sport between 2010 and 2017 and was responsible for the co-ordination of the sports science support services for DeaflympicsGB at the 2013 Summer Deaflympics held in Sofia, Bulgaria. Christopher J. Sole, PhD, CSCS, is an Assistant Professor of exercise and sport science at The Citadel, the Military College of South Carolina. His primary research interests include training monitoring, biomechanical analysis of resistance training exercise, adaptation to strength and power training and relationships between training, performance and injury in sport. Dr. Sole earned his PhD in sport physiology and performance from East Tennessee State University.
Perry Stewart, MSc, ASCC, CSCS, BASES, CSci, is the lead academy strength and conditioning coach (U9-16) at Arsenal Football Club and a visiting lecturer at the London Sport Institute, Middlesex University, delivering on the MSc strength and conditioning programme. He is an accredited strength and conditioning coach with the UK Strength and Conditioning Association (UKSCA) and National Strength and Conditioning Association (NSCA). Perry is also a BASES accredited sport scientist chartered through the Science Council. Perry consults with the UKSCA as a project team member and regularly contributes to the Strength and Conditioning Journal, as well as other journals. He was previously head of academy sport science at Queens Park Rangers football club, and has also worked within women’s football, youth tennis and with international athletes from taekwondo, judo, karate, athletics and fencing. Timothy J. Suchomel, PhD, CSCS*D, USAW-SPC, is an Assistant Professor in the department of human movement sciences and a strength and conditioning coach at Carroll University in Waukesha, Wisconsin, USA. Prior to Carroll University, Dr. Suchomel worked as an assistant strength and conditioning coach and sport scientist during his doctoral work at East Tennessee State University. He is a certified strength and conditioning specialist with distinction through the National Strength and Conditioning Association and a certified sports performance coach through USA Weightlifting. Natalie Williams is a PhD student at Swansea University researching the use of vascular occlusion for sports performance. Natalie’s area of expertise is applied exercise physiology looking at athlete preparation and recovery for optimal sports performance. Natalie currently provides exercise physiology support to Welsh Weightlifting and also previously worked with a range of sports supported by Sport Wales, including cycling, gymnastics and athletics. Natalie was previously sport science manager for Swim Wales. Nick Winkelman is the Head of Athletic Performance and Science for the Irish Rugby Football Union. Prior to working for Irish Rugby, Dr. Winkelman was the Director of Education for EXOS (formerly Athletes’ Performance) where he oversaw the development and execution of all internal and external educational initiatives. As a performance coach, Nick has worked with many athletes within the NFL, MLB, NBA, national sport organizations and military. He also oversaw the speed and assessment component of the EXOS NFL Draft Development Program, which supports more than 100 athletes a year preparing for the NFL (American football).
Abbreviations 1RM ADP AMP AO ATP BASES C CC CHO CK CMJ CNe COD CODS COM COMP CSA CT CWI DJs DLPFC dm DRF EF EIMD EMG EUR FI FMS FO FPPA FTot F-v GAS GCT GH GPT
one repetition maximum adenosine diphosphate adenosine monophosphate antioxidant supplements adensosine triphosphate British Association of Sport and Exercise Sciences cortisol contractile component carbohydrate creatine kinase countermovement jump critical non-essentials change of direction change of direction speed centre of mass competition cross-sectional area complex training cold water immersion drop jumps dorsolateral prefrontal cortex dry muscle decrease in the ratio of force extrafusal fibers exercise-induced muscle damage electromyography/electromyographic/electromyogram eccentric utilization ratio fatigue index Functional Movement Screen functional overreaching frontal plane projection angle support phase Force-velocity general adaptation syndrome ground contact time growth hormone general physical training
GRF GSAC H+ HB HF HIIT HR IPC KP KR LESS LG LLR LSD LSI LT LTP M1 MAE MAS MCT MG MLR MLSS MS MSFT mTOR MTS MTU MVC MVIC NFO OBLA OT PAP PCr PDH PEC PFK PFPS PGC-1α Pi Pmax PMC PT
ground reaction force gastrocnemius-soleus-achilles complex hydrogen ion haemoglobin horizontal force high-intensity interval training heart rate ischemic pre-conditioning knowledge of performance knowledge of results Landing Error Scoring System lateral gastrocnemius long-latency response long slow distance running Limb Symmetry Index lactate threshold lactate turnpoint primary motor cortex method of amplification of error maximal aerobic speed monocarboxylate transport proteins medial gastrocnemius medium-latency response maximal lactate steady state muscle spindles Multi-Stage Fitness Test mammalian target of rapamycin muscle-tendon stiffness musculotendinous (muscle-tendon) unit maximal voluntary contraction maximal voluntary isometric contraction non-functional overreaching onset blood lactate accumulation overtraining post-activation potentiation phosphocreatine pyruvate dehydrogenase parallel elastic component phosphofructokinase patella-femoral pain syndrome peroxisome proliferator-activated receptor gamma coactivator 1-alpha inorganic phosphate maximum horizontal external power output premotor cortex plyometric training
P-v RE RF RFD RM ROM ROS RPE RSA S&C SEC SFRA SJ SLH SLR SLS SM SMA SPPCs SSC SSPT T TCA TJA TL TWI v0 VCCF VEGF VF VHS VL V̇O2 max V̇O2 peak vOBLA VPCF vV̇O2 max WBC YIRT
power-velocity running economy ratio of forces rate of force development repetition maximum range of motion reactive oxygen species rate of perceived exertion repeated-sprint ability strength and conditioning series elastic component stimulus-fatigue-recovery-adaptation theory squat jump single leg hop short-latency response single leg squat self-motivate supplementary motor area strength-power potentiating complexes stretch-shortening cycle sport-specific physical training testosterone tricarboxylic acid tuck jump assessment training load thermoneutral water immersion theoretical maximal force (F0) to the theoretical velocity cautionary coach feedback vascular endothelial growth factor vertical force Very Heavy Sled vastus lateralis maximal oxygen uptake peak oxygen uptake velocity at the onset of blood lactate accumulation positive coach feedback velocity at V̇O2 max whole body cryotherapy Yo-Yo Intermittent Recovery Test
CHAPTER 1
Strength and conditioning: Coach or scientist? Perry Stewart, Paul Comfort and Anthony Turner With the growth of professionalism and the significant financial incentives (television rights, sponsorships, wages, merchandise) associated with elite sport, it is unsurprising that the demand for scientific support services is on the increase in many sports. One of the disciplines that has experienced such growth and popularity is strength and conditioning (S&C). S&C coaches are employed through government-funded organizations (national institutes of sport), educational establishments (schools, colleges and universities), professional sport clubs, commercial performance facilities and by individual athletes (Dawson et al., 2013). Fundamentally, the role of an S&C coach is to enhance athleticism and decrease the risk of sports injuries through the testing, evaluation and prescription of appropriate exercises in close collaboration with sport coaches, physiotherapists and other relevant professionals. However, despite its growing acceptance within the interdisciplinary team, S&C coach responsibilities widely vary, which is poignantly highlighted in job specifications and further complicated by the different job titles advertised, which have recently included: S&C specialist, physical preparation coach, movement specialist and performance specialist to name a few. What is known however, is the role of an S&C coach is multifaceted and that sporting performance in the context of physical preparation is influenced by much more than simply what an athlete does in the weight room or on the track/field/court. The roles and responsibilities of today’s S&C coach extending far beyond that of designing and implementing training programmes. It is pertinent for all current and aspiring S&C coaches to appreciate the breadth and depth of knowledge and skills required to effectively work in, and excel in, the discipline of S&C. Arguably the role now is a lot different to the one carried out as little as 10 years ago, and we must appreciate its evolution towards a practitioner who is just as much a scientist as a coach. Therefore, the aim of this introductory chapter is to review the necessary attributes required to be an effective practitioner within the S&C industry. This will be achieved by exploring and further exemplifying the facets of S&C coaching. It is the intention that this will in turn set the context and significance of each chapter that follows, where all these components are discussed in far greater detail.
THE COACH It is prudent to start our review at the origin of the role, coaching. The role of a coach, regardless of type (technical, S&C etc.) or sport, is to improve athletes’ physical, mental and emotional performance, in preparation for sporting competition (Dorgo, 2009). Previous conceptual models of coaching have emerged from different theoretical perspectives including leadership, expertise, coach-
athlete relationships, motivation and education, highlighting the complexity of a coach’s role – all of which are important. Côté and Gilbert (2009), define coaching effectiveness as: The consistent application of integrated professional, interpersonal and intra-personal knowledge to improve athletes’ competence, confidence, connection, and character in specific coaching contexts. This definition can be better understood when the three components of this model (knowledge, outcomes and contexts) are considered. The coach’s skills, attitudes and behaviours – collectively referred to as ‘knowledge’ – are separated into three interrelated categories: 1)
2)
3)
Professional knowledge: Expert knowledge of subject (and sport) specific theories. Within the realm of S&C this is likely to include: understanding the demands of competition; how to plan and programme components such as strength, power, speed, and metabolic conditioning; application of macro, meso and micro-cycles; principles of dynamic correspondence; how to differentiate training for different populations; and pedagogical theories. Interpersonal knowledge: To be successful, coaches have to interact effectively with their athletes, head and assistant coaches, as well as parents and other key stakeholders. This refers to the soft skills (sometimes referred to as emotional intelligence) required to identify, use, understand and manage interactions. Intrapersonal knowledge: Described as self-awareness and introspection, the ability of a coach to critically reflect. Gilbert and Trudel’s (2002) research examined good coaches and how they translate experience into knowledge and skills through reflection. In summary, a coach’s ability to maximize athletes’ outcomes rests not only on extensive professional and interpersonal knowledge, but also on constant introspection, review and revision of one’s practice (Côté and Gilbert, 2009).
Traditionally, coaches focus the majority of attention towards developing professional knowledge. Although expert knowledge of the industry and the sport is essential, it is narrow-minded to assume this component alone will lead to being an effective coach and having a successful career. In fact, it is the integration of professional knowledge, how well a coach connects with others (interpersonal skills), and how open they are to continued learning and self reflection (intrapersonal skills) that will determine how effective and successful an S&C coach will be. The second component of effective coaching focuses on ‘athlete outcomes’, which typically fall into performance gains (successful performances and player development) and positive psychological responses (high level of self esteem, intrinsic motivation, enjoyment and satisfaction). Côté and Gilbert (2009) identified four athlete outcomes, namely: competence, confidence, connection and character/caring. It is believed that the coach responsible for designing appropriate training conditions can enhance all of these. These are explained in relation to the S&C industry below: •
•
Competence: Enhanced physical capabilities. This may include improving an athlete’s movement proficiency, strength, power, speed and endurance performance. Such qualities are commonly measured and assessed using field or laboratory based tests. However, a vital consideration for any S&C coach is whether enhanced athletic ability corresponds to improved sporting performance (which is harder to objectively measure in the majority of cases). Confidence: Improved sense of overall positive self-worth. A coach and athlete should agree on
• •
achievable objectives and the coach ought to design programmes that allow the athlete to succeed. Connection: Facilitating positive bonds and social relationships inside and outside of sport. A coach can encourage communication between athlete and staff, parents and non-sport peers. Character: Encouraging moral attributes such as respect, integrity, empathy and responsibility. Encourage athletes to take responsibility for their own environment, programming and personal standards.
The third and final component of effective coaching is ‘coaching contexts’, which refers to the unique settings in which coaches work. Côté & Gilbert (2009) describe coaching effectiveness and expertise as context specific, with three classifications identified: (1) recreational, (2) developmental and (3) elite sport. Further to this, the following situational factors should be considered: (1) context (individual athlete or team sport, male or female, senior or youth populations), (2) employment type (full or part time), (3) the role (senior position or intern) and (4) the employer (amateur/professional organization, state funded or education). The context alters the focus and attention of the coach and requires a high level of specificity related to programme design and delivery. For example, an S&C coach working with a developmental team athlete with a low training age will plan, deliver and evaluate outcomes differently than if working with an elite individual athlete in a highly demanding performance environment.
SCIENCE OF COACHING It is still common to hear coaching being referred to as an ‘art’ as opposed to a science. However, there is an emerging body of research surrounding motor behaviour and skill acquisition, which scientifically underpins the use of effective communication in coaching. The primary emphasis of such research has been to examine the effects of coaching instructions, cues and feedback on attentional focus (i.e., the conscious ability to focus attention through explicit thoughts in an effort to execute a task). These studies generally reveal that communication or cues that focus the athlete’s attention internally on to bodily movements (e.g. extend your knee and ankle) evoke different results to those that cause the athlete to have an external focus (e.g. explode off the ground like a rocket). In general, providing external attentional focus results in increased ability to learn (Wulf et al., 2002), greater retention of information (Wulf, 2007) and enhanced ability to perform tasks under pressure (Bell and Hardy, 2009). In addition to motor learning outcomes, external focus instructions and cues can have positive effects on neuromuscular, physiological and psychophysical outcomes (Benz et al., 2016). Therefore, subtle differences in the way a coach communicates instructions and feedback noticeably impact the athlete’s performance, in both the short and long term. Such research provides evidence that coaching is not only an art, but embodies scientific principles, giving the term coaching science legitimacy within the coaching community.
THE SCIENTIST It is clear from criteria detailed in job specifications that the responsibilities of an S&C coach have evolved to include roles from other sport science disciplines. Before exploring the application of sport science we consider the definition of science:
Science is the “pursuit and application of knowledge and understanding, following systematic methodologies based on evidence” (sciencecouncil.org) Therefore, sport science can be thought of as a scientific process used to guide the practice of sport with the ultimate aim of improving sporting performance (Bishop et al., 2006). The British Association of Sport and Exercise Sciences (BASES) recognizes that the application of scientific principles in sport is principally achieved through one of the three branches of science: biomechanics, physiology and psychology (see Table 1.1). The importance of nutrition in sport and exercise science is evident and now recognized as an integral role within the interdisciplinary team, hence its inclusion in this chapter. The discipline of S&C is fundamentally engrained in sport science with, for example, the knowledge of programming being underpinned by the understanding of how the anatomy will adapt (physiology), how changing exercise technique can impact the kinetic chain and joint loading (biomechanics), goal setting and motivation (psychology) and advising an athlete what and when to eat to maximize performance or recovery (nutrition). However, in addition to the underpinning knowledge that allows S&C professionals to perform their primary role, coaches are progressively being expected to perform postural, gait and movement screening, testing using laboratory based equipment (e.g. force plates, isokinetic dynamometry, body composition analysis) and monitoring of physical and physiological responses (e.g. vertical jumps, heart rate, position [via GPS], rating of perceived exertion [RPE], subjective questionnaires, blood and saliva analyses). TABLE 1.1 The definition and correspondence of scientific area to the roles of a typical S&C coach (http://www.bases.org.uk/About-Sport-And-Exercise-Science) Definition
Relation to S&C
Biomechanics
An examination of the causes and consequences of – Movement analysis human movement – Athlete performance testing/profiling – Monitoring external training responses
Physiology
An examination of the way the body responds to exercise and training
– Athlete performance testing/profiling – Monitoring internal training responses – Recovery modalities
Psychology
An examination of human behavior within exercise science
– Profiling – Monitoring (questionnaires, e.g., POMS) – Goal setting
Nutrition
An examination and practice of nutrition to enhance – Fueling wellbeing and athletic performance – Hydration – Supplementation
While the availability of sport science support is increasing, funding to provide such specialist support is still relatively limited for many sports (Reid et al., 2004) and is often reserved for the elite and wealthy organizations. Although it should be noted that it is not suggested that S&C coaches will or should fill the roles of biomechanists, physiologists, psychologists or nutritionists, S&C coaches are expected to have a working understanding of, or at times even embrace the role of these professions. In effect, the role of an S&C coach is similar to that of an interdisciplinary sport and exercise scientist who attempts to utilize and integrate more than one area of sport science to solve real world problems (Burwitz et al., 1994). With the majority of S&C coaches holding a minimum of
an undergraduate level degree in an exercise science discipline such as sport and exercise science (Hartshorn et al., 2016), it is perhaps unsurprising as to why the professional S&C coach is expected to absorb these roles. It is also hard to say whether these growing responsibilities were academia led (noting that degrees in S&C teach would-be coaches these skills as though they are required to succeed), or a reflection of the economic status of the organization. In addition to having sound professional knowledge of a broad range of scientific areas and their practical application, the S&C coach is commonly expected to perform data analysis. Due to the evidence-based environments in which S&C coaches work, the ability to run statistical analyses using appropriate platforms (Excel, SPSS, etc.), is becoming increasingly important. Such skills enable the S&C coach to identify the success or failure of an intervention, to recognize meaningful changes and trends and that ultimately inform best practice. Furthermore, this information must be interpreted, filtered and communicated to technical coaches, support staff, athletes and parents in a way that is relevant and meaningful. This requires the S&C coach to firstly, be competent at completing the required analysis and secondly, have adequate interpersonal knowledge to communicate the results within the correct sporting context.
PERFORMANCE LIFESTYLE: NON-CONTACT COACHING Since the dawn of professionalization in elite sport, and the subsequent increased commercial attention and financial incentives (for both athlete and organization), performance outcomes (success of team/individual, win/loss ratio, player development) have become of paramount importance. Nurturing an athlete is now far detached from the traditional ideology that the individual need only focus on technical/tactical refinement and physical enhancement, all of which can be achieved during training sessions. It is now expected that professionals such as S&C coaches influence lifestyle through the education of athletes to capitalize on the non-contact hours that were once unaccounted for; in essence, there is now a need for non-contact coaching. A term that embraces this concept is ‘marginal gains’, which was coined and popularized by Sir Dave Brailsford who experienced great success as the performance director of GB Cycling at the 2012 Olympics. Marginal gains refer to the aggregation of a number of small gains that result in a large gain in overall performance. Brailsford sums it up as “put simply… how small improvements in a number of different aspects of what we do can have a huge impact on the performance of the team” (Slater, 2012). Clive Woodward describes using a similar concept when leading the England Rugby team to World Cup victory in 2003. Woodward employed a strategy of improving ‘critical non-essentials’ (CNe). This approach focused on improving the small details of everything in the preparation and playing of the team. It is worth noting, however, that many athletes need to focus on the development of the basics first, and that such approaches as those mentioned above should be used with highly developed athletes only. Although many of the approaches used within elite sport are outside the control of S&C coaches (for example, development of technology, organizational culture, competition schedule, travel arrangements, etc.), many alterations to daily lifestyle can be prescribed or controlled, these may include: recovery modalities, sleep hygiene, strategies to reduce risk of infection, ergonomics of equipment and travel, dealing with travelling across time zones, etc. All of the aforementioned are concepts rooted in scientific rationale and are designed and implemented to gain small advantages. The S&C coach must now be constantly investigating ways to improve physical outcomes, positive psychology, training environment and performance lifestyle for athletes to truly gain a competitive
edge. However, although slight advantages can be achieved via small modifications, these are only meaningful if the S&C coach has successfully implemented key concepts, such as appropriate analysis, planning, coaching, monitoring and recovery.
CONSIDERATIONS FOR A MODERN DAY S&C COACH An S&C coach must consider a multitude of factors before commencing a working relationship with an athlete. Crudely, these can be categorized into: analysis, planning, coaching, monitoring and recovery (before returning back to analysis) (see Figure 1.1). Below is a non-exhaustive list of some of the elements that may need to be considered when working with athletes:
Analysis (& re-analysis) • • • •
Athlete Background/Objective: short, medium, long term objectives? How to monitor success or failure? Injury history? Training age? Biological age? Preferences? Sport/Competition Demands: How many games/tournaments? Priority games/tournaments? How long is the season? Travel demands? Physical demands (how far and fast, etc.)? Injury prevalence within sport/population, including common mechanisms of injury? Postural and Movement Screening: What type of movement screen? For what reason are you screening? What are the movement dysfunctions? What drives movement dysfunction? Implications on transfer of force through the kinetic chain and injury prevalence? Physical Performance Testing: Determining successful athletic factors in the sport? Strength/power/speed/agility/endurance tests? Laboratory or field based testing? Reliability? Validity of test? How to interpret and present results?
FIGURE 1.1
Considerations for a modern day S&C coach before commencing a working relationship with an athlete.
Planning (within context)
• • • •
Periodization: Linear or non-linear? How to structure macro, meso and micro cycles? Knowing when to overload and when to taper and when to rest? How to structure technical sessions? Exercise Programming: Training methods? Associated adaptations? Exercise selection? Exercise sequence (concurrent or single stimulus)? Prescription of training loads? Rehabilitation/Prehabilitation: Methods and exercises to tackle high risk groups/muscles/joints? When to apply prehabilitation strategies? Return to play/competition strategies? Remedial/preparatory exercise? Non-Contact Coaching: Nutritional guidance? Sleep hygiene? Strategies to reduce the risk of infection? How to prepare for different time zones, climates, surfaces?
Coaching •
•
• •
Professional Knowledge: How to apply fundamental training principles? Dynamic correspondence of training? Understanding of sport/competition rules, regulations and physical demands? Knowledge of skill acquisition and pedagogical theory? Which method of training and coaching style induces optimal physical and psychological response (might be different at different times)? Interpersonal Knowledge: How do you communicate with athletes, coaches and other stakeholders? Awareness of verbal cues (internal vs. external) and non-verbal communication? How do athletes best retain information? Are you able to adapt the programme in relation to how the athlete is feeling? Intrapersonal Knowledge: Do you evaluate sessions? How do you evaluate? Does it inform future practice? Open and willing to try new ideas? Confidence, Connection, Character: Do you understand what motivates your athlete/s? How to install confidence? How to be a role model and leader? How can you install good habits that transfer into wider society? How to create a performance environment?
Monitoring •
Monitor training load (TL) and responses to TL: Internal methods? External methods? Methods to assess response to training? Performance tests? Physiological markers? Psychological assessments? Wellbeing? Are the metrics/markers/questions sensitive enough to detect meaningful changes? Determining differences between functional overreaching (FO), nonfunctional overreaching (NFO), overtraining (OT)? Data analysis – reliability? Validity? Statistical significance/meaningful changes (magnitude based inferences)? What, how and who to report the information? What actions are required as a result?
Recovery •
Do we need to use recovery strategies at this point? What is the aim of recovery strategy? What are the best strategies? When to apply? Should everyone use the same recovery strategy? Are they proactively planned or reactive to environment? Physiological and psycho-social response?
(Return to analysis.)
CONCLUSION S&C is a relatively new support service within the interdisciplinary team in elite sport. It is clear that the role of an S&C professional is multifaceted (see Figure 1.2) and fundamentally requires effective attitudes, behaviours and skills of coaching and the understanding and application of various sport science disciplines to be successful. Kraemer (1990) recognizes additional skills such as organization, administration, athlete motivation, education and public relations as integral to the role. Although traditionally a coach may value professional knowledge above all else, high levels of interpersonal knowledge within sport-specific contexts is essential to be able to constantly interact with athletes, coaches, support staff and other stakeholders. In an era where millions of pounds are at stake and the difference between being on and off the podium are separated by mere fractions of a second, a largely evidence-based culture has evolved. S&C coaches must analyse, interpret and influence decision-making using facts and figures, as hunches or instincts are becoming increasingly more difficult to justify to technical coaches and managers, and can rarely promote change when change is needed. Thus in summary, the discipline of S&C requires the individual to be both an effective coach and an interdisciplinary sport scientist. These required skill sets should be embraced and seen as essential if the S&C coach is to truly excel. Therefore, due to the breadth and depth of knowledge and skills required, it may be suggested that S&C coaches should strive to be excellent ‘generalists’ and only consider being a ‘specialist’ once the basics have been mastered. The following chapters provide a greater in-depth analysis of these areas and are an important part of appreciating the role of the modern day S&C coach. These chapters will be principally structured into two sections: (1) an objective and concise review of pertinent literature in the specific subject area, and (2) a discussion (including applied examples) of context-specific practical applications.
FIGURE 1.2
The multi-faceted nature of strength and conditioning.
REFERENCES Bell, J.J. and Hardy, J., 2009. Effects of attentional focus on skilled performance in golf. Journal of Applied Sport Psychology, 21(2), pp. 163–177. Benz, A., Winkelman, N., Porter, J. and Nimphius, S., 2016. Coaching instructions and cues for enhancing sprint performance. Strength & Conditioning Journal, 38(1), pp. 1–11. Bishop, D., Burnett, A., Farrow, D., Gabbett, T. and Newton, R., 2006. Sports-science roundtable: does sports-science research influence
practice? International Journal of Sports Physiology and Performance, 1(2), pp. 161–168. Burwitz, L., Moore, P.M. and Wilkinson, D.M., 1994. Future directions for performance – related sports science research: An interdisciplinary approach. Journal of Sports Sciences, 12(1), pp. 93–109. Côté, J. and Gilbert, W., 2009. An integrative definition of coaching effectiveness and expertise. International Journal of Sports Science & Coaching, 4(3), pp. 307–323. Dawson, A.J., Leonard, Z.M., Wehner, K.A. and Gastin, P.B., 2013. Building without a plan: The career experiences of Australian strength and conditioning coaches. The Journal of Strength & Conditioning Research, 27(5), pp. 1423–1434. Dorgo, S., 2009. Unfolding the practical knowledge of an expert strength and conditioning coach. International Journal of Sports Science & Coaching, 4(1), pp. 17–30. Gilbert, W.D. and Trudel, P., 2002. Learning to coach through experience: Reflection in model youth sport coaches. Journal of Teaching in Physical Education, 21(1), pp. 16–34. Hartshorn, M.D., Read, P.J., Bishop, C. and Turner, A.N., 2016. Profile of a strength and conditioning coach: Backgrounds, duties, and perceptions. Strength & Conditioning Journal, 38(6), pp. 89–94. http://www.bases.org.uk/About-Sport-and-Exercise-Science Kraemer, W. J. 1990. A fundamental skill of the profession. National Strength & Conditioning Journal, 12(6), pp. 72–73. Reid, C., Stewart, E. and Thorne, G., 2004. Multidisciplinary sport science teams in elite sport: Comprehensive servicing or conflict and confusion? The Sport Psychologist, 18(2), pp. 204–217. Slater, S., Olympics cycling: marginal gains underpin Team GB dominance. www.BBC.com, 8 August 2012. http://www.bbc.co.uk/sport/olympics/19174302 Wulf, G., 2007. Internal versus external focus instructions. In: Wulf, G., 2007. Attention and Motor Skill Learning. Human Kinetics: Champaign, IL, pp. 35–81. Wulf, G., McConnel, N., Gärtner, M. and Schwarz, A., 2002. Enhancing the learning of sport skills through external-focus feedback. Journal of Motor Behaviour, 34(2), pp. 171–182.
PART 1 Developing your athlete
CHAPTER 2
Developing muscular strength and power Timothy J. Suchomel and Paul Comfort
INTRODUCTION This chapter discusses the importance of muscular strength and power with regard to sport performance, physiological underpinnings, and various methods of improving these qualities in athletes. While basic concepts of periodisation and programming for improving strength and power characteristics will be mentioned within this chapter, more thorough discussions can be found in Chapter 8, as well as Bompa and Haff (2009), DeWeese et al. (2015a, 2015b), and Stone et al. (1982).
SECTION 1 THE IMPORTANCE OF MUSCULAR STRENGTH AND POWER FOR ATHLETES Muscular strength is defined as the ability to exert force on an external resistance (Stone, 1993). Based on the demands of a sport/event, an athlete may have to manipulate their own body mass against gravity (e.g. sprinting, gymnastics, etc.), both their body mass and an opponent’s body mass (e.g. rugby, wrestling, etc.), or an external object (e.g. soccer, weightlifting, etc.). Ultimately, the force exerted will change or tend to change the motion of a body in space. This concept is based on Newton’s second law (i.e. law of acceleration) whereby force (f) is equal to the product of mass (m) and acceleration (a) (f = ma). Based on this principle, the acceleration of a given mass is directly proportional, and in the same direction of, the force applied. Thus, it appears that muscular strength is the primary factor for producing an effective and efficient movement of an athlete’s body or an external object. This concept has been supported throughout the literature as muscular strength has been correlated to greater rate of force development (RFD), power, jumping, sprinting, change of direction, sport-specific skills, and postactivation potentiation (PAP) magnitude (Suchomel et al., 2016b). Previous literature indicated that both RFD and power output are two of the most important characteristics regarding an athlete’s performance (Baker, 2001b; Stone et al., 2002; Morrissey et al., 1995). Given that muscular strength serves as the foundation upon which other abilities can be enhanced, it should come as no surprise that greater magnitudes of RFD and power output are byproducts of increased strength.
Rate of force development Rate of force development may be defined as the change in force divided by the change in time. Regarding sport performance, the ability to rapidly produce force is critical given the time constraints of various tasks. This notion is supported by evidence that suggests that it takes individuals a longer period of time (>300ms) to produce their maximum force (Aagaard et al., 2002a; Aagaard, 2003) compared to the duration of jumping and ground contact time during sprinting (Andersen and Aagaard, 2006). As mentioned above, increases in muscular strength enhance an athlete’s ability to increase their force magnitude and RFD. Previous research has demonstrated that resistance training may enhance an athlete’s RFD characteristics, which may lead to improved performance (Aagaard et al., 2002a; Andersen et al., 2010; Häkkinen et al., 1985). A recent review provided evidence that RFD, along with greater muscular strength, may underpin the development of greater power output (Taber et al., 2016) (Figure 2.1).
Power output As mentioned above, alongside RFD, power output is considered to be one of the most important characteristics regarding an athlete’s performance. Power output may be defined as the rate of work performed. Any given sport task requires the completion of a given amount of mechanical work.
While the work performed is important, athletes have limited time to perform these tasks and thus it would seem beneficial to complete the work as fast as possible. For example, an athlete who completes the required work of a given task more quickly may be given a competitive edge compared to their opponent (e.g. rebound in basketball) or may win the overall competition (e.g. 100m sprint). Previous research has indicated that power output differs between the playing level of athletes (Fry and Kraemer, 1991; Baker, 2001a; Hansen et al., 2011) and between starters and non-starters in various sports (Young et al., 2005; Fry and Kraemer, 1991; Gabbett, 2009). Further research has noted strong relationships between power output and performance characteristics such as sprinting (Weyand et al., 2010; Weyand et al., 2000), jumping (Hori et al., 2008; Newton et al., 1999), change of direction (Nimphius et al., 2010; Spiteri et al., 2012), and throwing velocity (McEvoy and Newton, 1998; Marques et al., 2011). Given the importance of power output to an athlete’s success, many strength and conditioning practitioners have sought to improve these qualities through various training strategies. Common training strategies that have been used to enhance power output will be discussed in second half of this chapter.
MORPHOLOGICAL FACTORS AFFECTING STRENGTH AND POWER Cross-sectional area Previous literature has indicated that an increase in an athlete’s muscle cross-sectional area (CSA) and work capacity (i.e. force production capacity) may lead to an enhanced ability to increase their muscular strength (Minetti, 2002; Zamparo et al., 2002; Stone et al., 1982). Typically, this is achieved via a resistance training phase that includes a high volume of work completed with moderate to moderately high intensities (60–80% 1RM). Greater detail will be provided in second half of this chapter.
FIGURE 2.1
Comparison of force, power, RFD and movement time between stronger and weaker athletes during a countermovement jump.
An increase in muscle fibre CSA results in an increased size of the overall muscle (hypertrophy). From a physiological perspective, increases in muscle CSA lead to improved force production due to an increased number of newly formed sarcomeres. Simply put, an increase in the number of
sarcomeres (i.e. smallest contractile unit within muscle cell) increases the number of potential interactions between actin and myosin microfilaments (i.e. cross-bridges) which ultimately increases the force a muscle can produce. This is supported by research from Kawakami et al. (1993) which indicated that muscle fibre pennation angles are greater in hypertrophied muscles. A greater pennation angle permits a greater number of cross-bridge interactions to occur within a given area of the muscle, due to the packing of muscle fascicles within the area (Figure 2.2).
FIGURE 2.2
Medial gastrocnemius (MG) fascicle length (dashed line) and MG pennation angle (θ), as measured between the superficial (A) and deep (B) MG aponeuroses.
Another influence on the CSA of muscle fibres is the ratio of Type II:I fibres. Previous research indicated that an increased CSA following resistance training coincided with a greater Type II:I ratio due to a greater rate of hypertrophy of Type II muscle fibres compared to Type I fibres (Campos et al., 2002). Additional research noted that a greater percent change in Type II:I ratio following eight weeks of resistance training strongly correlated with the percent change of squat jump power (Häkkinen et al., 1981). Thus, it appears that an increased CSA coinciding with a greater Type II:I ratio may increase the ability to generate power by altering the force-velocity characteristics of the muscle. However, it should be noted that the training modality will greatly impact which motor units will be recruited and thus affect which muscle fibres (e.g. Type I, IIa, IIx) adapt to the training stimulus. The training modality may also affect how additional sarcomeres are added. For example, high force training (i.e. resistance training) may result in increases in a muscle’s CSA by adding sarcomeres in parallel (Figure 2.3), which may increase the overall force produced by the muscle given that each sarcomere acts independently. In contrast, high velocity training, e.g., plyometrics (discussed in detail in Chapter 16), may add sarcomeres in series (Figure 2.4), which may increase shortening velocity at the expense of force production given that the sarcomeres in series pull against each other. This concept is important to consider given the demands of athletes in various sports.
FIGURE 2.3
Four sarcomeres in parallel. Adapted from Stone et al. (2007).
FIGURE 2.4
Four sarcomeres in series. Adapted from Stone et al. (2007).
Muscle architecture While the overall size of the muscle may affect the magnitude of force produced, additional muscle architecture characteristics may affect muscle tension. A muscle’s pennation angle may be defined as the angle in which the fascicles (i.e. bundle of muscle fibres) attach to the superficial or deep aponeurosis (Figure 2.2). The muscle’s pennation angle will determine the force-velocity characteristics of the muscle. For example, a greater pennation angle will allow the muscle to place a greater emphasis on force due to the ability to pack more muscle fascicles into a given area, leading to a greater number of cross-bridge interactions and enhanced force production (Huxley, 1974). In contrast, a smaller pennation angle will place a greater emphasis on velocity due to the position of the fascicles being more parallel in relation to the muscle’s aponeuroses, leading to a greater shortening velocity due to the combined shortening of sarcomeres across the area of the muscle belly. A number of studies have assessed longitudinal changes in muscle architecture (i.e. muscle thickness, pennation angle, and fascicle length) following various resistance training programs, illustrating that changes in muscle architecture may affect performance outcomes. For example, Nimphius et al. (2012) indicated that moderate increases in fascicle length following resistance training were strongly correlated with sprint times to first and second base from home plate in elite softball players. Additional research observed increases in muscle thickness and pennation angles following heavy strength training (Aagaard et al., 2001; Kawakami et al., 1995). Such adaptations may be favorable when it comes to producing greater overall magnitudes of force within the muscle. Further research indicated that training with relatively high velocity muscle actions and lighter loads (1RM). Another aspect to consider with eccentric training is the type of movement(s) the athlete is able to perform. For example, much of the previously discussed literature within this section has focused on eccentric-only movements. However, a growing body of literature has examined another type of eccentric training, termed accentuated eccentric. Accentuated eccentric training involves performing the eccentric phase of a lift with a heavier load than the concentric phase as a result of a portion of the load being removed by a weight release system (Ojasto and Häkkinen, 2009), spotters (Brandenburg and Docherty, 2002), the athlete dropping it (Sheppard et al., 2008), or flywheel (de Hoyo et al., 2015) at the end of the eccentric phase. Collectively, the previous studies provide evidence that accentuated eccentric training may produce greater adaptations in explosive performance characteristics (i.e. jumping, sprinting, and concentric power). Although a limited body of literature exists, it appears that accentuated eccentric training may provide an effective training stimulus to improve an athlete’s strength-power performance.
Complex training & strength-power potentiation complexes Complex training (CT) is a training modality that involves completing a resistance training exercise prior to performing a ballistic exercise that is biomechanically similar (Robbins, 2005). For example, back squats may be paired with countermovement jumps, while the bench press may be paired with bench press throws. CT may allow athletes to perform high force or power exercises at a higher intensity compared to traditional training (Verkhoshansky, 1986; Ebben et al., 2000), ultimately creating a superior training stimulus. In theory, CT may result in greater strength and speed adaptations compared to traditional resistance training methods longitudinally by providing a broader range of training stimuli (Ebben and Watts, 1998; Jones and Lees, 2003). A topic of frequent research that uses CT principles is postactivation potentiation (PAP). PAP is defined as an acute enhancement in performance as a result of the muscle’s contractile history (Robbins, 2005). Training complexes designed to produce a potentiated state are termed strengthpower potentiating complexes (SPPCs) (Robbins, 2005; Stone et al., 2008). SPPCs involve performing a high force or high power movement that is used to potentiate the performance of a subsequent high velocity or power movement. While a number of studies have demonstrated that various potentiation stimuli may acutely enhance strength-power performance (Gullich and Schmidtbleicher, 1996; Young et al., 1998; Bullock and Comfort, 2011), a number of factors within the SPPC or the athlete’s characteristics may affect the magnitude of potentiation produced (Suchomel et al., 2016a). Thus, it is not surprising that similar SPPCs resulted in no change or a decrease in subsequent performances in other studies (Tsolakis and Bogdanis, 2011; Jensen and Ebben, 2003; Till and Cooke, 2009). While the concept of implementing SPPCs within an athlete’s resistance training programs is appealing, limited research has examined the longitudinal effects of training with SPPCs (Docherty and Hodgson, 2007). In addition, practitioners should note that the use of SPPCs may not be as appropriate for weaker individuals as greater muscular strength may lead to faster and greater potentiation (Suchomel et al., 2016d; Seitz et al., 2014; Miyamoto et al., 2013). Finally, it should be noted that the long-term use of SPPCs may not be appropriate given the goals of specific resistance training phases. For example, implementing SPPCs may be specific to the goals of a strength-speed phase, but actually counterproductive during a strength-endurance phase.
Unilateral vs. bilateral training Some practitioners may argue that unilateral exercises may be more sport-specific given the unilateral weight bearing phase of various sport tasks (e.g. sprinting, cutting tasks, etc.). Thus, a frequent topic of discussion within the strength and conditioning field is the use of unilateral exercises compared to bilateral exercises. Unilateral/partial unilateral movements may be defined as those where the resistance is unevenly distributed between an individual’s limbs, whereas bilateral movements are those where the resistance is distributed evenly, for the most part, between an individual’s limbs (McCurdy et al., 2005). The vast majority of resistance training programs implement predominantly bilateral exercises for strength and power development. This is not surprising given that strong relationships exist between bilateral strength and sprinting, jump height and peak power, and change of direction performance (Suchomel et al., 2016b). However, in order to provide practitioners with a variety of options for exercise prescription, further discussion on unilateral exercise is needed. Several studies have compared the training effects of unilateral and bilateral training. McCurdy et al. (2005) examined the strength and power adaptation differences following eight weeks of unilateral
or bilateral strength training and plyometric exercise in untrained subjects. Their results indicated that both groups improved to a similar extent, suggesting that either mode of training may be equally as effective. Similar results from another study indicated that both unilateral and bilateral plyometric training improved both countermovement jump (CMJ) and alternate leg bounding performance in previously untrained females (Makaruk et al., 2011). However, the authors also noted that only the bilateral training group retained their training adaptations following a four week detraining period. A more recent study indicated that similar improvements in unilateral and bilateral strength, sprint speed, and agility were displayed by Academy rugby players following five weeks of either training with the rear foot elevated split squat or traditional back squat exercise (Speirs et al., 2016). Collectively, the previous studies indicate that training with unilateral exercises may be an effective alternative to bilateral exercises when it comes to improving various performance parameters. Previous literature has indicated that gluteus medius, hamstring, and quadriceps activation was greater during a modified split squat compared to a traditional bilateral squat (McCurdy et al., 2010). This should not be overly surprising given the decreased stability of unilateral exercises. However, decreased stability may be viewed as a limitation because it is difficult to prescribe heavy loads with unilateral exercises. Given that greater stability within a movement may lead to a greater potential to express force (Behm and Anderson, 2006), it would appear that bilateral exercises may serve as a better foundation for improving an athlete’s strength-power characteristics. However, that is not to say that unilateral exercises should not be programmed; rather, they should be implemented as assistance exercises to bilateral lifts, especially during the general preparatory phase of training.
Variable resistance training Traditional resistance training methods typically involve performing exercises with an eccentric and concentric component in which the external load remains constant throughout the entire range of motion. While this type of training has become an essential addition to training programs, it is not without its limitations. For example, an athlete performing a back squat may be limited at the lowest point of their squat due to a decreased capacity to produce force in that position. As a result, athletes may experience a “sticking point” when they begin to ascend due to mechanical disadvantages being present within the active musculature. In contrast, muscle force production continues to increase and peaks during the top portion of the squat. Based on this description of the back squat, it would appear that a method of training that trains each portion of the lift based on its mechanical advantage/disadvantage would be beneficial. Variable resistance training refers to a training method that alters the external resistance during the exercise in order to maximize muscle force throughout the range of motion (Fleck and Kraemer, 2014). Traditionally, this method of training involves the use of chains or elastic bands during exercises such as the back squat (Figure 2.6) or bench press (Figure 2.7). The addition of chains or elastic bands may alter the loading profile of an exercise (Israetel et al., 2010), which may allow the athlete to match changes in joint leverage (Zatsiorsky, 1995) and overcome mechanical disadvantages at various joint angles (Ebben and Jensen, 2002; Wallace et al., 2006). Support for this method of training comes from a meta-analysis that indicated that greater strength gains were produced during the bench press exercise following variable resistance training compared to traditional methods (Soria-Gila et al., 2015). While additional training studies are needed, it appears that variable resistance training may be used as an effective training tool for developing muscular strength and power.
Kettlebell training Another form of resistance training that has gained popularity is the use of kettlebell exercises. Kettlebells are implements that consist of a weighted ball and handle (Cotter, 2014). Among other movements, individuals have used kettlebells in a variety of ways including swings, goblet squats, accelerated swings, and modified weightlifting exercises such as a snatch for the purposes of developing strength and power. Previous research has indicated that kettlebell training may improve various measures of muscular strength (Otto III et al., 2012; Lake and Lauder, 2012; Jay et al., 2011; Manocchia et al., 2013; Jay et al., 2013) and explosive performance as measured by vertical jumping (Otto III et al., 2012; Lake and Lauder, 2012) and clean and jerk three repetition maximum (RM) (Manocchia et al., 2013). However, it should be noted that two other studies indicated that vertical jump (Jay et al., 2013) and sprint performance (Holmstrup et al., 2016) were not enhanced following kettlebell training when compared to a control group, indicating that not all research supports the use of kettlebells as a strength training modality.
FIGURE 2.6
Back squat exercise using variable resistance with chains.
FIGURE 2.7
Bench press exercise using variable resistance with elastic bands.
The majority of available research suggests that kettlebell training may provide an effective strength-power training stimulus. However, it should be noted that more traditional methods of training, such as weightlifting, may provide superior adaptations when it comes to improving maximal strength and explosiveness (Otto III et al., 2012). This may in part be due to overload that may be
placed on the body. For example, athletes training with weightlifting movements may be able to clean and jerk 100kg; however, it may be difficult to perform a kettlebell swing with the same load using proper technique. Further research examining kettlebell training is needed to determine its role within strength and conditioning programs.
BALLISTIC VS. NON-BALLISTIC The intent of performing an exercise may alter a given training stimulus. Ballistic exercises (i.e. those that accelerate throughout the entire concentric movement) may lower the recruitment threshold for motor units (van Cutsem et al., 1998, Desmedt and Godaux, 1977) and allow the entire motor neuron pool to be activated within a few milliseconds (Duchateau and Hainaut, 2003). Based on the discussion provided earlier in this chapter, recruiting a greater number of motor units will ultimately lead to greater magnitudes and rates of force production. This notion is supported by previous research that indicated that ballistic exercises produced greater force, velocity, power, and muscle activation compared to the same exercises performed quickly (Lake et al., 2012, Newton et al., 1996). Additional research indicates that ballistic movements may also produce superior potentiation effects compared to non-ballistic exercises (Suchomel et al., 2016c). The superiority of ballistic exercises to produce greater training stimuli is displayed in Table 2.2, where the ballistic exercises (e.g. weightlifting movements) produce greater relative power outputs compared to traditional/nonballistic resistance training exercises (e.g. back squat, bench press, etc.). Due to the potential training benefits of ballistic-type exercises, it should come as no surprise that practitioners often implement these exercises throughout the training year. However, it should be noted that the goals of each training phase will often dictate which exercises are prescribed.
LOADING CONSIDERATIONS Training to failure Training with heavy loads will ultimately lead to increases in muscular strength. A method of training that emphasises this idea is training with loads that result in failure on the final repetition. The theory behind this method is that training with RM loads will lead to greater overall adaptations in strength compared to training with submaximal loads. However, a previous meta-analysis indicated that training to failure does not elicit greater strength gains compared to not training to failure (Peterson et al., 2005). This is supported by a second meta-analysis that stated that training to failure may be unnecessary when it comes to maximising muscular strength (Davies et al., 2016). The authors noted that if training to failure is incorporated into training programs, it should be used sparingly in order to limit the risks of injuries and overtraining. While training to failure likely stimulates the recruitment of high threshold motor units, this type of training cannot be sustained for long periods of time. Certainly there are periods where the primary emphasis may be lifting very heavy loads (90–95% 1RM) to improve maximal strength qualities; however, it does not appear that training to failure is a required element in an athlete’s resistance training program.
Combining heavy and light loads
Training for maximal strength and power requires the use of a variety of loads. Specific to strength gains, heavier loads will likely provide a training stimulus that will enhance the magnitude and rate of force production of an athlete. In contrast, training to enhance maximal power production requires the use of a range of loads that train the entire force-velocity curve (Haff and Nimphius, 2012). The training loads implemented with various exercises should complement the exercises that are being used. For example, heavier loads may be used with core exercises (e.g. squats, presses, and pulls) and certain weightlifting movements (e.g. power clean, pull from the floor, mid-thigh pull) that emphasise high force production, while lighter loads may be prescribed for more ballistic movements that emphasise high velocities (e.g. jump squat, jump shrug, bench press throws). However, as mentioned above, combination loading may also be achieved through the implementation of both weight training (high force) and plyometrics (high velocity). Suchomel et al. (2017) discussed this concept using weightlifting derivatives. It should be noted that a combination loading stimulus may also be achieved across each microcycle (e.g. week of training) and session of training. Over the course of an individual microcycle, the same exercises may be implemented throughout the week; however, the exercises are prescribed using a “heavy day/light day” loading concept. A recent review discussed this method of programming for track and field athletes (DeWeese et al., 2015b). In addition, Harris et al. (2000) displayed that a combination loading group performed back squats at 80% 1RM on their heavy day and back squats at 60% 1RM on their light day. Similarly, achieving a combined loading stimulus within a single training session is realised through the combination of working sets as well as warmup and warm-down sets of each exercise.
Optimal loads Some literature supports the idea of training at or near the load that maximises power production, termed the “optimal load” (Kawamori & Haff, 2004). In theory, optimal loads provide an ideal combination of force and velocity magnitudes that produce high power outputs. However, it should be noted that a number of factors may affect optimal loads. For example, recent research indicated that the optimal load or range of loads for the greatest power output is exercise specific for both upper (Soriano et al., 2016) and lower body exercises (Soriano et al., 2015). Additional literature suggests that the load that maximises power may be specific to the system (athlete plus barbell), barbell, or joint (McBride et al., 2011), indicating that it may be necessary to train with a range of loads, especially as an athlete gets stronger (Stone et al., 2003). Collectively, it appears that training near or at optimal loads may be beneficial from a power development standpoint. However, the extant literature supports the notion that practitioners should prescribe a range of loads instead of a single load in order to train both low and high force power characteristics during different exercises (Haff and Nimphius, 2012).
TRAINING STATUS An athlete’s training status may dictate 1) what exercises and loads the individual can tolerate and 2) what their training emphasis should be. As with any type of training, practitioners should be mindful of an athlete’s abilities as exercise competency will dictate whether or not it is appropriate to implement certain exercises or progress using various training modalities.
Because muscular strength serves as a foundation for a number of other abilities (Suchomel et al., 2016b), the training emphasis for weaker and/or less well-trained athletes should focus on increasing maximal strength. Too often practitioners place an emphasis on high velocity or power training without developing the necessary strength characteristics that will allow the athletes to exploit power-type training more extensively. That is not to say that power-type exercises such as weightlifting movements and plyometrics should not be prescribed to a weaker athlete, but they may not be featured as exclusively until an athlete increases their baseline strength levels using core movements such as squats, presses, and pulls. While the emphasis of training for weaker and/or less well-trained individuals may be on gaining maximal strength, the emphasis of training for stronger/well-trained athletes may be modified. Previous literature indicated that although strength influences an athlete’s performance, the degree of this influence may diminish when athletes maintain high levels of strength (Kraemer and Newton, 2000). Therefore, the likely magnitude of potential adaptation for increasing strength is reduced as an athlete’s maximal strength increases. As a result, additional literature has indicated that after achieving specific standards of strength (parallel back squat ≥2 x body weight as the barbell load), an athlete’s training emphasis may shift towards power-type or RFD training while maintaining or increasing their strength levels (Stone et al., 2007, DeWeese et al., 2015b). Specifically, achieving a high baseline level of strength may allow an athlete to maximize the benefits of incorporating training modalities such as plyometrics, ballistic exercises, and CT.
SUMMARY Muscular strength is defined as the ability to exert force on an external object and is considered to be the primary factor for greater RFD and power. It is important that adequate strength development is the primary, although not exclusive, focus of training initially, before progressing to power-type training once an athlete’s strength increases. By achieving a high level of muscular strength, athletes may increase their RFD, power, and athletic performance, while also decreasing the risk of injury (Suchomel et al., 2016b). Both morphological and neuromuscular factors may affect the development of muscular strength and power. Morphological factors include muscle cross-sectional area and architecture while neuromuscular factors include motor unit recruitment, rate coding, motor unit synchronisation, and neuromuscular inhibition. From a practical standpoint, the periodisation model, modality of resistance training, prescribed loads, and training status may directly affect muscular strength and power adaptations and training emphases. The training programs of weaker individuals should focus on improving muscular strength before too much emphasis is placed on power. In contrast, stronger athletes may shift to a power emphasis while maintaining or improving their strength level.
REFERENCES Aagaard, P. 2003. Training-induced changes in neural function. Exerc Sport Sci Rev, 31, 61–67. Aagaard, P., Andersen, J. L., Dyhre-Poulsen, P., Leffers, A. M., Wagner, A., Magnusson, S. P., Halkjær-Kristensen, J. & Simonsen, E. B. 2001. A mechanism for increased contractile strength of human pennate muscle in response to strength training: changes in muscle architecture. J Physiol, 534, 613–623. Aagaard, P., Simonsen, E. B., Andersen, J. L., Magnusson, P. & Dyhre-Poulsen, P. 2002a. Increased rate of force development and neural drive of human skeletal muscle following resistance training. J Appl Physiol, 93, 1318–1326. Aagaard, P., Simonsen, E. B., Andersen, J. L., Magnusson, P. & Dyhre-Poulsen, P. 2002b. Neural adaptation to resistance training:
changes in evoked V-wave and H-reflex responses. J Appl Physiol, 92, 2309–2318. Aagaard, P., Simonsen, E. B., Andersen, J. L., Magnusson, S. P., Halkjær-Kristensen, J. & Dyhre-Poulsen, P. 2000. Neural inhibition during maximal eccentric and concentric quadriceps contraction: effects of resistance training. J Appl Physiol, 89, 2249–2257. Alegre, L. M., Jiménez, F., Gonzalo-Orden, J. M., Martín-Acero, R. & Aguado, X. 2006. Effects of dynamic resistance training on fascicle length and isometric strength. J Sports Sci, 24, 501–508. Allerheiligen, B. & Rogers, R. 1995. Plyometrics program design. Strength Cond J, 17, 26–31. Andersen, L. L. & Aagaard, P. 2006. Influence of maximal muscle strength and intrinsic muscle contractile properties on contractile rate of force development. Eur J Appl Physiol, 96, 46–52. Andersen, L. L., Andersen, J. L., Zebis, M. K. & Aagaard, P. 2010. Early and late rate of force development: differential adaptive responses to resistance training? Scand J Med Sci Sports, 20, e162–e169. Anderson, K. & Behm, D. G. 2005. Trunk muscle activity increases with unstable squat movements. Can J Appl Physiol, 30, 33–45. Arabatzi, F. & Kellis, E. 2012. Olympic weightlifting training causes different knee muscle-coactivation adaptations compared with traditional weight training. J Strength Cond Res, 26, 2192–2201. Augustsson, J., Esko, A., Thomeé, R. & Svantesson, U. 1998. Weight training of the thigh muscles using closed versus open kinetic chain exercises: a comparison of performance enhancement. J Orthop Sports Phys Ther, 27, 3–8. Baker, D. 2001a. Comparison of upper-body strength and power between professional and college-aged rugby league players. J Strength Cond Res, 15, 30–35. Baker, D. 2001b. A series of studies on the training of high-intensity muscle power in rugby league football players. J Strength Cond Res, 15, 198–209. Behm, D. G. & Anderson, K. G. 2006. The role of instability with resistance training. J Strength Cond Res, 20, 716–722. Blackburn, J. R. & Morrissey, M. C. 1998. The relationship between open and closed kinetic chain strength of the lower limb and jumping performance. J Ortho Sports Phys Ther, 27, 430–435. Blazevich, A. J., Cannavan, D., Coleman, D. R. & Horne, S. 2007. Influence of concentric and eccentric resistance training on architectural adaptation in human quadriceps muscles. J Appl Physiol, 103, 1565–1575. Blazevich, A. J., Gill, N. D., Bronks, R. & Newton, R. U. 2003. Training-specific muscle architecture adaptation after 5-wk training in athletes. Med Sci Sports Exerc, 35, 2013–2022. Bobbert, M. F. & Van Soest, A. J. 1994. Effects of muscle strengthening on vertical jump height: a simulation study. Med Sci Sports Exerc, 26, 1012–1020. Bompa, T. O. & Haff, G. 2009. Periodization: Theory and Methodology of Training, Champaign, IL, Human Kinetics. Brandenburg, J. E. & Docherty, D. 2002. The effects of accentuated eccentric loading on strength, muscle hypertrophy, and neural adaptations in trained individuals. J Strength Cond Res, 16, 25–32. Bullock, N. & Comfort, P. 2011. An investigation into the acute effects of depth jumps on maximal strength performance. J Strength Cond Res, 25, 3137–3141. Campos, G. E., Luecke, T. J., Wendeln, H. K., Toma, K., Hagerman, F. C., Murray, T. F., Ragg, K. E., Ratamess, N. A., Kraemer, W. J. & Staron, R. S. 2002. Muscular adaptations in response to three different resistance-training regimens: specificity of repetition maximum training zones. Eur J Appl Physiol, 88, 50–60. Channell, B. T. & Barfield, J. P. 2008. Effect of Olympic and traditional resistance training on vertical jump improvement in high school boys. J Strength Cond Res, 22, 1522–1527. Chaouachi, A., Hammami, R., Kaabi, S., Chamari, K., Drinkwater, E. J. & Behm, D. G. 2014. Olympic weightlifting and plyometric training with children provides similar or greater performance improvements than traditional resistance training. J Strength Cond Res, 28, 1483–1496. Cormie, P., McGuigan, M. R. & Newton, R. U. 2011. Developing maximal neuromuscular power: part 2 – training considerations for improving maximal power production. Sports Med, 41, 125–146. Cotter, S. 2014. Kettlebell Training, Champaign, IL, Human Kinetics. Davies, T., Orr, R., Halaki, M., Hackett, D. 2016. Effect of training leading to repetition failure on muscular strength: A systematic review and meta-analysis. Sports Med, 46, 487–502. de Hoyo, M., Pozzo, M., Sañudo, B., Carrasco, L., Gonzalo-Skok, O., Domínguez-Cobo, S. & Morán-Camacho, E. 2015. Effects of a 10week in-season eccentric-overload training program on muscle-injury prevention and performance in junior elite soccer players. Int J Sports Physiol Perform, 10, 46–52. Desmedt, J. E. & Godaux, E. 1977. Ballistic contractions in man: characteristic recruitment pattern of single motor units of the tibialis anterior muscle. J Physiol, 264, 673–693. Desmedt, J. E. & Godaux, E. 1978. Ballistic contractions in fast or slow human muscles: discharge patterns of single motor units. J Physiol, 285, 185–196. DeWeese, B. H., Hornsby, G., Stone, M. & Stone, M. H. 2015a. The training process: Planning for strength–power training in track and field. Part 1: Theoretical aspects. J Sport Health Sci, 4, 308–317. DeWeese, B. H., Hornsby, G., Stone, M. & Stone, M. H. 2015b. The training process: Planning for strength–power training in track and field. Part 2: Practical and applied aspects. J Sport Health Sci, 4, 318–324. Docherty, D. & Hodgson, M. J. 2007. The application of postactivation potentiation to elite sport. Int J Sports Physiol Perform, 2, 439–
444. Douglas, J., Pearson, S., Ross, A. & McGuigan, M. R. 2016a. Chronic adaptations to eccentric training: a systematic review. Sports Med, Epub ahead of print. Douglas, J., Pearson, S., Ross, A. & McGuigan, M. R. 2016b. Eccentric exercise: physiological characteristics and acute responses. Sports Med, Epub ahead of print, 1–13. Duchateau, J. & Hainaut, K. 2003. Mechanisms of muscle and motor unit adaptation to explosive power training. In: Paavov, V. K. (ed.) Strength and Power in Sport. 2nd ed. Oxford, Blackwell Science. Ebben, W. P., Feldmann, C. R., Vanderzanden, T. L., Fauth, M. L. & Petushek, E. J. 2010. Periodized plyometric training is effective for women, and performance is not influenced by the length of post-training recovery. J Strength Cond Res, 24, 1–7. Ebben, W. P. & Jensen, R. L. 2002. Electromyographic and kinetic analysis of traditional, chain, and elastic band squats. J Strength Cond Res, 16, 547–550. Ebben, W. P., Jensen, R. L. & Blackard, D. O. 2000. Electromyographic and kinetic analysis of complex training variables. J Strength Cond Res, 14, 451–456. Ebben, W. P., Suchomel, T. J. & Garceau, L. R. 2014. The effect of plyometric training volume on jumping performance. In: Sato, K., Sands, W. A. & Mizuguchi, S., eds. 32nd International Conference of Biomechanics in Sports, Johnson City, TN, USA. 566–569. Ebben, W. P. & Watts, P. B. 1998. A review of combined weight training and plyometric training modes: complex training. Strength Cond J, 20, 18–27. Ema, R., Wakahara, T., Miyamoto, N., Kanehisa, H. & Kawakami, Y. 2013. Inhom*ogeneous architectural changes of the quadriceps femoris induced by resistance training. Eur J Appl Physiol, 113, 2691–2703. English, K. L., Loehr, J. A., Lee, S. M. C. & Smith, S. M. 2014. Early-phase musculoskeletal adaptations to different levels of eccentric resistance after 8 weeks of lower body training. Eur J Appl Physiol, 114, 2263–2280. Enoka, R. M. 1995. Morphological features and activation patterns of motor units. J Clin Neurophysiol, 12, 538–559. Farthing, J. P. & Chilibeck, P. D. 2003. The effects of eccentric and concentric training at different velocities on muscle hypertrophy. Eur J Appl Physiol, 89, 578–586. Fleck, S. J. & Kraemer, W. J. 2014. Designing Resistance Training Programs, Champaign, IL, Human Kinetics. Franchi, M. V., Atherton, P. J., Reeves, N. D., Flück, M., Williams, J., Mitchell, W. K., Selby, A., Beltran Valls, R. M. & Narici, M. V. 2014. Architectural, functional and molecular responses to concentric and eccentric loading in human skeletal muscle. Acta Physiologica, 210, 642–654. Fry, A. C. & Kraemer, W. J. 1991. Physical performance characteristics of American collegiate football players. J Strength Cond Res, 5, 126–138. Gabbett, T. J. 2009. Physiological and anthropometric characteristics of starters and non-starters in junior rugby league players, aged 13– 17 years. J Sports Med Phys Fitness, 49, 233–239. Gabriel, D. A., Kamen, G. & Frost, G. 2006. Neural adaptations to resistive exercise. Sports Med, 36, 133–149. Gullich, A. & Schmidtbleicher, D. 1996. MVC-induced short-term potentiation of explosive force. New Stud Athletics, 11, 67–81. Hackett, D., Davies, T., Soomro, N. & Halaki, M. 2015. Olympic weightlifting training improves vertical jump height in sportspeople: a systematic review with meta-analysis. Br J Sports Med, Epub ahead of print, bjsports-2015-094951. Haff, G. G. 2000. Roundtable discussion: Machines versus free weights. Strength Cond J, 22, 18–30. Haff, G. G. & Nimphius, S. 2012. Training principles for power. Strength Cond J, 34, 2–12. Haff, G. G. & Stone, M. H. 2015. Methods of developing power with special reference to football players. Strength Cond J, 37, 2–16. Häkkinen, K., Komi, P. V. & Alen, M. 1985. Effect of explosive type strength training on isometric force- and relaxation-time, electromyographic and muscle fibre characteristics of leg extensor muscles. Acta Physiologica Scandinavica, 125, 587–600. Häkkinen, K., Komi, P. V. & Tesch, P. A. 1981. Effect of combined concentric and eccentric strength training and detraining on forcetime, muscle fiber and metabolic characteristics of leg extensor muscles. Scand J Med Sci Sports, 3, 50–58. Hansen, K. T., Cronin, J. B., Pickering, S. L. & Douglas, L. 2011. Do force–time and power–time measures in a loaded jump squat differentiate between speed performance and playing level in elite and elite junior rugby union players? J Strength Cond Res, 25, 2382–2391. Harris, G. R., Stone, M. H., O’Bryant, H. S., Proulx, C. M. & Johnson, R. L. 2000. Short-term performance effects of high power, high force, or combined weight-training methods. J Strength Cond Res, 14, 14–20. Harrison, J. S. 2010. Bodyweight training: a return to basics. Strength Cond J, 32, 52–55. Henneman, E., Somjen, G. & Carpenter, D. O. 1965. Excitability and inhibitibility of motoneurons of different sizes. J Neurophysiol, 28, 599–620. Hoffman, J. R., Cooper, J., Wendell, M. & Kang, J. 2004. Comparison of Olympic vs. traditional power lifting training programs in football players. J Strength Cond Res, 18, 129–135. Holmstrup, M. E., Jensen, B. T., Evans, W. S. & Marshall, E. C. 2016. Eight weeks of kettlebell swing training does not improve sprint performance in recreationally active females. Int J Exerc Sci, 9, 437–444. Hori, N., Newton, R. U., Andrews, W. A., Kawamori, N., McGuigan, M. R. & Nosaka, K. 2008. Does performance of hang power clean differentiate performance of jumping, sprinting, and changing of direction? J Strength Cond Res, 22, 412–418. Huxley, A. F. 1974. Muscular contraction. J Physiol, 243, 1–43.
Isner-Horobeti, M.E., Dufour, S. P., Vautravers, P., Geny, B., Coudeyre, E. & Richard, R. 2013. Eccentric exercise training: modalities, applications and perspectives. Sports Med, 43, 483–512. Israetel, M. A., McBride, J. M., Nuzzo, J. L., Skinner, J. W. & Dayne, A. M. 2010. Kinetic and kinematic differences between squats performed with and without elastic bands. J Strength Cond Res, 24, 190–194. Issurin, V. B. 2008. Block periodization versus traditional training theory: a review. J Sports Med Phys Fitness, 48, 65–75. Issurin, V. B. 2010. New horizons for the methodology and physiology of training periodization. Sports Med, 40, 189–206. Jay, K., Frisch, D., Hansen, K., Zebis, M. K., Andersen, C. H., Mortensen, O. S. & Andersen, L. L. 2011. Kettlebell training for musculoskeletal and cardiovascular health: a randomized controlled trial. Scand J Work, Environ Health, 37, 196–203. Jay, K., Jakobsen, M. D., Sundstrup, E., Skotte, J. H., Jørgensen, M. B., Andersen, C. H., Pedersen, M. T. & Andersen, L. L. 2013. Effects of kettlebell training on postural coordination and jump performance: a randomized controlled trial. J Strength Cond Res, 27, 1202–1209. Jensen, R. L. & Ebben, W. P. 2003. Kinetic analysis of complex training rest interval effect on vertical jump performance. J Strength Cond Res, 17, 345–349. Jones, P. & Lees, A. 2003. A biomechanical analysis of the acute effects of complex training using lower limb exercises. J Strength Cond Res, 17, 694–700. Kawakami, Y., Abe, T. & f*ckunaga, T. 1993. Muscle-fiber pennation angles are greater in hypertrophied than in normal muscles. J Appl Physiol, 74, 2740–2744. Kawakami, Y., Abe, T., Kuno, S.-Y. & f*ckunaga, T. 1995. Training-induced changes in muscle architecture and specific tension. Eur J Appl Physiol Occup Physiol, 72, 37–43. Kawamori, N., Crum, A. J., Blumert, P. A., Kulik, J. R., Childers, J. T., Wood, J. A., Stone, M. H. & Haff, G. G. 2005. Influence of different relative intensities on power output during the hang power clean: identification of the optimal load. J Strength Cond Res, 19, 698–708. Kawakami, N., & Haff, G. (2004). The optimal training load for the development of muscular power. J. Strength Cond. Res, 18, 675– 684. Kraemer, W. J., Fleck, S. J. & Evans, W. J. 1996. Strength and power training: physiological mechanisms of adaptation. Exerc Sport Sci Rev, 24, 363–397. Kraemer, W. J. & Newton, R. U. 2000. Training for muscular power. Phys Med Rehab Clin N Am, 11, 341–368. Lake, J. P. & Lauder, M. A. 2012. Kettlebell swing training improves maximal and explosive strength. J Strength Cond Res, 26, 2228– 2233. Lake, J. P., Lauder, M. A., Smith, N. A. & Shorter, K. A. 2012. A comparison of ballistic and non-ballistic lower-body resistance exercise and the methods used to identify their positive lifting phases. J Appl Biomech, 28, 431–437. Leong, B., Kamen, G., Patten, C. & Burke, J. R. 1999. Maximal motor unit discharge rates in the quadriceps muscles of older weight lifters. Med Sci Sports Exerc, 31, 1638–1644. Makaruk, H., Winchester, J. B., Sadowski, J., Czaplicki, A. & Sacewicz, T. 2011. Effects of unilateral and bilateral plyometric training on power and jumping ability in women. J Strength Cond Res, 25, 3311–3318. Malliaras, P., Kamal, B., Nowell, A., Farley, T., Dhamu, H., Simpson, V., Morrissey, D., Langberg, H., Maffulli, N. & Reeves, N. D. 2013. Patellar tendon adaptation in relation to load-intensity and contraction type. J Biomech, 46, 1893–1899. Manocchia, P., Spierer, D. K., Lufkin, A. K. S., Minichiello, J. & Castro, J. 2013. Transference of kettlebell training to strength, power, and endurance. J Strength Cond Res, 27, 477–484. Marques, M., Saavedra, F., Abrantes, C. & Aidar, F. 2011. Associations between rate of force development metrics and throwing velocity in elite team handball players: a short research report. J Hum Kinet, 29, 53–57. McBride, J. M., Haines, T. L. & Kirby, T. J. 2011. Effect of loading on peak power of the bar, body, and system during power cleans, squats, and jump squats. J Sports Sci, 29, 1215–1221. McCurdy, K. W., Langford, G. A., Doscher, M. W., Wiley, L. P. & Mallard, K. 2005. The effects of short-term unilateral and bilateral lower-body resistance training on measures of strength and power. J Strength Cond Res, 19, 9–15. McCurdy, K. W., O’Kelley, E., Kutz, M., Langford, G., Ernest, J. & Torres, M. 2010. Comparison of lower extremity EMG between the 2-leg squat and modified single-leg squat in female athletes. J Sport Rehabil, 19, 57–70. McEvoy, K. P. & Newton, R. U. 1998. Baseball throwing speed and base running speed: the effects of ballistic resistance training. J Strength Cond Res, 12, 216–221. Milner-Brown, H. S. & Stein, R. B. 1975. The relation between the surface electromyogram and muscular force. J Physiol, 246, 549– 569. Minetti, A. E. 2002. On the mechanical power of joint extensions as affected by the change in muscle force (or cross-sectional area), ceteris paribus. Eur J Appl Physiol, 86, 363–369. Miyamoto, N., Wakahara, T., Ema, R. & Kawakami, Y. 2013. Further potentiation of dynamic muscle strength after resistance training. Med Sci Sports Exerc, 45, 1323–1330. Morrissey, M. C., Harman, E. A. & Johnson, M. J. 1995. Resistance training modes: specificity and effectiveness. Med Sci Sports Exerc, 27, 648–660. Newton, R. U., Kraemer, W. J. & Häkkinen, K. 1999. Effects of ballistic training on preseason preparation of elite volleyball players.
Med Sci Sports Exerc, 31, 323–330. Newton, R. U., Kraemer, W. J., Häkkinen, K., Humphries, B. & Murphy, A. J. 1996. Kinematics, kinetics, and muscle activation during explosive upper body movements. J Appl Biomech, 12, 31–43. Nimphius, S., McGuigan, M. R. & Newton, R. U. 2010. Relationship between strength, power, speed, and change of direction performance of female softball players. J Strength Cond Res, 24, 885–895. Nimphius, S., McGuigan, M. R. & Newton, R. U. 2012. Changes in muscle architecture and performance during a competitive season in female softball players. J Strength Cond Res, 26, 2655–2666. Ojasto, T. & Häkkinen, K. 2009. Effects of different accentuated eccentric load levels in eccentric-concentric actions on acute neuromuscular, maximal force, and power responses. J Strength Cond Res, 23, 996–1004. Östenberg, A., Roos, E., Ekdah, C. & Roos, H. 1998. Isokinetic knee extensor strength and functional performance in healthy female soccer players. Scand J Med Sci Sports, 8, 257–264. Otto III, W. H., Coburn, J. W., Brown, L. E. & Spiering, B. A. 2012. Effects of weightlifting vs. kettlebell training on vertical jump, strength, and body composition. J Strength Cond Res, 26, 1199–1202. Peterson, M. D., Rhea, M. R. & Alvar, B. A. 2005. Applications of the dose-response for muscular strength development: A review of meta-analytic efficacy and reliability for designing training prescription. J Strength Cond Res, 19, 950–958. Robbins, D. W. 2005. Postactivation potentiation and its practical applicability: a brief review. J Strength Cond Res, 19, 453–458. Saplinskas, J. S., Chobotas, M. A. & Yashchaninas, I. I. 1980. The time of completed motor acts and impulse activity of single motor units according to the training level and sport specialization of tested persons. Electromyogr Clinical Neurophysiol, 20, 529–539. Seitz, L. B., De Villarreal, E. S. S. & Haf, G. G. 2014. The temporal profile of postactivation potentiation is related to strength level. J Strength Cond Res, 28, 706–715. Semmler, J. G. 2002. Motor unit synchronization and neuromuscular performance. Exerc Sport Sci Rev, 30, 8–14. Semmler, J. G., Kutscher, D. V., Zhou, S. & Enoka, R. M. 2000. Motor unit synchronization is enhanced during slow shortening and lengthening contractions of the first dorsal interosseus muscle. Soc Neurosci Abstr, 26, 463. Semmler, J. G. & Nordstrom, M. A. 1998. Motor unit discharge and force tremor in skill-and strength-trained individuals. Exp Brain Res, 119, 27–38. Sheppard, J., Hobson, S., Barker, M., Taylor, K., Chapman, D., McGuigan, M. & Newton, R. U. 2008. The effect of training with accentuated eccentric load counter-movement jumps on strength and power characteristics of high-performance volleyball players. Int J Sports Sci Coach, 3, 355–363. Soria-Gila, M. A., Chirosa, I. J., Bautista, I. J., Baena, S. & Chirosa, L. J. 2015. Effects of variable resistance training on maximal strength: a meta-analysis. J Strength Cond Res, 29, 3260–3270. Soriano, M. A., Jiménez-Reyes, P., Rhea, M. R. & Marín, P. J. et al. 2015. The optimal load for maximal power production during lowerbody resistance exercises: a meta-analysis. Sports Med, 45, 1191–1205. Soriano, M. A., Suchomel, T. J. & Marin, P. J. 2016. The optimal load for improving maximal power production during upper-body exercises: a meta-analysis. Sports Med, Epub ahead of print. Speirs, D. E., Bennett, M. A., Finn, C. V. & Turner, A. P. 2016. Unilateral vs. bilateral squat training for strength, sprints, and agility in academy rugby players. J Strength Cond Res, 30, 386–392. Spiteri, T., Nimphius, S. & Wilkie, J. 2012. Comparison of running times during reactive offensive and defensive agility protocols. J Aust Strength Cond, 20, 73–78. Stone, M. H. 1993. Position statement: explosive exercises and training. Natl Strength Cond Assoc J, 15, 7–15. Stone, M. H., Moir, G., Glaister, M. & Sanders, R. 2002. How much strength is necessary? Phys Ther Sport, 3, 88–96. Stone, M. H., O’Bryant, H., Garhammer, J., McMillan, J. & Rozenek, R. 1982. A theoretical model of strength training. Strength Cond J, 4, 36–39. Stone, M. H., O’Bryant, H. S., McCoy, L., Coglianese, R., Lehmkuhl, M. & Schilling, B. 2003. Power and maximum strength relationships during performance of dynamic and static weighted jumps. J Strength Cond Res, 17, 140–147. Stone, M. H., Sands, W. A., Pierce, K. C., Ramsey, M. W. & Haff, G. G. 2008. Power and power potentiation among strength-power athletes: preliminary study. Int J Sports Physiol Perform, 3, 55–67. Stone, M. H., Stone, M. & Sands, W. A. 2007. Principles and Practice of Resistance Training, Champaign, IL, Human Kinetics. Suchomel, T. J., Comfort, P. & Lake, J. P. 2017. Enhancing the force-velocity profile of athletes using weightlifting derivatives. Strength Cond J, 39, 10–20. Suchomel, T. J., Lamont, H. S. & Moir, G. L. 2016a. Understanding vertical jump potentiation: a deterministic model. Sports Med, 46, 809–828. Suchomel, T. J., Nimphius, S. & Stone, M. H. 2016b. The importance of muscular strength in athletic performance. Sports Med, 46, 1419–1449. Suchomel, T. J., Sato, K., DeWeese, B. H., Ebben, W. P. & Stone, M. H. 2016c. Potentiation effects of half-squats performed in a ballistic or non-ballistic manner. J Strength Cond Res, 30, 1652–1660. Suchomel, T. J., Sato, K., DeWeese, B. H., Ebben, W. P. & Stone, M. H. 2016d. Potentiation following ballistic and non-ballistic complexes: the effect of strength level. J Strength Cond Res, 30, 1825–1833. Taber, C. B., Bellon, C. R., Abbott, H. & Bingham, G. E. 2016. Roles of maximal strength and rate of force development in maximizing
muscular power. Strength Cond J, 38, 71–78. Teo, S. Y., Newton, M. J., Newton, R. U., Dempsey, A. R. & Fairchild, T. J. 2016. Comparing the effectiveness of a short-term vertical jump versus weightlifting program on athletic power development. J Strength Cond Res, 30, 2741–2748. Till, K. A. & Cooke, C. 2009. The effects of postactivation potentiation on sprint and jump performance of male academy soccer players. J Strength Cond Res, 23, 1960–1967. Tricoli, V., Lamas, L., Carnevale, R. & Ugrinowitsch, C. 2005. Short-term effects on lower-body functional power development: weightlifting vs. vertical jump training programs. J Strength Cond Res, 19, 433–437. Tsolakis, C. & Bogdanis, G. C. 2011. Influence of type of muscle contraction and gender on postactivation potentiation of upper and lower limb explosive performance in elite fencers. J Sports Sci Med, 10, 577–583. van Cutsem, M., Duchateau, J. & Hainaut, K. 1998. Changes in single motor unit behaviour contribute to the increase in contraction speed after dynamic training in humans. J Physiol, 513, 295–305. Verkhoshansky, Y. 1986. Speed-strength preparation and development of strength endurance of athletes in various specializations. Soviet Sports Review, 22, 120–124. Wakahara, T., Miyamoto, N., Sugisaki, N., Murata, K., Kanehisa, H., Kawakami, Y., f*ckunaga, T. & Yanai, T. 2012. Association between regional differences in muscle activation in one session of resistance exercise and in muscle hypertrophy after resistance training. Eur J Appl Physiol, 112, 1569–1576. Wallace, B. J., Winchester, J. B. & McGuigan, M. R. 2006. Effects of elastic bands on force and power characteristics during the back squat exercise. J Strength Cond Res, 20, 268–272. Wells, A. J., f*ckuda, D. H., Hoffman, J. R., Gonzalez, A. M., Jajtner, A. R., Townsend, J. R., Mangine, G. T., Fragala, M. S. & Stout, J. R. 2014. Vastus lateralis exhibits non-hom*ogenous adaptation to resistance training. Muscle Nerve, 50, 785–793. Weyand, P. G., Sandell, R. F., Prime, D. N. L. & Bundle, M. W. 2010. The biological limits to running speed are imposed from the ground up. J Appl Physiol, 108, 950–961. Weyand, P. G., Sternlight, D. B., Bellizzi, M. J. & Wright, S. 2000. Faster top running speeds are achieved with greater ground forces, not more rapid leg movements. J Appl Physiol, 89, 1991–1999. Young, W. B., Jenner, A. & Griffiths, K. 1998. Acute enhancement of power performance from heavy load squats. J Strength Cond Res, 12, 82–84. Young, W. B., Newton, R. U., Doyle, T. L. A., Chapman, D., Cormack, S., Stewart, C. & Dawson, B. 2005. Physiological and anthropometric characteristics of starters and non-starters and playing positions in elite Australian Rules football: a case study. J Sci Med Sport, 8, 333–345. Zamparo, P., Minetti, A. & Di Prampero, P. 2002. Interplay among the changes of muscle strength, cross-sectional area and maximal explosive power: theory and facts. Eur J Appl Physiol, 88, 193–202. Zatsiorsky, V. 1995. Science and Practice of Strength Training, Champaign, IL, Human Kinetics.
CHAPTER 3
Stretch-shortening cycle and muscle-tendon stiffness John J. McMahon
INTRODUCTION This chapter begins by introducing the stretch-shortening cycle (SSC), describing its underpinning mechanisms and explaining the influence of muscle-tendon stiffness (MTS) on SSC function. The chapter then describes the different levels at which MTS can be directly or indirectly measured during SSC tasks which involve the entire lower limb(s) such as running, jumping and hopping. The following section provides a commentary on the effects of MTS on performance outcomes measured during running, jumping and hopping which serves to inform practitioners of the benefits and limitations of performing these tasks with a stiff or compliant limb strategy. The chapter concludes by summarising the results of contemporary training studies to inform training recommendations. The information presented in this chapter should, therefore, help practitioners with the design of their training programmes aimed at developing task-specific SSC function.
WHAT IS THE STRETCH-SHORTENING CYCLE? Early research findings revealed that when isolated skeletal muscle fibres were tetanically stimulated (i.e., maximally activated by a nerve stimulator), stretched and then immediately allowed to shorten, they performed a far greater amount of positive work when compared to being purely shortened alone (Cavagna et al., 1965; Cavagna et al., 1968). This sequential combination of eccentric (lengthening) and concentric (shortening) muscle actions was later termed the SSC (Cavanagh and Komi, 1979). In addition to when measured during isolated conditions, the apparent “performance enhancing” effect of the SSC was also demonstrated during a range of SSC actions involving the entire lower limb(s), such as running, jumping and hopping (Asmussen and Bonde-Petersen, 1974; f*ckashiro and Komi, 1987; Luhtanen and Komi, 1978). Whilst it is important to note the SSC is common to upper limb movements too, such as throwing (Newton et al., 1997), the majority of scientific studies that have explored the SSC to date have solely investigated the lower limb(s) and so this chapter will discuss lower limb SSC actions only. Due to its aforementioned prevalence in running, jumping and hopping movements, which are
performed by many athletes as part of both training and competition, the SSC forms the most common type of lower limb muscle function (Van Ingen Schenau et al., 1997a). In recent years, there has been much debate over the proposed mechanisms which cause the potentiating effect (e.g., increased positive work) of the SSC, however, stimulation of muscle stretch reflexes (e.g., muscle spindles) and storage and reutilisation of elastic energy in the muscle-tendon unit (MTU) are the two primary mechanisms that have been repeatedly acknowledged among researchers (Cormie et al., 2011; Van Ingen Schenau et al., 1997a, 1997b; Turner and Jeffreys, 2011). During the SSC, stretch reflexes act to increase muscle stiffness (Taube et al., 2012), and tendon stiffness influences the storage and reutilisation of elastic energy (Farris et al., 2011), thus it can be deduced that MTS has a profound influence on SSC function.
WHAT IS STIFFNESS? Simply stated, stiffness describes the relationship between a given force and the magnitude of deformation (i.e., stretch) of an object or body (Butler et al., 2003; Brughelli and Cronin, 2008a; McMahon et al., 2012). When applied to the MTU, the object or body could be the muscle, the tendon or both. The term “stiffness” is based on Hooke’s Law, which has been described in detail elsewhere (Butler et al., 2003; Brughelli and Cronin, 2008a), and describes the stiffness of an ideal spring-mass system (Butler et al., 2003). When an object that obeys Hooke’s Law deforms (such as tendon), its change in length will be directly proportional to the force acting upon it (Alexander, 1997) (Figure 3.1). During this deformation (e.g., during the eccentric phase of a SSC action), the object will store elastic energy which will be reutilised as the object shortens (e.g., during the concentric phase of a SSC action) and returns to its original resting length (Butler et al., 2003). It is worth pointing out at this stage that activated muscle does not always adhere to Hooke’s Law and the reasons for this will be discussed in the later sections of this chapter. Nevertheless, during the performance of SSC actions, stiffness can be described at a broad range of levels, from an individual MTU, to modelling the entire body as a simple spring-mass system (Butler et al., 2003; Brughelli and Cronin, 2008a).
FIGURE 3.1
An example of an object that obeys Hooke’s Law and the equation to calculate stiffness (k), where ΔF = change in force and Δx = change in length.
MUSCLE-TENDON STIFFNESS When considering stiffness in context of the various MTUs which surround the lower limb joints, it is known that there are both passive (tendon, connective tissue, etc., which are commonly referred to as the series and parallel elastic components) and active (muscle, which is commonly referred to as the contractile component) components. Due to this, the MTU is considered to be a variably stiff system because whilst tendon possesses a fairly linear relationship (due to it demonstrating mainly elastic behaviour) between force and deformation (Farris et al., 2011; Lichtwark and Wilson, 2005), muscle can vary its stiffness through both feedforward (e.g., pre-programmed) and feedback (e.g., reflex) activation mechanisms (Taube et al., 2012). It must also be noted that the tendon is known to possess viscous as well as elastic properties (Pearson and McMahon, 2012), and so the amount of tendon stretch (and thus storage of elastic energy) experienced during SSC actions will be somewhat affected by tendon loading rate (McMahon et al., 2014). Muscle activation is, therefore, the primary modulator of MTS during SSC actions, as this will influence both muscle stiffness (i.e., the resultant muscle length changes) and tendon stiffness (i.e., by affecting load rate) alike. As mentioned earlier, both pre-programmed and reflex muscle activation strategies largely dictate the muscle stiffness attained during SSC tasks (Taube et al., 2012). The pre-programmed aspect of muscle activation relates to both muscle pre-activation, which acts to provide sufficient stiffness to the MTU at initial ground contact (Taube et al., 2012), and variable activation during ground contact, which helps to maintain stiffness (i.e., prevent muscle lengthening) in the braking phase and then facilitate the controlled release of high forces (produced in the braking phase) in the subsequent propulsion phase (Komi, 2003). The reflex aspect of muscle activation relates primarily to the stimulation of a stretch reflex called short-latency response (SLR), although when muscle is preactivated prior to stretching (as is the case during SSC tasks) there are medium-latency (MLR) and long-latency (LLR) responses involved too (Taube et al., 2012). These reflex responses simply relate to their time-course of stimulation, with time epochs of 30–60 ms, 60–90 ms and 90–120 ms typically relating to the SLR, MLR and LLR, respectively. It has been suggested, however, that stretch reflex contributions to muscle stiffness are more apparent when the muscle is not fully activated (e.g., during sub-maximal SSC tasks [Cronin et al., 2011]) in order to help prevent sudden muscle yielding during the braking phase (Taube et al., 2012). Calculating individual MTS contributions to the total stiffness attained by a given MTU during SSC tasks is a relatively complex process which requires the simultaneous collection of ultrasound, electromyography, force platform and motion analysis data, followed by a lengthy data analysis process which makes this discrete level of analysis difficult to perform in a competitive sport setting. Thus, in the applied strength and conditioning research and practice setting, it is more common to see ‘global’ measures of lower limb MTS assessments, such as joint stiffness (Kjoint) and leg stiffness (Kleg), as these measures are easier to attain, require less processing time and can still provide valuable insight into how MTS influences SSC function during a variety of athletic tasks (e.g., running, jumping, hopping).
JOINT STIFFNESS
Lower limb Kjoint is typically calculated using the torsional-spring model (Figure 3.2) as the ratio of the peak sagittal plane joint moment (i.e., the joint rotatory force) to peak sagittal plane joint angular displacement (Figure 3.3) between the instants of ground contact and maximum joint flexion (Farley et al., 1998). An alternative method of quantifying Kjoint has also been described in the literature as the ratio of negative mechanical work to change in joint angle between the instants of ground contact and maximum joint flexion (Arampatzis et al., 1999), however, this method was later critiqued (Gunther and Blickhan, 2002), and to the author’s knowledge, has not since been reported in any other studies. Despite the method used, however, Kjoint calculations require access to both a force platform and either two- or three-dimensional motion capture, so this equipment may be more accessible to strength and conditioning researchers and practitioners than the addition of ultrasound and electromyography equipment needed to calculate MTS. The torsional-spring model assumes that the lower limb can be represented by multiple spring-like joints (i.e., the ankle, knee and hip) during SSC actions, which flex and extend during the ground contact period, thus storing and releasing energy (Figure 3.2).
FIGURE 3.2
An example of the torsional spring model and how it corresponds to the human body.
FIGURE 3.3
An example of the joint moment–joint angular displacement relationship during loaded flexion and extension.
It has been suggested that Kjoint only provides a measure of ‘quasi-stiffness’, as one stiffness value is used to describe all contributing components to Kjoint, such as muscles, tendons, ligaments, cartilage and bone (Latash and Zatsiorsky, 1993). Nevertheless, Kjoint during SSC tasks is mainly influenced by the magnitude of agonist muscle activation, in addition to the magnitude of antagonist muscle coactivation, immediately prior to and during ground contact (Arampatzis et al., 2001b; Arampatzis et al., 2001a; Farley et al., 1998). Therefore, Kjoint is mainly controlled by muscle stiffness through the muscle activation mechanisms mentioned in the previous section. Another point to consider is that Kjoint attained during SSC tasks is also influenced by limb geometry at touchdown (Farley et al., 1998; Moritz and Farley, 2004; Devita and Skelly, 1992). This can be reasoned by the understanding of the joint moment–angle relationship, in that as the lower limb becomes more extended at touchdown, the moment about the joint decreases for any given external ground reaction force (Figure 3.4), resulting in decreased joint flexion for any given level of extensor muscle activation (Moritz and Farley, 2004).
LEG STIFFNESS It has been shown in several studies that Kjoint is the primary determinant of Kleg during SSC actions (Farley et al., 1998; Arampatzis et al., 1999; Kuitunen et al., 2002), and so although the predominant joint that regulates Kleg depends on the type of SSC task being performed, this most ‘global’ measure of lower limb stiffness provides valuable information pertaining to SSC function and is the easiest of the lower limb stiffness hierarchy to measure in both lab and field settings. The Kleg measurement is based on the human body acting as a simple spring-mass system during SSC tasks (Brughelli and Cronin, 2008b; Geyer et al., 2006). The spring-mass model (Figure 3.5) is comprised of a point mass (equal to body mass), which is supported by a single massless Hookean spring (representing the leg or legs depending upon whether a unilateral or bilateral task is being
performed) (Blickhan, 1989; McMahon and Cheng, 1990). When the spring is not compressed (i.e., during the flight phase of SSC tasks), it does not store any energy and thus no force is developed; however, energy is stored when the spring is compressed (i.e., during the braking phase of SSC tasks) and force is produced, and the majority of this energy is reutilised when the spring subsequently recoils (i.e., during the propulsion phase of SSC tasks) (Brughelli and Cronin, 2008a).
FIGURE 3.4
An example of how joint touchdown angles influence leg and joint stiffness values.
From the spring-mass model, Kleg can be calculated as the ratio of the peak ground reaction force to peak leg compression during the period of ground contact (McMahon and Cheng, 1990). Other methods can also be used to calculate Kleg based on body mass and either the natural period of oscillation (McMahon et al., 1987; Cavagna et al., 1988) or temporal characteristics such as ground contact and flight times (Morin et al., 2005; Dalleau et al., 2004). Although the latter methods (i.e., based on body mass and temporal factors) have been less frequently reported in the scientific literature (Brughelli and Cronin, 2008b; Serpell et al., 2012), they are commonly used in applied practice due to these measurements of Kleg being easily attainable from simple jump mats, photoelectric cells (e.g., Optojump) and even iPhone apps (Balsalobre-Fernández et al., 2017). The limitation of using field-based calculations of Kleg is that they do not directly include force and deformation in their calculations, and so they provide somewhat of a proxy of ‘true’ Kleg.
FIGURE 3.5
An example of the spring-mass model and how it corresponds to the human body.
STIFFNESS AND PERFORMANCE The implications of MTS being primarily regulated by pre-programmed and reflex muscle activation, and somewhat influenced by tendon stiffness and joint geometry, is that it is acutely sensitive to changes in SSC task type and intensity which, in turn, influences SSC function (Ishikawa et al., 2005; Ishikawa and Komi, 2004; McMahon et al., 2014). For example, when bilateral drop jumps (DJs) were performed from increasing drop heights (10 cm lower than ‘optimal’ drop height, optimal drop height as determined by best jump height achieved, and 10 cm higher than ‘optimal’ drop height), vastus lateralis (VL) muscle activation increased, decreased and remained unchanged during the precontact, braking and propulsive phases, respectively, but tendon recoil decreased (Ishikawa et al., 2005). Tendon recoil also reduced by virtue of increased drop height for the medial gastrocnemius (MG), and its activation patterns were similar to those reported for the VL in the pre-contact and braking phases; however, the MG showed increased activation during the propulsive phase (Ishikawa et al., 2005). Interestingly, the SLR amplitude decreased for the MG but increased for the VL during DJs performed from the highest drop (Ishikawa et al., 2005). This is perhaps explained by the MG showing a reduction in lengthening during the braking phase, whereas the VL demonstrated a general increase in lengthening during this phase (Ishikawa et al., 2005), since the muscle spindle stretch reflex detects the rate and magnitude of muscle lengthening (Taube et al., 2012). These results illustrate that variations in MTS and thus SSC function for a given task and intensity is musclespecific (as noted by the differential response of the VL and MG MTUs), and that high stiffness (as shown for the highest drop condition) does not always transfer to improved performance (e.g.,
improved jump height). The differential stiffness strategies of the individual VL and MG muscle-tendon components during various DJ tasks mentioned above (Ishikawa et al., 2005) are echoed by a range of studies that explored the associations between muscle activation strategies and both Kleg and Kjoint attained in a range of DJ tasks. For example, there were significant correlations between Kleg and the magnitude of pre-activation of the MG, lateral gastrocnemius (LG), VL and the hamstrings during the performance of bilateral DJs by decathletes from a height of 20 cm (Arampatzis et al., 2001b). Interestingly, when DJs were performed from heights of 40 and 60 cm, relationships between Kleg and the magnitude of pre-activation were demonstrated for VL and the hamstrings only for this group of athletes (Arampatzis et al., 2001b). For female athletes, significant correlations between Kleg and the magnitude of pre-activation of the MG, LG and VL were found for bilateral DJs performed from a 20 cm height, whereas the magnitude of pre-activation of MG and VL only were correlated to Kleg attained during DJs from 40 cm (Arampatzis et al., 2001a). Nine healthy males also demonstrated a link between pre-activation of the VL muscle and Kknee during bilateral DJs performed from 50 cm (Horita et al., 2002). The above results pertaining to the varying muscle activation responses to DJs performed from different drop heights reflect the different Kjoint contributions to total Kleg that have been highlighted for a range of performances. For example, Kankle has been shown to be the primary determinant of Kleg during hopping in place at high (≥ 2.0 Hz) hopping frequencies whereby the ability to hop at high frequencies requires high levels of Kleg (Farley et al., 1998; Hobara et al., 2011). Contrastingly, Kknee was the primary modulator of Kleg at low (≤ 1.5 Hz) hopping frequencies which require lower levels of Kleg and where greater hop heights are noted (Hobara et al., 2011; Hobara et al., 2009). Similarly, Kknee was also the primary determinant of Kleg during both low (6.5 m.s–1) velocity running (Arampatzis et al., 1999) and sprint running (Kuitunen et al., 2002). These differential joint contributions to total Kleg across different SSC tasks reflect differential muscle-tendon contributions to these tasks, with the contribution of tendon (in terms of total lengthening and shortening of the MTU) being higher and muscle length being almost constant (i.e., isometric) when Kleg increases (McMahon et al., 2013b). Based on the results of the research presented above, it is apparent that there is an appropriate amount of Kleg for success in a particular SSC task. This notion is supported by a range of scientific studies related to jumping. For example, during DJ performances from heights of 20–60 cm, jump height was maximised when participants adopted a range of Kleg strategies (Arampatzis et al., 2001a, 2001b; Laffaye and Choukou, 2010). However, the general trend in these studies was that too much Kleg had a negative impact upon vertical jump height (Arampatzis et al., 2001a, 2001b; Laffaye and Choukou, 2010), and this was especially seen in a study whereby DJs were performed from very high (80 and 100 cm) drop heights (Walshe and Wilson, 1997). The potentially inhibiting effect of excessive Kleg was also demonstrated during a high jumping manoeuvre, as greatest jump heights were achieved when participants adopted a more compliant (i.e., less stiff) leg strategy (Laffaye et al., 2005). The aforementioned results suggest that the degree of Kleg required to successfully complete a jumping-based task depends upon both the aims (e.g., maximal height attainment vs. fast execution) and type (e.g., hopping vs. DJ) of the specific task being performed. Several studies have
also reported that Kleg was associated with increased running velocity (Farley and Gonzalez, 1996; Stefanyshyn and Nigg, 1998; Arampatzis et al., 1999; Hobara et al., 2010) and increased running economy (McMahon and Cheng, 1990, Heise and Martin, 1998, Dutto and Smith, 2002; Rabita et al., 2011) but not with sprint acceleration (Lockie et al., 2011; Chelly and Denis, 2001; Pruyn et al., 2014). The reason for Kleg being beneficial to DJ from lower heights, as compared to DJ from greater heights and high jumping, can be explained by increased Kleg being linked to shorter ground contact times and increased vGRFs (ground reaction force) (Arampatzis et al., 2001a, 2001b). When increasing jump height is the desired outcome, vertical impulse (area underneath the force-time curve) must be increased (Kirby et al., 2011). Although impulse can be maintained or increased by increasing vGRFs when ground contact times decrease (as seen when employing a stiff jumping strategy), it seems the latter prevails when high Kleg is demonstrated in DJs performed from greater heights and during high jumping. Similarly, researchers have shown that the achievement of faster top running speeds was more closely related to the production of a greater resultant GRF rather than to an increase in stride frequency (Weyand et al., 2000). Therefore, if running was to be performed with high Kleg, ground contact times would decrease (Farley et al., 1991; Arampatzis et al., 2001b, 2001a), which would reduce the time available for force production (Weyand et al., 2010). A reduction in resultant GRF during running would likely reduce stride length (McMahon and Cheng, 1990; Kerdok et al., 2002). This is, like for jumping, due to a reduction in impulse. For example, unless a reduction in ground contact time is accompanied by at least the maintenance of, or an increase in, GRF, there will be a reduction in impulse. Therefore, top running speeds may plateau with an increase in Kleg, in spite of a potential increase in stride frequency (McMahon et al., 1987; Farley and Gonzalez, 1996; Hobara et al., 2010). Recent work did indeed find that the fastest man on earth (i.e., Usain Bolt) ran with significantly lower Kleg, lower stride frequency and longer ground contact times during competition when compared with his two closest rivals (Taylor and Beneke, 2012). In terms of running economy, it is known that the storage and release of elastic energy will help to reduce the work of the muscle (Roberts and Marsh, 2003; Perl et al., 2012; Lichtwark and Barclay, 2010), and although previous studies revealed that a high Kleg strategy was associated with improved running economy (McMahon and Cheng, 1990; Heise and Martin, 1998; Dutto and Smith, 2002; Rabita et al., 2011), a stiffer MTU may not always elicit a more economical outcome. For example, previous studies have examined the relationship between MG muscle fascicle length and Achilles tendon stiffness and maximum efficiency during a range of running and walking tasks (Lichtwark and Wilson, 2007, 2008; Lichtwark et al., 2007), and despite maximum efficiency for both running and walking occurring at similar values of tendon stiffness, it was suggested that moving towards a stiffer tendon would reduce efficiency in the walking task but would be more ideal for running, along with longer muscle fibre lengths required to optimise efficiency as compared to walking. However, modelling indicated that fibre lengths could vary by approximately one and a half times (45–70 mm) and tendon stiffness by approximately threefold (150–500 N•mm–1) to give optimal efficiency in a given walking or running task (Lichtwark and Wilson, 2008), which further highlights both the individual and task-specific nature of ‘optimal’ MTS.
FIGURE 3.6
A schematic diagram illustrating how the leg(s) change from being more compliant (opposite of stiff) to more stiff for a range of stretch-shortening cycle tasks.
In conclusion, the amount of MTS required during a SSC task depends on desired task outcome (Figure 3.6). If reducing ground contact time and increasing GRF is sought then stiffer is better, but if increasing joint angular velocity to increase short sprint acceleration or jump height is sought then too much stiffness will be detrimental. Acutely modulating an athlete’s MTS strategy in the direction of stiffening their legs via verbal coaching cues, etc., will increase GRFs and load rates, and so this should only be done if they are appropriately conditioned and (in line with the previous point) if the task warrants a stiffer strategy (Figure 3.6). A safer and more sensible approach to increasing MTS is through long-term training.
STIFFNESS AND TRAINING Only a few studies to date have examined the effects of training interventions on Kleg and Kjoint, as determined during SSC actions (Table 3.1). Most of the training interventions included in these studies were very distinct, which makes it somewhat difficult to make any definitive conclusions about the most effective training methods for increasing Kleg and Kjoint, but there are some general trends noted across studies which warrant discussion. Generally, traditional resistance exercises performed individually with ≤80% one repetition maximum (1RM) tended not to increase Kleg and Kjoint (Toumi et al., 2004; Kubo et al., 2007), unless performed concurrently with plyometric exercises (Toumi et al., 2004). Individual traditional resistance exercises can increase Kleg, however, if performed with a relative load of up to 90% 1RM (Cormie et al., 2010). Multiple traditional resistance exercises performed with ≥85% 1RM have been shown to increase task-specific Kleg (Millet et al., 2002; Arabatzi and Kellis, 2012). For example, the results presented by Millet et al. (2002) showed increased Kleg measured during running but not during hopping at 2.0 Hz. These task-specific differences in Kleg seen post-intervention are most likely due to the training programme being knee-dominant (Table 3.1), in light of Kknee being the primary modulator of Kleg during running (Arampatzis et al., 1999; Kuitunen et al., 2002) and Kankle
being the primary determinant of Kleg when hopping at 2.0 Hz (Farley et al., 1998; Hobara et al., 2011). Contrastingly, the training programme included in the study by Arabatzi & Kellis (2012) was also knee-focussed, although Kleg increased during DJs performed from 20 cm but not 60 cm, despite the latter drop height being more synonymous with Kknee regulation (Arampatzis et al., 2001b); this is possibly due to the relatively short training duration of 8 weeks. Similarly, moderate-heavy (60– 100% 1RM) traditional resistance exercise performed concomitantly with plyometric exercises increased Kleg during countermovement jump performance, but reduced Kleg during DJs performed from ≥30 cm drop heights (Hunter and Marshall, 2002). However, the participants tested by Marshall and Hunter (2002) had never performed any structured plyometric training prior to the commencement of the study nor were they given any verbal instructions either prior to or during the jump performances, which may have influenced these findings. TABLE 3.1 A summary of studies which have determined the effects of training interventions on global lower limb stiffness measures Study
Subjects
Toumi et al. 8 male (2004) handball players
Training Programme Overview
Training Duration
Result
6 × 10 reps of leg press at 70% 1-RM
6 weeks (4 sessions/week)
No change in Kleg (CMJ)
Cormie et al. (2010)
8 strength trained males
7 × 6 reps of jump squat at 0% 1-RM (2 sessions) & 3 × 5 reps of jump squat at 30% 1-RM (1 session)
10 weeks (3 sessions/week)
Increase in Kleg (CMJ)
Connie et al. (2010)
8 strength trained males
3 × 3–6 reps of back squat at 75–90% 1-RM
10 weeks (3 sessions/week)
Increase in Kleg (CMJ)
Hunter & Marshall (2002)
14 males (mixed sports)
1–4 × 3–8 reps of CMJs, 1–2 × 6–10 reps of DTs (30–90cm) & 2–3 × 6–10 reps of deadlift/squat at 60–100% 1-RM
10 weeks (2 sessions/week)
Increase in Kleg (CMJ) Decrease in Kleg (DJ 30,60 & 90 cm)
3–5 × 3–5 reps of hamstring curl, leg press, seated press, parallel squat, leg extension, & heel raise at >90% 1-RM
14 weeks (2 sessions/week)
No change in Kleg (hopping) Increase in Kleg (running)
Arabatzi & 9 physically 4–6 × 4–6 reps of power clean, snatch, clean and Kellis active jerk, high pull, half-squat at >85% 1-RM (2012) males
8 weeks (3 sessions/week)
Increase in Kleg (DJ 20 & 60 cm)
Arabatzi & 9 physically 4–6 × 4–6 reps of leg press, leg curl, leg extension, Kellis active bench press, half-squat at >85% 1-RM (2012) males
8 weeks (3 sessions/week)
Increase in Kleg (DJ 20 cm) Decrease in Kleg (DJ 60 cm)
Toumi et al. 8 male (2004) handball players
6 × 10 reps of leg press at 70% 1-RM & 3 × 5 reps 6 weeks (4 of cross-over jump sessions/week)
Increase in Kleg (CMJ)
Kubo et al. 24 (2007) physically males
5 × 10 reps of unilateral hopping & DJs (20cm) at 40% 1-RM
12 weeks (4 sessions/week)
Increase in Kankle (DJ 20 cm)
Kubo et al. 24 (2007) physically males
5 × 10 reps of unilateral calf raise at 80% 1-RM
12 weeks (4 sessions/week)
No change in Kankle (DJ 20 cm)
Millet et al. 7 male (2002) triathletes
Notes: CMJ = countermovement jump, DJ = drop jump
In contrast to the contradictory Kleg and Kjoint adaptations brought about via traditional resistance training interventions mentioned above, all training programmes that included either plyometric, ballistic or Olympic weightlifting exercises increased Kleg and Kjoint (Cormie et al., 2010; Kubo et al., 2007; Arabatzi and Kellis, 2012). The differential adaptations to Kleg and Kjoint following different exercise modalities and intensities have been attributed to the different mechanisms that modulate MTS attainment. For example, heavy resistance training (≥80% 1RM) leads to greater strength (i.e., muscle force) capacity, and although muscle strength is not a direct measure of muscle stiffness, it can be thought of as a proxy for stiffness (Pearson and McMahon, 2012). Additionally, tendon stiffness, is related to the force producing capacity of the muscle (Arampatzis et al., 2007; Muraoka et al., 2005), and, as has been shown in several studies, tendon stiffness increases in response to traditional resistance training, in addition to isometric and eccentric-focussed training (refer to the recent systematic review and meta-analysis on this topic by Bohm et al., 2015). Alternatively, enhanced muscle recruitment strategies (as is commonly associated with plyometric training and weightlifting [Chimera et al., 2004; Arabatzi and Kellis, 2012]) may explain increased post-training Kleg and Kjoint (Taube et al., 2012), as muscle strength and tendon stiffness generally do not increase following plyometric training (Kubo et al., 2007; Bohm et al., 2015) unless performed with a very high volume (Fouré et al., 2010, 2011). The mixed results of training studies presented in Table 3.1, particularly when interpreted alongside the underpinning mechanisms for MTS adaptation, highlight the efficacy of including both traditional resistance (i.e., strength) and power-focussed exercises in a training programme designed to increase MTS. Traditional resistance exercises, particularly when utilised by relatively weak athletes, should be performed for at least 8–12 weeks as this is the minimum amount of time likely needed to induce increases in tendon stiffness, despite muscle strength gains occurring from as soon as 4 weeks (Kubo et al., 2012, 2010). If an athlete is relatively strong then it may be prudent to include low-load SSC tasks alongside traditional resistance exercises (particularly as they progress through the training weeks) to facilitate the previously mentioned enhanced muscle activation strategies that can be gained through this (Chimera et al., 2004). Because increases in muscle strength generally outweigh increases in tendon stiffness, due to the differential time-course of adaptation of these structures to resistance training (Kubo et al., 2012, 2010), moderate-high-load SSC tasks performed too early may lead to excessive strain of the lower limb tendons (McMahon et al., 2013a). Thus these should be avoided until at least after the 12-week resistance training period, unless the athlete is deemed to be ‘strong’ (see Chapter 2) and is used to performing such SSC tasks.
REFERENCES Alexander, R. M. (1997) Invited Editorial on “Interaction of leg stiffness and surface stiffness during human hopping”. Journal of Applied Physiology, 82, 13–14. Arabatzi, F. & Kellis, E. (2012) Olympic weightlifting training causes different knee muscle-coactivation adaptations compared with traditional weight training. The Journal of Strength and Conditioning Research, 26, 2192–2201. Arampatzis, A., Bruggemann, G. P. & Klapsing, G. M. (2001a) Leg stiffness and mechanical energetic processes during jumping on a sprung surface. Medicine and Science in Sports and Exercise, 33, 923–931. Arampatzis, A., Bruggemann, G. P. & Metzler, V. (1999) The effect of speed on leg stiffness and joint kinetics in human running. Journal of Biomechanics, 32, 1349–1353.
Arampatzis, A., Karamanidis, K., Morey-Klapsing, G., De Monte, G. & Stafilidis, S. (2007) Mechanical properties of the triceps surae tendon and aponeurosis in relation to intensity of sport activity. Journal of Biomechanics, 40, 1946–1952. Arampatzis, A., Schade, F., Walsh, M. & Bruggemann, G. P. (2001b) Influence of leg stiffness and its effect on myodynamic jumping performance. Journal of Electromyography and Kinesiology, 11, 355–364. Asmussen, E. & Bonde-Petersen, F. (1974) Storage of elastic energy in skeletal muscles in man. Acta Physiologica Scandinavica, 91, 385–392. Balsalobre-Fernández, C. Hovannes, A. & Jean-Benoit, M. (2017) The Validity and Reliability of an iPhone App for Measuring Running Mechanics. Journal of Applied Biomechanics, 33, 222–226. Blickhan, R. (1989) The spring mass model for running and hopping. Journal of Biomechanics, 22, 1217–1227. Bohm, S., Mersmann, F. & Arampatzis, A. (2015) Human tendon adaptation in response to mechanical loading: a systematic review and meta-analysis of exercise intervention studies on healthy adults. Sports Medicine – Open, 1, 1–18. Brughelli, M. & Cronin, J. (2008a) Influence of running velocity on vertical, leg and joint stiffness: modelling and recommendations for future research. Sports Medicine, 38, 647–657. Brughelli, M. & Cronin, J. (2008b) A review of research on the mechanical stiffness in running and jumping: methodology and implications. Scandinavian Journal of Medicine and Science in Sports, 18, 417–426. Butler, R. J., Crowell, H. P. & Davis, I. M. (2003) Lower extremity stiffness: implications for performance and injury. Clinical Biomechanics, 18, 511–517. Cavagna, G. A., Dusman, B. & Margaria, R. (1968) Positive work done by a previously stretched muscle. Journal of Applied Physiology, 24, 21–32. Cavagna, G. A., Franzetti, P., Heglund, N. C. & Willems, P. (1988) The determinants of the step frequency in running, trotting and hopping in man and other vertebrates. The Journal of Physiology, 399, 81–92. Cavagna, G. A., Saibene, F. P. & Margaria, R. (1965) Effect of negative work on the amount of positive work performed by an isolated muscle. Journal of Applied Physiology, 20, 157–158. Cavanagh, P. & Komi, P. (1979) Electromechanical delay in human skeletal muscle under concentric and eccentric contractions. European Journal of Applied Physiology and Occupational Physiology, 42, 159–163. Chelly, S. M. & Denis, C. (2001) Leg power and hopping stiffness: relationship with sprint running performance. Medicine and Science in Sports and Exercise, 33, 326–333. Chimera, N. J., Swanik, K. A., Swanik, C. B. & Straub, S. J. (2004) Effects of plyometric training on muscle-activation strategies and performance in female athletes. Journal of Athletic Training, 39, 24–31. Cormie, P., McGuigan, M. R. & Newton, R. U. (2010) Changes in the eccentric phase contribute to improved stretch-shorten cycle performance after training. Medicine and Science in Sports and Exercise, 42, 1731–1744. Cormie, P., McGuigan, M. R. & Newton, R. U. (2011) Developing maximal neuromuscular power part 1– biological basis of maximal power production. Sports Medicine, 41, 17–38. Cronin, N. J., Carty, C. P. & Barrett, R. S. (2011) Triceps surae short latency stretch reflexes contribute to ankle stiffness regulation during human running. PLoS ONE, 6, e23917. Dalleau, G., Belli, A., Viale, F., Lacour, J. R. & Bourdin, M. (2004) A simple method for field measurements of leg stiffness in hopping. International Journal of Sports Medicine, 25, 170–176. Devita, P. & Skelly, W. A. (1992) Effect of landing stiffness on joint kinetics and energeics in the lower-extremity. Medicine and Science in Sports and Exercise, 24, 108–115. Dutto, D. J. & Smith, G. A. (2002) Changes in spring-mass characteristics during treadmill running to exhaustion. Medicine and Science in Sports and Exercise, 34, 1324–1331. Farley, C. T., Blickhan, R., Saito, J. & Taylor, C. R. (1991) Hopping frequency in humans: a test of how springs set stride frequency in bouncing gaits. Journal of Applied Physiology, 71, 2127–2132. Farley, C. T. & Gonzalez, O. (1996) Leg stiffness and stride frequency in human running. Journal of Biomechanics, 29, 181–186. Farley, C. T., Houdijk, H. H. P., Van Strien, C. & Louie, M. (1998) Mechanism of leg stiffness adjustment for hopping on surfaces of different stiffnesses. Journal of Applied Physiology, 85, 1044–1055. Farris, D. J., Trewartha, G. & McGuigan, M. P. (2011) Could intra-tendinous hyperthermia during running explain chronic injury of the human Achilles tendon? Journal of Biomechanics, 44, 822–826. Fouré, A., Nordez, A. & Cornu, C. (2010) Plyometric training effects on Achilles tendon stiffness and dissipative properties. Journal of Applied Physiology, 109, 849–854. Fouré, A., Nordez, A., McNair, P. & Cornu, C. (2011) Effects of plyometric training on both active and passive parts of the plantarflexors series elastic component stiffness of muscle-tendon complex. European Journal of Applied Physiology, 111, 539– 548. f*ckashiro, S. & Komi, P. V. (1987) Joint moment and mechanical power flow of the lower limb during vertical jump. International Journal of Sports Medicine, 8, 357. Geyer, H., Seyfarth, A. & Blickhan, R. (2006) Compliant leg behaviour explains basic dynamics of walking and running. Proceedings of the Royal Society B: Biological Sciences, 273, 2861–2867. Gunther, M. & Blickhan, R. (2002) Joint stiffness of the ankle and the knee in running. Journal of Biomechanics, 35, 1459–1474.
Heise, G. D. & Martin, P. E. (1998) “Leg spring” characteristics and the aerobic demand of running. Medicine and Science in Sports and Exercise, 30, 750–754. Hobara, H., Inoue, K., Gomi, K., Sakamoto, M., Muraoka, T., Iso, S. & Kanosue, K. (2010) Continuous change in spring-mass characteristics during a 400 m sprint. Journal of Science and Medicine in Sport, 13, 256–261. Hobara, H., Inoue, K., Omuro, K., Muraoka, T. & Kanosue, K. (2011) Determinant of leg stiffness during hopping is frequencydependent. European Journal of Applied Physiology, 111, 2195–2201. Hobara, H., Muraoka, T., Omuro, K., Gomi, K., Sakamoto, M., Inoue, K. & Kanosue, K. (2009) Knee stiffness is a major determinant of leg stiffness during maximal hopping. Journal of Biomechanics, 42, 1768–1771. Horita, T., Komi, P. V., Nicol, C. & Kryolainen, H. (2002) Interaction between pre-landing activities and stiffness regulation of the knee joint musculoskeletal system in the drop jump: implications to performance. European Journal of Applied Physiology, 88, 76–84. Hunter, J. P. & Marshall, R. N. (2002) Effects of power and flexibility training on vertical jump technique. Medicine and Science in Sports and Exercise, 34, 478–486. Ishikawa, M. & Komi, P. V. (2004) Effects of different dropping intensities on fascicle and tendinous tissue behavior during stretchshortening cycle exercise. Journal of Applied Physiology, 96, 848–852. Ishikawa, M., Niemela, E. & Komi, P. V. (2005) Interaction between fascicle and tendinous tissues in short-contact stretch-shortening cycle exercise with varying eccentric intensities. Journal of Applied Physiology, 99, 217–223. Kerdok, A. E., Biewener, A. A., McMahon, T. A., Weyand, P. G. & Herr, H. M. (2002) Energetics and mechanics of human running on surfaces of different stiffnesses. Journal of Applied Physiology, 92, 469–478. Kirby, T., McBride, J., Haines, T. & Dayne, A. (2011) Relative net vertical impulse determines jumping performance. International Journal of Sports Physiology and Performance, 27, 207–214. Komi, P. V. (2003) Stretch-shortening cycle. In: Komi, P. V. (Ed.) Strength and Power in Sport. 2nd ed. Oxford, Blackwell Science. Kubo, K., Ikebukuro, T., Maki, A., Yata, H. & Tsunoda, N. (2012) Time course of changes in the human Achilles tendon properties and metabolism during training and detraining in vivo. European Journal of Applied Physiology, 112, 2679–2691. Kubo, K., Ikebukuro, T., Yata, H., Tsunoda, N. & Kanehisa, H. (2010) Time course of changes in muscle and tendon properties during strength training and detraining. Journal of Strength and Conditioning Research, 24, 322–331. Kubo, K., Morimoto, M., Komuro, T., Yata, H., Tsunoda, N., Kanehisa, H. & f*ckunaga, T. (2007) Effects of plyometric and weight training on muscle-tendon complex and jump performance. Medicine and Science in Sports and Exercise, 39, 1801–1810. Kuitunen, S., Komi, P. V. & Kyrolainen, H. (2002) Knee and ankle joint stiffness in sprint running. Medicine and Science in Sports and Exercise, 34, 166–173. Laffaye, G., Bardy, B. G. & Durey, A. (2005) Leg stiffness and expertise in men jumping. Medicine and Science in Sports and Exercise 37, 536–543. Laffaye, G. & Choukou, M. A. (2010) Gender bias in the effect of dropping height on jumping performance in volleyball players. The Journal of Strength and Conditioning Research, 24, 2143–2148. Latash, M. L. & Zatsiorsky, V. M. (1993) Joint stiffness: myth or reality? Human Movement Science, 12, 653–692. Lichtwark, G. A. & Barclay, C. J. (2010) The influence of tendon compliance on muscle power output and efficiency during cyclic contractions. The Journal of Experimental Biology, 213, 707–714. Lichtwark, G. A., Bougoulias, K. & Wilson, A. M. (2007) Muscle fascicle and series elastic element length changes along the length of the human gastrocnemius during walking and running. Journal of Biomechanics, 40, 157–164. Lichtwark, G. A. & Wilson, A. M. (2005) In vivo mechanical properties of the human Achilles tendon during one-legged hopping. Journal of Experimental Biology, 208, 4715–4725. Lichtwark, G. A. & Wilson, A. M. (2007) Is Achilles tendon compliance optimised for maximum muscle efficiency during locomotion? Journal of Biomechanics, 40, 1768–1775. Lichtwark, G. A. & Wilson, A. M. (2008) Optimal muscle fascicle length and tendon stiffness for maximising gastrocnemius efficiency during human walking and running. Journal of Theoretical Biology, 252, 662–673. Lockie, R. G., Murphy, A. J., Knight, T. J. & Janse de Jonge, X. A. K. (2011) Factors that differentiate acceleration ability in field sport athletes. The Journal of Strength and Conditioning Research, 25, 2704–2714. Luhtanen, P. & Komi, P. V. (1978) Mechanical energy states during running. European Journal of Applied Physiology and Occupational Physiology 38, 41–48. McMahon, J. J., Comfort, P. & Pearson, S. (2012) Lower limb stiffness: effect on performance and training considerations. Strength and Conditioning Journal, 34, 94–101. McMahon, J. J., Comfort, P. & Pearson, S. (2014) Relationships between medial gastrocnemius tendon stiffness and lower limb stiffness during unilateral hopping. The Journal of Strength and Conditioning Research, 28, S2. McMahon, J. J., Pearson, S. & Comfort, P. (2013a) Changes in medial gastrocnemius muscle-tendon interaction following 8 weeks of resistance training. The Journal of Strength and Conditioning Research, 27, S1–S2. McMahon, J. J., Pearson, S. & Comfort, P. (2013b) Changes in medial gastrocnemius muscle-tendon interaction with an increase in movement frequency. The Journal of Strength and Conditioning Research, 27, S77–S78. McMahon, T. A. & Cheng, G. C. (1990) The mechanics of running – how does stiffness couple with speed? Journal of Biomechanics, 23, 65–78.
McMahon, T. A., Valiant, G. & Frederick, E. C. (1987) Groucho running. Journal of Applied Physiology, 62, 2326–2337. Millet, G. P., Jaouen, B., Borrani, F. & Candau, R. (2002) Effects of concurrent endurance and strength training on running economy and VO2 kinetics. Medicine and Science in Sports and Exercise, 34, 1351–1359. Morin, J. B., Dalleau, G., Kyröläinen, H. H., Jeannin, T. & Belli, A. (2005) A simple method for measuring stiffness during running. Journal of Applied Biomechanics, 21, 167–180. Moritz, C. T. & Farley, C. T. (2004) Passive dynamics change leg mechanics for an unexpected surface during human hopping. Journal of Applied Physiology, 97, 1313–1322. Muraoka, T., Muramatsu, T., f*ckunaga, T. & Kanehisa, H. (2005) Elastic properties of human Achilles tendon are correlated to muscle strength. Journal of Applied Physiology, 99, 665–669. Newton, U. R., Murphy, J. A., Humphries, J. B., Wilson, J. G., Kraemer, J. W. & Häkkinen, K. (1997) Influence of load and stretch shortening cycle on the kinematics, kinetics and muscle activation that occurs during explosive upper-body movements. European Journal of Applied Physiology and Occupational Physiology, 75, 333–342. Pearson, S. J. & McMahon, J. (2012) Lower limb mechanical properties: determining factors and implications for performance. Sports Medicine, 42, 929–940. Perl, D. P., Daoud, A. I. & Lieberman, D. E. (2012) Effects of footwear and strike type on running economy. Medicine and Science in Sports and Exercise, 4, 1335–1343. Pruyn, E. C., Watsford, M. & Murphy, A. (2014) The relationship between lower-body stiffness and dynamic performance. Applied Physiology, Nutrition, and Metabolism, 39, 1144–1150. Rabita, G., Slawinski, J., Girard, O., Bignet, F. & Hausswirth, C. (2011) Spring-mass behavior during exhaustive run at constant velocity in elite triathletes. Medicine and Science in Sports and Exercise, 43, 685–692. Roberts, T. J. & Marsh, R. L. (2003) Probing the limits to muscle-powered accelerations: lessons from jumping bullfrogs. The Journal of Experimental Biology, 206, 2567–2580. Serpell, B. G., Ball, N. B., Scarvell, J. M. & Smith, P. N. (2012) A review of models of vertical, leg, and knee stiffness in adults for running, jumping or hopping tasks. Journal of Sports Sciences, 30, 1347–1363. Stefanyshyn, D. J. & Nigg, B. M. (1998) Contribution of the lower extremity joints to mechanical energy in running vertical jumps and running long jumps. Journal of Sports Sciences, 16, 177–186. Taube, W., Leukel, C. & Gollhofer, A. (2012) How neurons make us jump: The neural control of stretch-shortening cycle movements. Exercise and Sport Sciences Reviews, 40, 106–115. Taylor, M. J. D. & Beneke, R. (2012) Spring mass characteristics of the fastest men on earth. International Journal of Sports Medicine, 33, 667–670. Toumi, H., Best, T. M., Martin, A. & Poumarat, G. (2004) Muscle plasticity after weight and combined (weight plus jump) training. Medicine and Science in Sports and Exercise, 36, 1580–1588. Turner, A. N. & Jeffreys, I. (2011) The stretch-shortening cycle: proposed mechanisms and methods for enhancement. Strength and Conditioning Journal, 32, 87–99. Van Ingen Schenau, G. J., Bobbert, M. F. & DeHaan, A. (1997a) Does elastic energy enhance work and efficiency in the stretchshortening cycle? Journal of Applied Biomechanics, 13, 389–415. Van Ingen Schenau, G. J., Bobbert, M. F. & DeHaan, A. (1997b) Mechanics and energetics of the stretch-shortening cycle: a stimulating discussion. Journal of Applied Biomechanics, 13, 484–496. Walshe, A. D. & Wilson, G. J. (1997) The influence of musculotendinous stiffness on drop jump performance. Canadian Journal of Applied Physiology, 22, 117–132. Weyand, P. G., Sandell, R. F., Prime, D. N. L. & Bundle, M. W. (2010) The biological limits to running speed are imposed from the ground up. Journal of Applied Physiology, 108, 950–961. Weyand, P. G., Sternlight, D. B., Bellizzi, M. J. & Wright, S. (2000) Faster top running speeds are achieved with greater ground forces not more rapid leg movements. Journal of Applied Physiology, 89, 1991–1999.
CHAPTER 4
Endocrinology and resistance training Anthony Turner and Christian Cook INTRODUCTION The endocrine system includes all tissues and glands that secrete hormones into the circulatory system. In this chapter, we focus on those involved in resistance training, mainly (1) the anabolic hormone (those that directly or pervasively promote tissue building) testosterone and (2) the primary catabolic hormone (promoting tissue degradation or repartitioning of energy reserves) cortisol. To a large extent, these hormones can influence our motivation to train, the loads we lift, performance gains and our ability to cope with large volumes of training stress. Naturally then, understanding their effects as part of a periodised strength and conditioning (S&C) programme is important if increases in strength, hypertrophy and general performance are to be optimised; providing this information is therefore the aim of this chapter. Testosterone (T) and cortisol are affected by the following strength training variables: exercise modality (involved musculature), exercise sequence, intensity (load), sets and repetitions (volume) and rest period. They are also affected by preconditioning (priming) strategies (discussed in Chapter 10) and environmental stimuli, such as observers, training partners and visual images, for example. Finally, the individual athlete is also a factor, with elite athletes often showing different patterns to sub-elite counterparts due to training history and base line strength. The manipulation of each of these variables will be discussed throughout, but first we will describe the fundamental role of receptors and the significance of muscle remodelling.
HORMONE-RECEPTOR COMPLEX Hormones can be defined as chemical messengers that are transported to specific target cells which possess specific hormone receptors. The specificity of a hormone and its receptor is often explained using the lock and key theory, whereby the receptor is the lock and the hormone is the key. It is important to note that while the concentration of hormones is important, so too is the number of receptors available, as this ultimately determines the possibility of interactions. For example, when a cell has reached its genetic ceiling for adaptation (e.g., through protein accretion), receptors may become non-responsive and down-regulate, thus reducing the probability of hormonal binding (Kraemer et al., 2008). Alternatively, receptors can up-regulate and increase the probability of interactions. In essence, exposure to T and stress can alter both affinity and the number of androgen receptors, which can change the probability of a response (Basualto-Alarcón et al., 2013). For
example, Kadi et al. (2000) reported that in response to continued resistance training, power lifters had a greater number of androgen receptors in their trapezius muscle, and thus an enhanced ability to use T. In addition, Ratamess et al. (2005) have shown significant correlations between baseline androgen receptor content in the vastus lateralis and 1RM squat, further suggesting that androgen receptor content may assist in mediating strength changes during resistance training.
MUSCLE REMODELLING Muscle remodelling involves the disruption of muscle fibres (stimulus/load dependent) in response to mechanical loading, resulting in the inflammatory process (immune cells and catabolic hormones) and subsequent release of anabolic hormones (Clarkson & Tremblay, 1998). In addition, mechanical loading increases receptor and membrane permeability to hormones and nutrients, therefore tissue activation may be considered a precursor to anabolism (Kraemer & Ratamess, 2005). Consequently, only the recruited muscle fibres can be remodelled (Kraemer et al., 2008), emphasising the need to exercise muscle groups in a sport-specific manner (including range of motion, muscle action, velocity of movement, force generation and relative intensity), and the need to utilise progressive overload. The latter will increase motor unit recruitment, thereby exposing a greater number of muscle fibres to hormone-tissue interactions (Kraemer & Ratamess, 2005). Given the need to induce muscle damage (and thus an inflammatory response) so that adaptations can occur, it is interesting to consider whether implementing recovery strategies during phases in which hypertrophy is the goal, is actually detrimental. Because hypertrophy occurs in response to damage, strategies that actually reduce the subsequent inflammatory response, such as contrast water therapy, compression garments and massage, may limit its effect. Such suggestions may influence team-sport, pre-season recovery routines, where hypertrophy may be sought, vs. in-season routines, where performance maintenance is fundamental and must be quickly re-established following games. Current practices thus appear to discourage recovery strategies in the off-season, and only include them during the season and when in close proximity to competitions. This theory is discussed further in Chapter 12.
TESTOSTERONE Testosterone is responsible for the development of male secondary sex characteristics, spermatogenesis and the male skeletal system. Pertinent to this discussion, T is involved in the muscle growth and protein retention observed during strength training through its direct (i.e., muscle growth) and indirect (e.g., stimulation of growth hormone and neuron receptors and effects on training motivation) affects on muscle tissue (Fleck & Kraemer, 2004; Kraemer et al., 2008). Moreover, due to its anabolic effects, the levels of circulating T have been proposed as a physiological marker to evaluate the anabolic status of the body (Hakkinen et al., 1985). Finally, T is also related to behaviour modification, and more recent research appears to see this as being its greatest asset within training and performance adaptations; our discussion of T thus starts here.
Testosterone and behaviour Testosterone’s correlation to strength and hypertrophy may reflect its biomarker potential for stress,
rather than simply its direct anabolic effects on muscle (Crewther et al., 2012). More recent research in sport has started to exploit T’s known effect on behaviour (Aleman et al., 2004), including increasing aggression (Hermans et al., 2008), risk-taking (Ronay & von Hippel, 2010) and unconscious motivation (Aarts & van Honk, 2009), as well as exploring its modulation via nonphysical interventions. This has been demonstrated previously, for example, through visual images including sports fans watching their teams win (Bernhardt et al., 1998), competing at the home stadium (Neave & Wolfson, 2003) and watching previous victories (Carré & Putman, 2010). Also through watching a sexually arousing film (Stoléru & Ennaji, 1993) and being in a position regarded as powerful in display (Carney & Cuddy, 2010). Therefore, it has been proposed that utilising T’s ability to modulate behaviour through increased training motivation will positively influence training based outcomes (Cook & Beaven, 2013). In fact, in elite athletes who train closer to their maximum, this effect may be more influential than that of anabolism; these qualities result in a higher quality and quantity of work performed which in turn promote strength and hypertrophy using other anabolic functions. Given these findings, the S&C coach can maximise sessions and competition performance by identifying methods of psychological priming or preconditioning. In support of such priming, the volitional training performance of elite female athletes when selfselecting a 3RM workload was strongly related to individual variation in pre-exercise salivary T concentrations within a training program. Relationships were found in the bench press (R2 = 0.70), back squat (R2 = 0.45) and power production via a maximal-distance medicine ball throw (R2 = 0.50); similar results have also been found in males (Crewther et al., 2009a). Therefore, volitional workload selection and performance are correlated to relative pre-exercise salivary T levels. As such, in elite athletes, free T may be a useful marker of voluntary effort and its role here may supersede its role on muscle hypertrophy via protein synthesis. For example, given that small, between-session increases in total load (i.e., continued overload) are indicative of adaptations and become more difficult as the athlete progresses in training age, the athlete’s voluntary effort partially reflects their state of motivation, recovery and readiness to perform in individual training sessions (Cook & Beaven, 2013). Interestingly, then, previous associations found between strength, power and T levels (discussed below) may also be related to an enhanced psychological desire to perform well. Therefore, in addition to priming T via physical interventions such as prior workouts and exercise order (again discussed below), T may also be primed via non-physical interventions such as videos, feedback and peer assessment; a summary of studies examining this is outlined in Table 1.
Testosterone and strength and power As well as cellular interactions, T can bind with receptors on neurons and therefore increase instantaneous muscle strength and recruited muscle mass (Kraemer et al., 2008; Kraemer & Ratamess, 2005). This is achieved through an increase in neurotransmitter release and structural adaptations of the neuromuscular junction (Fleck & Kraemer, 2004; Nagaya & Herrera, 1995), where T-nervous interactions can regenerate nerves and increase the cell body size and dendrite length and diameter (Nagaya & Herrera, 1995). These neural adaptations (along with behavioural modifications), coupled with its effects on calcium handling and muscle contractility (Curl et al., 1989), may demonstrate an advanced strategy to increase force capability. For example, basal serum T levels have been correlated to average power output, jump height and both power and work performed during 60s continuous jumping (Bosco et al., 1996b). Basal T levels have also been correlated with
countermovement jump height, strength and sprint speed in professional male rugby players (Crewther et al., 2012; Crewther et al., 2009b), soccer players (Bosco et al., 1996a) and elite women athletes (Cardinale & Stone, 2006). These correlations may be due, in part, to T’s significant effects on motor neurons (Viru et al., 2003), and serves to highlight the importance of increased T concentrations and the significance of T-nervous interactions within sports performance. Given the aforementioned benefits of T on strength, power and training motivation, it appears prudent to coincide training with periods of increased T availability. TABLE 4.1 Individual studies examining the priming of testosterone via non-physical interventions such as videos, feedback and peer assessment Motivational videos Cook & Crewther (2012a) examined the acute effects of video clips on salivary T and cortisol (C) concentrations and subsequent 3RM squat performances in elite male rugby players. They found that significant (p > 0.001) increases in T concentrations were noted with watching erotic, humorous, aggressive and training videos, with T decreasing significantly (versus control) after a sad clip. A significant improvement in 3RM performances was noted after the erotic, aggressive and training clips and a strong withinindividual correlation (r = 0.85) was noted between the relative changes in T and the 3RM squats across all video sessions. Finally, the aggressive video clip induced the largest relative change in T. The authors suggested that findings may be related to T’s (behavioural) effect on risk-taking (Ronay & von Hippel, 2010), whereby they were willing to try and lift a heavier weight. Pre-match video with feedback Given that a pre-match talk, often with video analysis, is commonplace in elite sport, Crewther & Cook (2012b) assessed the T and C response following this. They hypothesised that watching a video clip of successful skill execution by the player with positive coach feedback (VPCF) would produce the largest pre-game T responses, the smallest cortisol (C) responses and the best performance outcomes. This was compared to watching a video clip of successful skill execution by an opposing player with cautionary coach feedback (VCCF), and the player left alone to self-motivate (SM). Salivary free T and C, along with player performance as rated by the coach, were indeed best in the former condition, with VCCF producing the largest C response. Across all treatments, greater individual T responses and lower C responses were associated with better performance outcomes. Post-match video with feedback Crewther and Cook (2012) tested the effects of different post-match video and feedback interventions on the subsequent hormonal responses to a physical stress-test (i.e., three sets of power cleans, back squats and bench press) and game performance in professional rugby union players. On four occasions, players completed a video session (one hour each) with accompanying coach feedback the day after a rugby union match. The interventions showed either video footage of player mistakes with negative coach feedback (NCF1) or player successes with positive feedback (PCF1). The PFC approach was associated with significantly (p > 0.01) greater free T (36% to 42%) and associated with higher (28% to 51%) pre-game T concentrations and superior game-ranked performances. The authors concluded that the post-game presentation of specific video footage combined with different coach feedback influenced the free hormonal state of rugby players and game performance several days later. Their results further support the reciprocal model (Mazur & Booth, 1998), which states that free hormones not only influence behaviour, but also are in turn affected by behaviour. Social environment and video presentations Cook & Crewther (2014) examined the social environment effects during a post-match video presentation on the subsequent hormonal responses and match performance in professional male athletes. To modify the social environment the video presentations were completed in the presence of: (1) strangers who were bigger (SB), (2) strangers who were smaller (SS), (3) friends who were bigger (FB) and (4) friends who were smaller (FS). The T responses to the stress test differed in magnitude across each intervention (SS > SB and FB > FS), as did C responsiveness (SB > SS > FS and FB). This agreed with previous research showing that T levels increased when they defeated strangers, but not their friends (Wagner et al., 2002). Differences in male T concentrations have also been demonstrated when interacting socially with other males simply perceived to be similar (i.e., increasing T) or dissimilar (i.e., lowering T) (DeSoto et al., 2009). Coaches can use this information to determine the suitability of feedback, not simply in terms of whether it is positive or not, but the audience with which it is shared in front of.
Manipulating exercise sessions to enhance testosterone release Testosterone exhibits diurnal variations whereby concentrations are typically higher in the morning and drop throughout the day; this is also the case for cortisol, however (Lejune-Lenain et al., 1987). The question emerges of whether it is better to exercise in the morning when concentrations are highest, or to exercise in the evening to maintain increased concentrations throughout the day (Kraemer et al., 2008). Cook et al. (2013) have investigated the effect of offsetting the circadian decline in T through morning training; they compared the efficacy of a morning strength or sprint session on afternoon performance. They found that the addition of morning short sprints potentiated subsequent afternoon sprints only, however, a short weights session increased not only afternoon sprint performance, but also measures of maximal strength and lower body power; both interventions increased T above a control group. This finding is supported through data investigating afternoon throwing performance in shot-putters following a morning resistance training session (Ekstrand et al. 2013). Here afternoon throwing performance was improved for up to 6 hours. Teo et al. (2011) investigated the effects of circadian rhythm on a single training session on maximal force production and power output. Results revealed that both, measured within countermovement jumps, squat jumps, isometric pulls and 1RM squats, were highest at 4 p.m. compared to 8 a.m. (lowest), 12 p.m. and 8 p.m. (both similar). This pattern was mirrored by aural temperature, with the increase in body temperature considered largely responsible. Four p.m. also revealed the lowest rating of perceived exertion (RPE) and collectively data argues that coaches and athletes should consider scheduling training or testing sessions around this time (Teo et al., 2011), or at least consider the significance an increase in core body temperature has; this is discussed further in Chapter 10. Perhaps two sessions, with the first being resistance training based and the second, consisting of more sport-specific speed and power based drills, commencing at 4 p.m., is ideal. Beaven et al. (2011) investigated the ordering of exercises within a training session to identify which exercise sequence provides an enhanced anabolic milieu for adaptation; specifically, should you programme strength exercises first or power exercises first? The power block consisted of three sets of three repetitions of jump squat exercise at 50% of 1RM and the strength block consisted of three sets of three repetitions of box squat at 3RM. The hormonal response after the strength–power bout was greatest, demonstrating small increase in T (13% ± 7%) and a trivial increase in cortisol (27% ± 30%). Results thus suggest that this exercise sequence is optimal in creating an anabolic environment. Finally, T concentrations during training sessions have been reported to remain elevated for up to 45 to 60 minutes and decrease from then on (Zatsiorsky & Kraemer, 2006). Viru et al. (2003) further suggested that following training sessions of 1-hour duration, the testosterone: cortisol (T:C) ratio (discussed below) may decrease as a fatigue phenomenon. It may be prudent therefore to limit exercise sessions to ≤60 minutes as beyond this duration the session may begin to progress towards catabolism, whereby more receptors become responsive to cortisol interactions. Such an approach possibly warrants splitting the days training objectives into two to three ~30 minute sessions, rather than one longer duration session. However, it should be noted that such advice may best suit strength and power based training as hypertrophy sessions may be required to extend beyond this given the need to train to failure across multiple exercises; more recent research defines this as more important than the concentration of hormones. This is discussed below.
Manipulating acute resistance training variables to enhance testosterone release
Large muscle group exercises such as squats, deadlifts (Fahey et al., 1976), Olympic lifts (Kraemer et al., 1992) and jump squats (Volek et al., 1997) significantly increase T concentrations, whereas little or no change has been reported with bench press and exercises involving smaller musculature (Kraemer et al., 2008; Fleck & Kraemer, 2004). It may be advised that, within a training session, large muscle group exercises are performed before small muscle group exercises in order to expose the smaller musculature to the increased concentrations of T (Kraemer & Ratamess, 2005). This is supported by Hansen et al. (2001) who measured strength changes in elbow flexors following nine weeks of strength training. Two groups performed elbow flexion exercises, however, one group preceded these with lower body exercise. Only this group significantly increased acute T concentrations with concomitant increases in the strength of the elbow flexors. Hakkinen & Pakarinen (1993) report increases in T (and growth hormone) following ten sets of ten repetitions at 70% 1RM, but no significant changes following twenty sets of 1RM. Further, Bosco et al. (2000) reported no change following ten sets of two to three repetitions, but when the volume increased to twenty sets of two to four repetitions, increases in T were noted. A moderate to high volume of exercise, achieved with multiple sets, repetitions or exercises may be required as the release of T may be correlated with lactate accumulation (Lin et al., 2001; Linnamo et al., 2005; Lu et al., 1997). Kraemer et al. (1991, 1990) and Beaven et al. (2008a) summarise that bodybuilding (hypertrophy) programmes, utilising moderate load, high volume training, with short rest periods are most effective for stimulating acute T increases. It should be noted that this prescription of training (three sets of ten repetitions, short rest periods) also notes the highest release of growth hormone with both hormones seemingly released maximally following high levels of lactate and hydrogen ions (Godfrey et al., 2009). It may be that lactate acts as a pseudo-hormone, but further research is required to fully elucidate its signalling role in this context (Godfrey et al., 2009). This association explains the muscle group-focussed sessions and short rest periods of bodybuilders, as sessions that alternate between body parts may allow for the dissipation of lactate and therefore reduce the T and growth hormone (GH) response. It may also explain the commonly used slow-continuous method (e.g., 4s concentric and 4s eccentric), as this would increase time under tension (facilitating the accumulation of lactate and hydrogen ions (H+), reduce local blood circulation (with total occlusion occurring at loads >45% 1RM) and promote venous pooling. The consequent promotion of blood pooling and fluid volume shifts in order to maintain osmotic pressure may then increase the concentration of hormones, time available for interaction and, therefore, the probability of hormone-receptor interactions. It must be noted, however, that such low velocity training does not translate effectively to enhanced strength, power or performance in athletic tasks.
Testosterone, growth hormone and hypertrophy Despite the above research, sole reliance (or rather assumed best practice) on the above “bodybuilding” style programming to design hypertrophy-based sessions has become contentious. Recent studies have questioned the direct role of T and growth hormone in response to exercise stimuli in promoting hypertrophy and indeed strength; these suggest that neither circulating hormones nor indeed load (Morton et al., 2016; Schoenfeld et al., 2015; West et al., 2009; West & Phillips, 2012) affect these outcomes. While they, like others, have shown that concentrations of T and growth hormone (and also cortisol) are increased as a result of an acute exercise bout (p < 0.001) over a 12-week training period (training 4 times/week), there is no significant change from baseline, and nor do concentration changes significantly correlate with any physical measure (e.g., changes in muscle cross
sectional area, lean body mass and strength increases in the bench, shoulder and leg press). Instead, both hypertrophy and strength increases can be achieved through high and low repetition training (using loads of 30–50% and 75–90% of 1RM, respectively) provided exercises are performed until volitional failure (Morton et al., 2016). The comparable gains in muscle cross sectional area and strength of high repetition training (relative to low repetition training) are likely because the former involves a higher volume, which requires maximal activation of motor units (Morton et al., 2016). It should be noted, however, that strength gains are still greatest using higher loads; this is discussed briefly below, but more detail is found in Chapter 2. There is growing consensus that volume load and training to muscular failure are the causative factors for muscle hypertrophy. The latter increases motor unit recruitment and thus the quantity of muscle fibres that are exposed to the stimulus and undergo the remodelling process. Perhaps traditional hypertrophy programmes (i.e., three sets of ten, short rest) are only more beneficial with respect to time, as you can fit more volume in within a shorter period of time? These answers may be further gleaned from the studies identified in Table 4.2. TABLE 4.2 Individual studies examining load, rest and hormones on hypertrophy and strength Effects of low vs. high load resistance training on muscle strength and hypertrophy Schoenfeld et al. (2015) compared a low load routine of 25–35 repetitions to a moderate load routine of 8–12 repetitions. Both groups performed three sets of seven different exercises representing all major muscles, with all sets performed to or near failure. Training was performed three times per week on non-consecutive days, for a total of eight weeks. Both high load and moderate load conditions produced significant increases in cross-sectional area (CSA), with no significant differences between groups. Improvements in back squat and bench press strength were greatest in the high load group, but only significant in the former. Upper body muscle endurance (assessed by the bench press at 50% 1RM to failure) improved, albeit non-significantly, to a greater extent in low load group. Both load conditions can increase hypertrophy, with changes in strength and endurance showing some specificity to load. Effects of different volume-equated resistance training loading strategies on muscular adaptations Schoenfeld et al. (2014) investigated adaptations to a volume-equated bodybuilding-type training program (3 sets of 10 with 90s rest) vs. a powerlifting-type routine (7 sets or 3RM with 3min rest) in well-trained subjects. After eight weeks, no significant differences were noted in muscle thickness of the biceps brachii, but significant differences were found in 1RM bench press, and a trend was found for greater increases in the 1RM squat; these gains naturally favoured the powerlifting approach. In conclusion, this study showed that both bodybuilding- and powerlifting-type training promote similar increases in muscular size, but powerlifting-type training is superior for enhancing maximal strength. The effect of inter-set rest intervals on resistance exercise-induced muscle hypertrophy Henselmans & Schoenfeld (2014) investigated the effect of inter-set rest intervals on resistance training-induced muscular hypertrophy. Their review revealed that the rest period recommendations of 30s to 1min, to mediate an elevation in post-exercise serum growth hormone levels, have become untenable; no study has demonstrated greater muscle hypertrophy using shorter compared with longer rest intervals.
Novice vs. experienced vs. well trained vs. elite Despite the above research, it is becoming increasingly important to differentiate between studies in novices, experienced or well trained and those regarded as elite. In this context, this continuum defines either strength and conditioning experience, normally recognised by measures of maximal strength, and/or level of sports performance and thus exposure to high-level environments and competitions (and associated stress). Many studies suggest a considerable difference between these
levels of athletes, with the reported associations between T and physical performance best demonstrated in elite-trained athletes (Crewther et al., 2011). For example, Crewther et al. (2012) only found relationships between salivary free T concentrations and back squat (1RM; r = 0.92) and sprinting (10m; r = 0.87) performance in those who could squat double body weight – the reasons for this are likely multifaceted and covered throughout this chapter, including via the dual-hormone hypothesis described below. Of note, the aforementioned correlations found above, are despite there being no difference in T concentrations between groups (i.e., 1RM > 2.0 × body weight vs. 1RM < 1.9 × body weight). Therefore, it may be that training background and strength levels are most important, as these are indicative of Type II fibre content and androgen receptor content, and infer enhanced motivation and risk taking behaviours, for example, these represent the enhanced ability to actually use free T. Therefore, more needs to be done to differentiate responses across populations, which may evolve into training paradigms that shift accordingly. It is also important to consider individual responses to resistance training; this is especially the case when working with elite athletes. Pooling data (and thus presenting means only) can have an impact on both the validity of the results and the interpretation of study findings. For example, Beaven et al. (2008b) compared acute individual T responses of professional elite rugby players across commonly prescribed resistance training protocols (4 × 10 at 70%, 3 × 5 at 85%, 5 × 15 at 55%, or 3 × 5 at 40%). They showed an insignificant protocol effect on T concentration when considered as a hom*ogenous group. However, when individual data among protocols were examined, a clear protocol-dependent effect was observed. Each individual athlete seemed to respond optimally, in terms of a T concentration increase, to one or two of the protocols, with minimal responses to the other protocols. Therefore, the protocol considered optimal in terms of anabolic response differed among individuals. However, as aforementioned, changes in T do acutely influence training motivation, and thus load lifted and perhaps in this context, the ability to lift until true muscle fatigue across several sets. The at least pervasive effect of T on strength and hypertrophy is nicely surmised by Beaven et al. (2008a). They identified that (1) men show muscle growth at puberty when T production increases (Ramos et al., 1998); (2) aging men gradually lose muscle mass and strength, and exogenous application of T can reverse this (Anawalt & Merriam, 2001); (3) T replacement increases the fat-free mass and muscle size caused by hypogonadism (i.e., reduction or absence of hormone secretion or other physiological activity of the gonads) (Bhasin et al., 1997; Aleman et al., 2004); (4) exogenous application of supraphysiologic doses of T in men results in greater strength and muscle gains from resistance exercise (Bhasin et al., 1999; Strawford et al., 1999); and (5) pharmacologic blockade of T-specific receptors suppresses exercise-induced hypertrophy of skeletal muscle (Inoue et al., 1994).
CORTISOL Cortisol (C), a steroid hormone, is secreted from the adrenal cortex following stimulation from adrenocorticotrophic hormone (released by the anterior pituitary gland). The primary pathway for C secretion is through stimulation of the hypothalamus by the central nervous system as a result of hypoglycaemia, the flight or fight response, or exercise. Cortisol is considered a catabolic hormone to skeletal muscle tissue, and is released in response to low levels of glycogen; its primary role is to stimulate gluconeogenesis and glycogenolysis via glycogen, protein and lipid metabolism, and through its permissive actions on other hormones (e.g., catecholamines and glucagon). Although, if
secreted over a prolonged period, it is generally considered detrimental to muscle mass, in short bursts it can actually facilitate subsequent anabolism. In this regard, it acts as a repartitioning hormone allowing energy to be re-distributed to where it is needed (e.g. a contracting muscle). It may also predict performance, similar to T (Crewther & Christian, 2010), and more recently, much like T, the effect C has on behavioural characteristics has been explored.
Cortisol concentration levels Cortisol release response is similar to T and GH, whereby anaerobic metabolism acts as a potent stimulus (Ratamess et al., 2005). Therefore, despite chronically high levels of C reflecting adverse effects and progression towards overtraining, acute responses may be an essential part of the remodelling process, whereby the muscle must first be disrupted before it can adapt (Kraemer & Ratamess, 2005). It is, however, suggested that these acute training variables are varied to allow the adrenal gland to recover (secrete less cortisol) and prevent overtraining. Continued stress causes delayed recovery due to the over release of C and its negative effects exerted through gluconeogenesis and immune system depression (Kraemer et al., 2008). The rise in GH and C concentrations during resistance training may also contribute to the regulation of glucose and glycogen metabolism (Samilios et al., 2003). Therefore, in strengthendurance type protocols (low load, high repetitions), the low tension applied for an extended period of time may cause hormonal responses in response to the activation of the anaerobic metabolism and the need for restoration of energy substrates (Samilios et al., 2003). It should be noted, however, that although bodybuilding type programmes evoke concurrent adaptations in both hormones, the magnitude of GH (and T) is greater than C, which may compensate for the negative effects (Samilios et al., 2003). Circulating C levels reflect tissue remodelling and concurrent inflammatory responses (Kraemer et al., 1996). High levels of C (> 800 mmol/L) may signify an overtrained state (Fry et al., 1998), and have been highly correlated to serum creatine kinase concentration, which is a marker of muscle damage (Kraemer et al., 1993). In addition, the T:C ratio may provide a gross estimation (as both hormones have multiple functions across multiple tissue organs) of the anabolic/catabolic state of the body (Fry & Kraemer, 1997; Fry & Schilling, 2002). This has been positively related to performance (Alen et al., 1998), overreaching (Hakkinen et al., 1987) and overtraining (Stone et al., 1991). For example, McLellan et al. (2010) examined pre, during, and post-match neuromuscular and endocrine responses to competitive rugby league match play. Force–time data from the CMJ (including peak rate of force development, peak power and peak force) and saliva samples were collected to determine the T:C ratio and force output characteristics. Results revealed a return to normal T:C within 48 hours post-match, with neuromuscular function equally compromised for up to 48 hours after match play. These may indicate that a minimum period of 48 hours is required for neuroendocrine homeostasis post-competition. Finally, T and insulin can counter the catabolic effects of C by blocking the genetic element in the DNA for C (Kraemer et al., 2008). However, this can only be achieved if they are bound to a greater number of receptors than C. Thus, after a period of training and endocrine adaptation, the effects of C may become less dramatic due to disinhibition of C by T (Kraemer et al., 2008). Resistance training experience of ≥ 2 years has been shown to be accompanied by increases in the T:C ratio (Hakkinen et al., 1998), and may be indicative of enhanced strength and training tolerance (Fry & Schilling, 2002).
Cortisol, behaviour and its moderating effect on testosterone Cortisol may jointly work with T to moderate status-seeking behaviours (Cook & Crewther, 2014). This may be achieved via suppression of the hypothalamic-pituitary-gonadal-axis (and T secretion), inhibition of T actions on the target tissue and/or the down-regulation of the androgen receptors (Liening & Josephs, 2010). Similar to T, C responsiveness can vary in the presence of strangers or friends (Wagner et al., 2002). The acute neuroendocrine responses to social interactions have possible implications for modifying future performance and recovery, with transient changes in T and C levels linked to recovery from a competitive sport and/or subsequent match performance (Crewther & Cook, 2012; Cook & Crewther, 2012b). Therefore, controlling for situations that may challenge the stress tolerance of athletes, if not used purposefully, may hinder any sought-after training adaptations or performance gain. The reported associations between T and physical performance tend to be best demonstrated in elite-trained athletes (Crewther et al., 2011). It is possible that these results might be less about a superior physical ability and more about a superior ability for performing under stress. For example, untrained individuals typically exhibit a larger neuroendocrine stress response (e.g., C) than trained individuals when exercising at the same workloads (Hackney, 2006). Behavioural studies explain that C may be moderating the effect of T (Mehta & Josephs, 2010; Mehta & Prasad, 2015) such that relationships are mostly positive at low C levels and negative at high C levels (Mehta & Prasad, 2015). For example, C can influence T activity or release via the motivational circuitry, psychological processing and feedback inhibition (Mehta & Prasad, 2015), supporting findings that T is positively related to dominance or aggression outcomes in men, but only when C levels are low (Mehta & Josephs, 2010; Mehta & Prasad, 2015). These findings are applicable to sport and exercise, not only because muscle performance and dominance are linked (Gallup et al., 2007), but also because any exercise protocol deemed to be stressful may attenuate results. Currently only Crewther et al. (2016) have explored the moderating effect of C within this context. They examined the effect of C on the T relationship within handgrip strength; the men were assessed around a short bout of sprint cycling exercise (to create “stress”). The authors found that while T and C measures did not predict pre-test or resultant changes in handgrip strength scores, a significant hormonal interaction was identified, such that T predicted both strength outcomes when taking into account individual differences in pre-test C levels. The direction of their relationships, however, was in contrast from the aforementioned. Specifically, pre-test T and handgrip strength were negatively associated in men with high pre-test C levels, and T and handgrip strength changes were negatively related in men with low pre-test C levels. The authors suggest that being less stressed (i.e., low C) might ensure that other potentiating mechanisms (e.g., myosin phosphorylation, motor unit recruitment) are activated by exercise (Tillin & Bishop, 2009), with a small or negative T response possibly indicating better tissue uptake (Crewther et al., 2011) and/or metabolite conversion (Wood & Stanton, 2012). Certainly further investigations are required into this mechanism which partly supports why inconsistent relationships are seen in men with little or no training experience, and why physiological elevations in T are not always necessary for muscle growth (Morton et al., 2016).
CONCLUSION AND PRACTICAL APPLICATION For muscle hypertrophy, training programmes can utilise three sets of ten repetitions at or near 10RM
loads, with short rest periods of no longer than one minute. This appears to maximally release anabolic hormones with blood lactate concentration seen as a causative factor. However, gaining research based momentum is the likelihood that actually three sets to failure, with rep ranges of 8–25, are just as effective. This appears to be due to motor unit recruitment rather than changes in hormone concentrations and load. Finally, seven sets of three repetitions (to failure) have also shown similar increases in hypertrophy, but this approach induces superior increases in strength. From a sports perspective, therefore, this may be the best volume load strategy. Beyond hypertrophy, and pertinent to sports performance, is the effect that T demonstrates on the nervous system and behaviour. High levels appear to augment physical performance either directly or through motivational and perhaps risk taking means. The timing of training sessions (including for purposes of priming) and the effect of feedback, videos and “psyching up” interventions, in general, should therefore be explored to truly maximise both the training and competition performances. Finally, it is important to acknowledge that more individualisation is needed when interpreting endocrinology research; this may be of particular relevance to elite athletes and very strong athletes. For example, the T release across commonly prescribed resistance training protocols differed greatly among professional athletes, suggesting that strength gain may be further enhanced by individuals adopting a periodisation model that predominately focused on the protocol that maximised their T response. The periodic measurement of hormones could therefore provide a method to ensure that the periodisation of resistance training is optimised for each individual athlete, also noting that athletes may, in time, change in their hormonal response to each resistance training protocol. Also, it may be that it is the increased androgen receptor content of very strong athletes that dictates the use of T, and perhaps interventions aimed at increasing T concentrations can not be realised until athletes can, for example, squat almost double body weight. Finally, it may be that it is an athlete’s ability to tolerate stress, or perhaps not view a particular situation as stressful, that ultimately dictates the benefits that T has to performance – with or without a high androgen receptor content. The moderating effect of C may be such that high C levels ultimately override high concentrations of T. Again, environmental stimuli, athlete feedback and recovery strategies become central to this.
REFERENCES Aarts, H., & van Honk, J. (2009). Testosterone and unconscious positive priming increase human motivation separately. Neuro Report, 20, 1300–1303. Aleman, A., Bronk, E., Kessels, R., Koppeschaar, H., & Van Honk, J. (2004). A single administration of testosterone improves visuospatial ability in young women. Psychoneuroendocrinology, 29, 612–617. Alen, M., Pakarinen, A., Hakkinen, K., & Komi, P. (1998). Responses of serum androgenic-anabolic and catabolic hormones to prolonged strength training. Int. J. Sport. Med, 9, 229–233. Anawalt, B., & Merriam, G. (2001). Neuroendocrine aging in men: andropause and somatopause. Endocrin Metab Clin, 30, 647–669. Basualto-Alarcón, C., Jorquera, G., Altamirano, F., Jaimovich, E., & Estrada, M. (2013). Testosterone signals through mTOR and androgen receptor to induce muscle hypertrophy. Med Sci Sports Exerc, 45 (9), 1712–1720. Beaven, C., Cook, C., & Gill, N. (2008a). Significant strength gains observed in rugby players after specific resistance exercise protocols based on individual salivary testosterone responses. J Strength Cond Res, 22 (2), 419–425. Beaven, C., Gill, N., & Cook, C. (2008b). Salivary testosterone and cortisol responses to four resistance exercise protocols in professional rugby players. J Strength Cond Res, 22, 426–432. Beaven, C., Gill, N., Ingram, J., & Hopkins, W. (2011). Acute salivary hormone responses to complex exercise bouts. J Strength Cond Res, 25 (4), 1072–1078. Bernhardt, P., Dabbs, J., Fielden, J., & Lutter, C. (1998). Testosterone changes during vicarious experiences of winning and losing among fans at sporting events. Physiol. Behav, 65, 59–62. Bhasin, S., Storer, T., Berman, N., Callegari, N., Cleavenger, B., Phillips, J., et al. (1999). The effects of supraphysiologic doses of testosterone on muscle size and strength in normal men. N Engl J Med, 355, 1–7.
Bhasin, S., Storer, T., Berman, N., Yarasheski, K., Cleavenger, B., Phillips, J. L., et al. (1997). Testosterone replacement increases fatfree mass and muscle size in hypogonadal men. J Clin Endocrinol Metab, 82, 407. Bosco, C., Colli, R., Bonomi, R., Von Duvillard, S., & Viru, A. (2000). Monitoring strength training: neuromuscular and hormonal profile. Med. Sci. Sport. Exerc, 32, 202–208. Bosco, C., Tihanyi, J., & Viru, A. (1996a). Relationships between field fitness test and basal serum testosterone and cortisol level in soccer players. Clin Physiol, 16 (317), 22. Bosco, C., Tihanyi, J., Rivalta, L., Parlato, G., Tranquilli, C., Pulvirenti, G., Fonti, C. Viru, M., Viru, A. (1996b). Hormonal responses in strenuous jumping effort. Jpn. J. Physiol, 46, 93–98. Cardinale, M., & Stone, M. (2006). Is testosterone influencing explosive performance? J Strength Cond Res, 20, 103–107. Carney, D., & Cuddy, A. Y. (2010). Power posing: brief nonverbal displays affect neuroendocrine levels and risk tolerance. Psychol. Sci, 21, 1363–1368. Carré, J., & Putman, S. (2010). Watching a previous victory produces an increase in testosterone among elite hockey players. Psychoneuroendocrinology, 35, 475–479. Clarkson, P., & Tremblay, I. (1998). Exercise-induced muscle damage, repair and adaptation in humans. J. Appl. Physiol, 65, 1–6. Cook, C., & Beaven, C. (2013). Salivary testosterone is related to self-selected training load in elite female athletes. Physiology and Behavior, 8 (12), 116–117. Cook, C., & Crewther, B. (2012a). Changes in salivary testosterone concentrations and subsequent voluntary squat performance following the presentation of short video clips. Hormones and Behavior, 61, 17–22. Cook, C., & Crewther, B. (2012b). The effects of different pre-game motivational interventions on athlete free hormonal state and subsequent performance in professional rugby union matches. Physiology and Behavior, 106 (5), 638–688. Cook, C., & Crewther, B. (2014). The social environment during a post-match video presentation affects the hormonal responses and playing performance in professional male athletes. Physiology and Behavior, 130, 170–175. Cook, C., Kilduff, L., Crewther, B., Beaven, M., & West, D. (2013). Morning based strength training improves afternoon physical performance in rugby union players. Journal of Science and Medicine in Sport, 17, 317–321. Crewther, B., & Christian, C. (2010). Relationships between salivary testosterone and cortisol concentrations and training performance in Olympic weightlifters. The Journal of Sports Medicine and Physical Fitness, 50 (3), 371–375. Crewther, B., & Cook, C. (2012). Effects of different post-match recovery interventions on subsequent athlete hormonal state and game performance. Physiol Behav, 106, 471–475. Crewther, B., Lowe, T., Weatherby, R., & Gill, N. (2009a). Prior sprint cycling did not enhance training adaptation, but resting salivary hormones were related to workout power and strength. Eur J Appl Physiol, 105, 919–927. Crewther, B., Lowe, T., Weatherby, R., Gill, N., & Keogh, J. (2009b). Neuromuscular performance of elite rugby union players and relationships with salivary hormones. J Strength Cond Res, 23, 2046–2053. Crewther, B., Thomas, A., Stewart-Williams, S., Kilduff, L., & Cook, C. (2016). Is salivary cortisol moderating the relationship between salivary testosterone and hand-grip strength in healthy men? European Journal of Sport Science, 1391, 1–7. Crewther, B., Cook, C., Cardinale, M., Weatherby, R., & Lowe, T. (2011). Two emerging concepts for elite athletes: the short-term effects of testosterone and cortisol on the neuromuscular system and the dose-response training role of these endogenous hormones. Sports Medicine, 41 (2), 103–123. Crewther, B., Cook, C., Gaviglio, C., Kilduff, L., & Drawer, S. (2012). Baseline strength can influence the ability of salivary free testosterone to predict squat and sprinting performance. J Strength Cond Res, 26 (1), 261–268. Curl, C., Delbridge, L., Canny, B., & Wendt, I. (1989). Testosterone modulates cardiomyocyte Ca(2+) handling and contractile function. Physiol Rev, 58, 293–297. Czech, M. P. (2009). Signal transmissions by the insulin-like growth factors. Cell, 59, 235–238. DeSoto, C., Hitlan, R., Deol, R., & McAdams, D. (2009). Testosterone fluctuations in young men: the difference between interacting with like and not-like others. Evol Psychol, 8, 173–188. Ekstrand, L., Battaglini, C., & McMurray, R. (2013). Assessing explosive power production using the backward overhead shot throw and the effects of morning resistance exercise on afternoon performance. J Strength Cond Res, 27 (1), 101–106. Fahey, T., Rolph, R., Moungmee, P., Nagel, J., & Mortara, S. (1976). Serum testosterone, body composition and strength of young adults. Med. Sci. Sports, 8, 31–34. Fleck, S., & Kraemer, W. (2004). Designing Resistance Training Programs. Champaign, IL: Human Kinetics. Fry, A., & Kraemer, W. (1997). Resistance exercise overtraining and overreaching: neuroendocrine responses. Sport. Med, 23, 106– 129. Fry, A., & Schilling, B. (2002). Weightlifting training and hormonal responses in adolescent males: implications for program design. Strength Cond, 24, 7–12. Fry, A., Kraemer, W., & Ramsey, L. (1998). Pituitary-adrenal-gonadal responses to high-intensity resistance exercise overtraining. J. Appl. Phsiol., 85, 2352–2359. Gallup, A., White, D., & Gallup, G. (2007). Handgrip strength predicts sexual behavior, body morphology, and aggression in male college students. Evolution and Human Behavior, 28 (6), 423–429. Godfrey, R., Whyte, G., Buckley, J., & Quinlivan, R. (2009). The role of lactate in the exercise-induced human growth hormone
response: evidence from McArdle disease. British Journal of Sports Medicine, 43 (7), 521–525. Hackney, A. (2006). Stress and the neuroendocrine system: the role of exercise as a stressor and modifier of stress. Expert Review of Endocrinology and Metabolism, 1 (6), 783–792. Hakkinen, K., & Pakarinen, A. (1993). Acute hormonal responses to two different fatiguing heavy-resistance protocols in male athletes. J. Appl. Physiol, 74, 882–887. Hakkinen, K., Komi, P., Alen, M., & Kauhanen, H. (1987). Relationships between training volume, physical performance capacity, and serum hormone concentrations during prolonged training in elite weightlifters. Int. J. Sport. Med, 8, 61–65. Hakkinen, K., Pakarinen, A., Alen, M., & Komi, P. (1985). Serum hormones during prolonged training of neuromuscular performance. Eur. J. Appl. Physiol, 53, 287–293. Hakkinen, K., Pakarinen, A., Newton, R., & Kraemer, W. (1998). Acute hormone responses to heavy resistance lower and upper extremity exercise in young versus old men. Eur J. Appl. Physiol, 77, 312–319. Hansen, S., Kvorning, T., Kjaer, M., & Sjogaard, G. (2001). The effect of short-term strength training on human skeletal muscle: importance of physiologically elevated hormone levels. Scand J. Med. Sci. Sport, 11, 347–354. Henselmans, M., & Schoenfeld, B. (2014). The effect of inter-set rest intervals on resistance exercise-induced muscle hypertrophy. Sports Medicine, 44 (12), 1635–1643. Hermans, E. J., Ramsey, N. F., & van Honk, J. (2008). Exogenous testosterone enhances responsiveness to social threat in the neural circuitry of social aggression in humans. Biol Psychiatry, 63, 263–270. Inoue, K., Yamasaki, S., Fushiki, T., Okada, Y., & Sugimoto, E. (1994). Androgen receptor agonist suppresses exercise-induced hypertrophy of skeletal muscle. Eur J Appl Physiol, 69, 88–91. Kadi, F., Bonnerud, P., Eriksson, A., & Thornell, T. (2000). The expression of androgen receptors in human neck and limb muscles: effects of training and self-administration of androgenic steroids. Histochem. Cell Biol, 113, 25–29. Kraemer, W., & Ratamess, N. (2005). Hormonal responses and adaptations to resistance exercise and training. Sport Medicine, 34, 339–361. Kraemer, W., Clemson, A., Triplett, N., Bush, J., Newton, R., & Lynch, J. (1996). The effects of plasma cortisol evelauation on total and differential leukocyte counts in response to heavy resistance exercise. Eur. J. Appl. Physiol, 73, 93–97. Kraemer, W., Fleck, S., Dziados, J., Harman, E., Marchitelli, L., Gordon, S., et al. (1993). Changes in hormonal concentrations following different heavy resistance exercise protocols in women. J. Appl. Physiol, 75, 594–604. Kraemer, W., Fry, A., Warren, B., Stone, M., Fleck, S., Kearney, J., et al. (1992). Acute hormonal response in elite junior weightlifters. Int. J. Sport. Med. 13, 103–109. Kraemer, W., Gorden, S., Fleck, S., Marchitelli, L., Mello, R., Diziados, J., et al. (1991). Endogenous anabolic hormonal and growth factor responses to heavy resistance exercise in males and females. Int. J. Sport. Med, 12, 228–235. Kraemer, W., Marchitelli, L., McCurry, D., Mello, R., Dziados, J., Harman, E., et al. (1990). Hormonal and growth factor responses to heavy resistance exercise. J. Appl. Physiol, 69, 1442–1450. Kraemer, W., Vingren, J., & Spiering, B. (2008). Endocrine responses to resistance training. In T. Baechle, & R. Earle, In: Essentials of Strength Training and Conditioning (pp. 41–64). Champaign, IL: Human Kinetics. Lejune-Lenain, C., Van Cauter, E., Desir, D., Beyloss, M., & Franckson, J. (1987). Control of circadian and episodic variations of adrenal androgens secretion in man. J. Endocrinol. Invest, 10, 267–276. Liening, S., & Josephs, R. (2010). It is not just about testosterone: physiologicalmediators and moderators of testosterone’s behavioral effects. Soc Pers Psychol Compass, 4, 982–994. Lin, H., Wang, S., & Wang, R. (2001). Stimulatory effect of exercise on testeosterone production by rat Leydig cells. J. Cell. Biochem, 83, 14–154. Linnamo, V., Pakarinen, A., Komi, P., Kraemer, W., & Hakkinen, K. (2005). Acute hormonal responses to submaximal and maximal heavy resistance and explosive exercises in men and women. J. Strength Cond. Res, 19, 566–571. Lu, S., Lau, C., Tung, Y., Huang, S., Chen, Y., Shih, H., et al. (1997). Lactate and the effects of exercise on testosterone secretion: evidence for the involvement of a cAMP-mediated mechanism. Med. Sci. Sports Exerc, 29, 1048–1054. Mazur, A., & Booth, A. (1998). Testosterone and dominance in men. Behav Brain Sci, 21, 353–397. McLellan, C., Lovell, D., & Glass, C. (2010). Creatine kinase and endocrine responses of elite player pre, during, and post rugby league match play. J Strength Cond Res, 24 (11), 2908–2919. Mehta, P., & Josephs, R. (2010). Testosterone and cortisol jointly regulate dominance: evidence for a dual-hormone hypothesis. Hormones and Behavior, 58 (5), 898–906. Mehta, P., & Prasad, S. (2015). The dual-hormone hypothesis: a brief review and future research agenda. Current opinion in behavioral sciences, 3, 163–168. Morton, R., Oikawa, S., Wavell, C., Mazara, N., McGlory, C., Quadrilatero, J., et al. (2016). Neither load nor systemic hormones determine resistance training-mediated hypertrophy or strength gains in resistance-trained young men. J. Appl. Physiol, In press. Nagaya, N., & Herrera, A. (1995). Effects of testosterone on synaptic efficacy at neuromuscular junctions in asexual dimorphic muscle of male frogs. J. Physiol, 483, 141–153. Neave, N., & Wolfson, S. (2003). Testosterone, territoriality, and the ‘home advantage’. Physiol. Behav., 78, 269–275. Ramos, E., Frontera, W., Llopart, A., & Feliciano, D. (1998). Strength and hormonal levels in adolescents: gender related differences. Int
J Sports Med, 19, 526–531. Ratamess, N., Kraemer, W., Volek, J., Jeff, S., Maresh, C., Van Heest, J., et al. (2005). Effects of heavy resistance exercise volume on post-exercise androgen receptor content in resistance trained men. J Steroid Biomech. Molec. Biol, 93, 35–42. Ronay, R., & von Hippel, W. (2010). The presence of an attractive woman elevates testosterone and physical risk taking in young men. Soc Psychol Pers Sci, , 57–64. Samilios, I., Pilianidis, T., Karamouzis, M., & Tokmakids, S. (2003). Hormonal responses after various resistance exercise protocols. Med. Sci. Sports Exerc, 35, 644–654. Schoenfeld, B., Peterson, M., Ogborn, D., Contreras, B., & Sonmez, G. (2015). Effects of low- vs. high-load resistance training on muscle strength and hypertrophy in well-trained men. J Strength Cond Res, 29, 2954–2963. Schoenfeld, B., Ratamess, N., Peterson, M., Contreras, B. S., & Alvar, B. (2014). Effects of different volume-equated resistance training loading strategies on muscular adaptations in well-trained men. J Strength Cond Res, 28 (10), 2909–2918. Stoléru, S., & Ennaji, A. C. (1993). LH pulsatile secretion and testosterone blood levels are influenced by sexual arousal in human males. Psychoneuroendocrinology, 18, 205–218. Stone, M., Fleck, S., Triplett, N., & Kraemer, W. (1991). Physiological adaptations to resistance training exercise. Sport. Med, 11, 210– 231. Strawford, A., Barbieri, T., van Loan, M., Parks, E. C., Barton, N. N., Christiansen, M., et al. (1999). Resistance exercise and supraphysiologic androgen therapy in eugonadal men with HIV-related weight loss. JAMA, 281, 1282–1290. Teo, W., McGuigan, M., & Newton, M. (2011). The effects of circadian rhythmicity of salivary cortisol and testosterone on maximal isometric force, maximal dynamic force, and power output. J Strength Cond Res, 25 (6), 1538–1545. Tillin, N., & Bishop, D. (2009). Factors modulating post-activation potentiation and its effect on performance of subsequent explosive activities. Sports Medicine, 39 (2), 147–166. Viru, A., Viru, M., & Bosco, C. (2003). Hormones in short-term exercises: resistance and power exercises. Strength Cond. J, 24, 7–15. Volek, J., Kraemer, W., Bush, J., Incledon, T., & Boetes, M. (1997). Testosterone and cortisol in relationship to dietary nutrients and resistance exercise. J. Appl. Physiol, 82, 49–57. Wagner, J., Flinn, M., & England, B. (2002). Hormonal response to competition among male coalitions. Evol Hum Behav, 23, 437–442. West, D., & Phillips, S. (2012). Associations of exercise-induced hormone profiles and gains in strength and hypertrophy in a large cohort after weight training. Eur J Appl Physiol, 112, 2693–2702. West, D., Kujbida, G., Moore, D., Atherton, P., Burd, N., Padzik, J., et al. (2009). Resistance exercise-induced increases in putative anabolic hormones do not enhance muscle protein synthesis or intracellular signalling in young men. J Physiol, 587, 5239–5247. Wood, R., & Stanton, S. (2012). Testosterone and sport: current perspectives. Hormones and Behavior, 61 (1), 147–155. Zatsiorsky, V., & Kraemer, W. (2006). Science and Practice of Strength Training (2nd Edition). Champaign, IL: Human Kinetics.
CHAPTER 5
Training aerobic fitness Alex Bliss and Rob Harley
SECTION 1 – INTRODUCTION DEFINING AEROBIC FITNESS AND OTHER FREQUENTLY ENCOUNTERED TERMS The physiological determinants of successful endurance sport performance have been considered for many years. Nobel prize winner A.V. Hill described endurance exercise in athletics and measured the contribution to performance by aerobic energy production pathways in the early 1920s. The maximal oxygen uptake was described as V̇O2 max and has continued to be considered an important performance determinant to the present day (Basset, 2002). However, a common issue in sports and exercise science is that the term “aerobic” is used to describe exercise in terms of duration, more so than the primary metabolic pathway for the activity. An “aerobic” effort is often used to describe long duration exercise, with the reverse being true of “anaerobic” efforts (Chamari & Padulo, 2015). In truth, dichotomising exercise into purely “aerobic” or “anaerobic” effort is not an accurate method by which to explain the physiological processes that are occurring. For example, at the end of a rampbased V̇O2 max test (described below), a participant’s blood lactate level will typically be above 8mmol·L–1. Therefore, during this test of maximal oxygen uptake, a portion of the energy provided to achieve the exercise intensity required during the test has come from anaerobic energy pathways (anaerobic glycolysis). To ensure consistency, and to encourage coaches and sports scientists working in applied practice to provide a clear message to their athletes, defining some of the common terminology encountered should help to improve practice (Chamari & Padulo, 2015). Therefore, prior to describing methods or strategies to train aerobic fitness, it is perhaps pertinent to carefully define what aerobic fitness is, and moreover, what it is not.
Aerobic fitness Aerobic fitness, otherwise known as cardiovascular fitness, is a broad term, and encompasses the main physiological determinants of performance, as outlined below. In sport and exercise settings, measuring an athlete’s cardiovascular fitness is a key tool when establishing the credentials for upcoming performances and attempting to understand or explain previous performances. This is particularly so in sports where demonstrating superior aerobic fitness is a critical determinant in the performance and success of the athlete, most notably in sports performed above 80% of maximum heart rate and lasting longer than an hour.
Aerobic power Technically, V̇O2 max is a measure of the rate of oxygen consumption (absolute = L·min–1. Relative to body mass = mL·kg–1·min–1) over a period of time. Therefore, a calculation of the maximal power generated by aerobic/oxidative pathways can be performed during a maximal oxygen uptake test involving the collection of expired air for gas analysis purposes. Individuals with high maximal aerobic power exhibit increased concentrations of aerobic enzymes, mitochondrial size and density, myoglobin, and capillary density, allowing for enhanced oxygen extraction at the muscular level
(Tomlin & Wenger, 2001).
Aerobic capacity Capacity, by definition, concerns the maximum amount that can be contained or produced. With regards to aerobic capacity, this is linked to the production of energy for exercise utilising aerobic metabolism pathways (MacInnis & Gibala, 2017). At maximal levels, this is often termed maximal aerobic capacity/maximal oxygen uptake (V̇O2 max) or peak aerobic capacity/peak oxygen uptake (V̇O2 peak). However, aerobic capacity is used as a term to identify blood lactate or ventilatory markers, such as maximal lactate steady-state (MLSS) or rate of work that can be sustained for extended periods of time, with increases in V̇O2 max and other aerobic capacity markers resulting from endurance training (Tomlin & Wenger, 2001; Ekblom et al., 1968).
PHYSIOLOGICAL DETERMINANTS OF ENDURANCE PERFORMANCE Requirements from the various metabolic systems that produce energy within the human body during endurance running are dictated by the functions of race duration and race intensity (Boileau et al., 1982). Oxidative phosphorylation is the primary energy producing pathway in middle- and longdistance events. Therefore, athletes of national, international, or world-class level usually display well-developed aerobic fitness in a number of critical physiological performance parameters closely linked to oxygen uptake, namely: 1. 2. 3.
the maximal oxygen uptake or V̇O2 max, the amount of oxygen required to exercise at submaximal speeds (e.g., running economy), the amount of oxygen required to maintain low blood lactate levels (lactate threshold, turnpoint) (Jones, 2007).
Models of endurance physiology from the mid 1990s to the end of the 21st century display these determinants of performance (and others), and they are inexorably linked to “performance velocity” (Coyle, 1995), “maximal velocity in races” (Basset and Howley, 2000), or “race pace” (Jones, 2006).
MEASURING AEROBIC FITNESS V̇O2 max is the criterion measure of aerobic fitness and is considered to be the best single physiological variable for defining the function of the cardiovascular and respiratory systems (Cooke, 2009). However, the “gold standard” method for assessing aerobic fitness is to directly measure pulmonary gas exchange during exercise. This can be achieved using the Douglas bag method or by using breath-by-breath systems. For further information on these methods, readers are encouraged to read Jones (2007). The measurement of the key determinants of aerobic fitness (see Table 5.1) can be conducted using various protocols. For endurance athletes, assessments will usually comprise a laboratory assessment of two parts: a “submaximal” test, used to establish blood lactate and ventilatory responses such as
economy/efficiency, and a “maximal” test, used to establish the V̇O2 max. Both tests include multiple stages that will incrementally increase in speed or power output required. Stage duration for the submaximal element of the assessment is usually three or four minutes, which is enough time to allow for “steady state” conditions to be achieved. This phase of the test is used to determine economy, lactate threshold, lactate turnpoint, and heart rate zones that can be used when prescribing training. The “maximal” test will involve shorter stage durations, but begin at a higher speed or power output and be performed until volitional exhaustion. The precision of these measurements has been shown to be around 3% and can be extremely useful in monitoring the effectiveness of training interventions (Jones, 2007). TABLE 5.1 Operational definitions for frequently encountered terms. Adapted from Jones (2007) Construct
Acronym
Definition
Lactate threshold
LT
The first “breakpoint” or “observable rise” in blood lactate levels where levels
Lactate turnpoint
LTP
The second “sudden and sustained” increase in blood lactate levels during incremental exercise. Approximate to MLSS.
Maximal lactate steady state
MLSS
The highest work rate at which blood lactate is elevated above baseline but remains
Onset blood lactate accumulation
OBLA
Blood lactate reference value of 4mmol·L–1. The level at which, despite consistent work rate, the level of blood lactate will accumulate and continually rise over time.
Maximal oxygen uptake
V̇O2 max
The maximal rate of oxygen uptake. Identified by a plateau (or reduction) in V̇O2 despite increasing work rate.
Peak oxygen uptake
V̇O2 peak
The peak rate of oxygen uptake. Used in the absence of a plateau in oxygen uptake.
Velocity at V̇O2 max
vV̇O2 max
The velocity at V̇O2 max obtained by solving the regression equation describing measured V̇O2 at submaximal intensities and V̇O2 max.
Running economy
RE
The oxygen cost (or energy cost, see Shaw et al., 2015) of running at submaximal speeds or distances.
consistently exceed baseline (~1mmol·L–1)
stable. Blood lactate levels should not rise more than 1mmol·L–1 after 30 minutes exercise at the same work rate.
Athletes from other sports that require direct assessment of their aerobic fitness might undergo profiling as outlined above, although “sport-specific”, field-based estimates, such as the yo-yo intermittent recovery or multistage fitness test, for example, might be utilised. These assessments sacrifice the precision of measurement that can be obtained in a laboratory setting (although some laboratory equipment and techniques can be utilised in the field, e.g., portable gas/lactate analysers) in an effort to improve ecological validity. The number of sport-specific, field-based protocols for measuring or estimating aerobic fitness are too numerous to adequately capture here, but have been extensively outlined (Winter et al., 2007; Tanner & Gore, 2013).
SECTION 2 – TRAINING PREFACE This section is not designed to be prescriptive, but to outline evidence-based training methods and techniques that have been employed to bring about improved performance. In a recent editorial for the International Journal of Sports Physiology and Performance on the importance of “context”, it was stated that: “there is such diversity across sports that it is important to consider the context of the individual athlete and environment… with decisions being made based on the sport, athlete level, training history, and so on” (McGuigan, 2016). Strength and conditioning scientists should be careful when extrapolating findings of research studies, particularly when using untrained participants, when giving advice to athletes and their coaches (Midgley et al., 2007). Coaches and scientists reading this chapter must carefully consider the complexities, nuances, and idiosyncrasies of their athlete(s) and their performance environment when applying any of the knowledge presented herein. If responsible for training prescription, they are encouraged to base their decision making processes around both evidence-based practice (from peer-reviewed scholarly journals, textbooks, etc.) and practice-based evidence (correspondence with their athlete[s] and their coach[es] or other practitioner peers). Over time, the strength and conditioning scientist will develop their own philosophy to training, based on the above, and should, through reflective practice and continued professional development, improve and adapt this philosophy to ensure they are creating a training environment that encourages positive adaptations for their athlete(s).
EXERCISE INTENSITY ZONES Improving the physiological determinants of endurance performance requires careful manipulation of training volume (duration and frequency) and intensity. While volume is easily identifiable (by distance completed or time spent training), intensity of training effort is more difficult to classify. A common approach is to use blood lactate responses and corresponding heart rates to exercise at different intensities obtained through an incremental ramp test. Seiler (2010) identified a three intensity zone model (Figure 5.1) based around the lactate threshold and ventilatory thresholds, while DiMenna and Jones (2016) have proposed a similar four zone model utilising intensity landmarks identified from a blood lactate profile. Seiler’s (2010) zone 1 was classified as “low intensity training” (below lactate/ventilatory turnpoint 1 – also called lactate threshold) and referred to as “easy training” by DiMenna and Jones (2016). Zone 2 was classified as “threshold training”, which describes the intensities between lactate threshold and lactate turnpoint/maximal lactate steady state, and referred to as “steady training” by DiMenna and Jones (2016). Zone 3, referred to as “high intensity training” (intensities above the lactate turnpoint/maximal lactate steady state), was broken down into two further zones by DiMenna and Jones (2016). The first is termed “tempo training”, which describes continuous training performed at intensities just above the lactate turnpoint, usually performed for 20 to 30 minutes. The second is termed “interval training” which involves short, highintensity bursts of activity from durations of six minutes down to 30 seconds performed with increasing intensity and shorter interval duration.
FIGURE 5.1
A three intensity zone model based on the identification of ventilatory or blood lactate thresholds (Seiler, 2010).
LOW-INTENSITY/EASY TRAINING (BELOW LACTATE THRESHOLD) This intensity of training is usually implemented as easy recovery sessions and to allow athletes the opportunity to accumulate large training volumes, and usually performed as bouts of greater than 30 minutes. High training volumes and number of years’ running experience have been suggested to be important for improving running economy (Morgan et al., 1995; Midgley et al., 2007). While being appropriate for distance athletes, its applicability for athletes who partake in repeated sprint activity sports is limited. Endurance athletes have been shown to spend around 80% of their training time in this zone (Seiler & Tønneson, 2009).
THRESHOLD/STEADY TRAINING (BETWEEN LACTATE THRESHOLD AND LACTATE TURNPOINT) This type of training is especially important for endurance athletes as it is felt that the accumulation of mileage over a prolonged period of time helps improve running economy. Jones (2006) reported that Paula Radcliffe’s running economy improved by 15% between 1992 and 2003, the largest improvements occurring at speeds where an individual undertakes the largest proportion of their training. Training at intensities below the lactate turnpoint are usually performed over distances of 5 to 15 miles. If coaches have not got access to laboratory data in determining speeds and heart rates that correspond to these training zones, a simple coaching cue of “comfortably hard” could help athletes achieve the correct intensity (see Figure 5.2 and Table 5.2). In the authors’ experience, this has proved especially useful when working with games players during the off-season due to their unfamiliarity with this form of training. Exercising above the lactate turnpoint will feel more physically demanding, and the corresponding coaching cue of “hardly comfortable” should help athletes internalise how they should be feeling during tempo and interval type training.
TEMPO AND HIGH-INTENSITY TRAINING (ABOVE LACTATE TURNPOINT/MAXIMAL LACTATE STEADY STATE)
Typically, periodised training programmes of highly trained endurance athletes will involve more continuous, low-intensity, high-volume type training early in the season, with short duration, highintensity training undertaken as the athlete enters their pre-competition and competition training phases (Laursen & Jenkins, 2002). The rationale behind utilising this training method is that increases in volume alone do not appear sufficient to improve the key determinants of endurance performance, other than running economy (Laursen & Jenkins, 2002). Esfarjani & Laursen (2007) showed that moderately trained athletes, training at velocities equivalent to 100% and 130% of the velocity at V̇O2 max (vV̇O2 max) led to significant improvements in vV̇O2 max, V̇O2 max, and 3000m time trial performance. The findings in recreationally active and moderately trained athletes also appear to extend to well-trained populations. Enoksen et al. (2011) demonstrated that in 10 weeks, well-trained middle-distance runners improved vV̇O2 max velocity at lactate threshold, and running economy when adopting a high-intensity, low-volume training programme, as where their matched high-volume, lowintensity training group improved their running economy only. The runners were training six times per week, completing mean training mileages of > 90km per week, and had mean V̇O2 max values > 70 mL·kg–1·min–1. The high-intensity group completed 33% of training at a heart rate higher than 82% of maximum, with the low-intensity group completing 13% of total training volume in the same range. However, it appears that the dose-response relationship for high-intensity interval training needs to be carefully considered with highly-trained athletes. Menz et al. (2015) found that 11 sessions of high-intensity interval training that elicited heart rate responses between 88% and 94% of maximum heart rate did not significantly affect V̇O2 max when compared with a control group. The most likely explanation for the lack of meaningful change was the short duration of the programme (three weeks) resulting in a chronic stimulus that was insufficient to promote physiological adaptation. Although other studies employing the same exercise regimen (four repetitions of four minutes or “4x4”) had demonstrated significant improvements in V̇O2 max in four weeks (Helgerud et al. 2007), the participants had markedly lower starting maximal aerobic power values than those of the Menz et al. (2015) study (58.1 ± 4.5 mL·kg–1·min–1 vs. 63.7 ± 7.7 mL·kg–1·min–1, respectively). This led the authors to conclude that, in line with other work, lower V̇O2 max values at baseline and changes to V̇O2 max are significantly correlated (Menz et al., 2015). Coaches and scientists should, therefore, consider the dose-response relationship when introducing high-intensity interval training with athletes, and on the balance of evidence, expect highly-trained athletes to respond more slowly to this type of training intervention than recreationally active or moderately-trained athletes.
FIGURE 5.2
Example blood lactate response to incrementally increasing running speed with corresponding training zones and physiological markers.
TABLE 5.2 Table of training zones and cues that can be used by athletes and coaches to estimate their current zone. With laboratory assessment, training zones and corresponding intensities can be based on blood lactate levels and the corresponding heart rate at that level to obtain an objective, easily monitored method to allow for training in the desired zone Training zone
Typical blood lactate range
Coaching cue
Breathing reference
(mmol·L–1) Low intensity/easy
~1
Very easy or easy
Very easy or easy to talk while exercising
Threshold/steady
1 (or higher than baseline)–3
Comfortably hard
Ok to talk
Tempo
3–4
Hardly comfortable
Hard to talk
High intensity
>4
Hard to maximum effort
Cannot talk
STRENGTH TRAINING AS PART OF A STRATEGY FOR IMPROVING AEROBIC FITNESS Historically, endurance training methods aiming at improving markers of aerobic fitness and strength training have been viewed as separate entities, with the traditional view being that improvements in aerobic fitness result from endurance training only (Yamamoto et al., 2008). Combining strength training with endurance training aimed at improving aerobic fitness (often referred to as concurrent training, discussed in more detail in Chapter 7) has been suggested to impair muscular hypertrophy and has been termed “the interference effect” (Hickson, 1980). Endurance athletes are often reluctant to engage with strength training through concerns over muscular hypertrophy, consequential increases in body mass, and perceived questionable specificity of the exercises undertaken (Crane, 2011). Other concerns expressed include delayed onset muscle soreness and decreased capillary density and mitochondrial function (Yamamoto et al., 2008). The issue of compatibility appears well grounded in physiological and resistance training theory, as it is known that strength and endurance training operate at different ends of the physiological energy systems spectrum (Jones et al., 2013). At the molecular level, following a bout of strength training, there is a sustained increase in the activity of mammalian target of rapamycin (mTOR) which helps to up-regulate protein synthesis and critically underpins improvements in muscle strength and size (Baar, 2014), which are key goals of this type of exercise. Following endurance training, there is increased activation of the adenosine-monophosphate-activated protein kinase-peroxisome proliferator-activated receptor gamma coactivator (AMPK-PCG 1α) pathway which inhibits mTOR and therefore leads to diminishing protein accretion (de Souza et al., 2014). Despite the above concerns, research has shown that the combination of a variety of strength training modalities with endurance or aerobic fitness training can bring about performance benefits (Bonacci et al., 2011; Beattie et al., 2014; Beattie et al., 2017). Traditional, heavy-resistance strength training enhances performance through stimulating adaptations in muscle cross-sectional area, or hypertrophy (Paavolainen et al., 1999). Classically, strength training is introduced into an athlete’s programme to bring about changes in muscle crosssectional area (hypertrophy) and to improve force generation properties of the muscles targeted. There are three main types of strength training: maximal strength, explosive strength (strength-speed and speed-strength), and reactive strength, each of which can be identified by the velocity of movement (Siff, 2003). It has been suggested that in order to provide the most functionally relevant and performance enhancing training for endurance athletes, the resistance training element should focus around explosive and reactive type exercise. Developing high levels of explosive-strength (also referred to as rate of force development) and subsequently high external mechanical power are thought to be two of the most important characteristics for a wide range of sporting performance (Suchomel et al., 2016). Sports performers that particularly benefit from high levels of explosivestrength are those that are required to jump, rapidly change direction, or, as in the case with sprint and short-middle-distance athletes, are required to sprint maximally (Haff & Nimphius, 2012). Paavolainen et al. (1999) investigated the use of simultaneous endurance training and explosive strength training, consisting of various sprints, jumps, and low-load, high-movement velocity resistance training, including leg press and leg extension exercises, on 5km running performance. They demonstrated an improvement in 5km time trial in well-trained endurance athletes without changes in maximal oxygen uptake. However, before explosive-strength can be developed, the scientific literature suggests that high levels of muscular strength must form the foundation on which
high rates of force development and external mechanical power can be built (Suchomel et al., 2016), as well as to reduce injury risk (Beattie et al., 2014). In addition to the rationale above, well-trained elite athletes are unlikely to be able to significantly alter their maximal oxygen uptake (Jones, 1998). Therefore, strength training has been proposed as a method by which performance in endurance events can be improved, as such training demonstrated beneficial effects on running economy, muscular power, and neuromuscular function (Paavolainen et al., 1999, Beattie et al., 2014; Beattie et al., 2017).
THE ROLE OF AEROBIC FITNESS IN REPEATED SPRINT ACTIVITY SPORTS The duration and intensity of sporting activity will dictate the importance of aerobic energy contribution and the types of aerobic fitness required for optimal performance. It is commonly recognised that the longer the duration and the higher the intensity of sporting activity the more influence levels of aerobic fitness will have on performance. A number of team sports, along with racquet sports, involve high-intensity activity interspersed with moderate to low-intensity activity, and are commonly referred to as repeated sprint activity sports. Although the exact aerobic contribution for peak performance in these sports and, therefore, the aerobic fitness levels which are required for high level performance will vary, and are often a cause for discussion, the importance of aerobic fitness, and its constituent parts, to help maintain a high work rate is of paramount importance. The interplay and link between increases in aerobic fitness components and increases in performance has been clearly demonstrated in a variety of sports. Helgerud et al. (2001) reported that elite junior soccer players (mean age 18.1 years and over eight years’ playing experience) were able to improve their soccer performance as indicated by a 20% increase in distance covered in the match, 100% increase in the number of sprints performed, 24% increase in the number of involvements with the ball, as well as players being able to perform at a higher work intensity (85.6% of max heart rate rather than 82.7%) following two sessions of interval training per week, consisting of 4x4 minutes at 90–95% max heart rate with a 3 minute active recovery, in addition to their regular training for eight weeks. This improvement in performance was facilitated by improvements in all three components of aerobic fitness with V̇O2 max significantly increasing from 58.1 ± 4.5 mL·kg–1·min–1 to 64.3 ± 3.0 mL·kg–1·min–1 (P1.0 demonstrating that the use of the SSC results in a greater jump height, however, if the ratio is 6 was considered ‘poor’. There were considerable differences between male and female cadet scores, with 29% of males and 14% of females scoring in the excellent category and 23% of males and 36% of females scoring poorly (Padua et al. 2009). Poor scores were associated with higher levels of knee valgus, hip adduction, and increased hip/knee internal rotation. Perhaps more importantly, the LESS was able to distinguish between subjects who had previously suffered an ACL injury and those who had not, an outcome that has been noted again more recently (Bell et al. 2014). TABLE 13.4 Operational definitions for the modified LESS sheet (adapted from Padua et al. 2011) LESS criteria
Operational definition
Rater view
Stance width
Abnormally wide or narrow stance during landing, they receive an error (+1)
Front
Foot-rotation position
Moderate amount of external rotation or internal rotation, they receive an error (+1)
Front
Initial foot-contact symmetry
If one foot lands before the other or there is alternating heel-totoe/toe-to-heel landing mechanics, they receive an error (+1)
Front
Knee valgus
Small amount of knee valgus (+1) Large amount of knee valgus (+2)
Front
Lateral trunk flexion
If trunk is not perfectly vertical in frontal plane, they receive an error (+1)
Front
Initial landing of feet
If subject lands heel-to-toe or flat-footed, they receive an error (+1)
Side
Amount of knee flexion
Small amount of knee flexion displacement (+1) Average amount of knee flexion displacement (+2)
Side
Amount of trunk flexion
Small amount of trunk flexion displacement (+1) Average amount of trunk flexion displacement (+2)
Side
Total joint displacement in sagittal plane
Large displacement of trunk & knees = ‘soft’ (0) Average displacement of trunk & knees = ‘average’ (+1) Small displacement of trunk & knees = ‘stiff’ (+2)
Side
Overall impression
Soft landing with no frontal plane motion at the knee = ‘excellent’ N/A (0) Stiff landing with large frontal plane motion at the knee = ‘poor’ (+2) All other criteria rates ‘average’ (+1)
Additional normative values for the LESS have been reported elsewhere in the research (Padua et al. 2012; Smith et al. 2012). Smith et al. (2012) reported mean LESS scores of 4.42–5.53 in healthy high school and college athletes versus 4.70–5.91 in high school and college athletes who had previous ACL injuries. Padua et al. (2012) undertook two ACL injury prevention programs on youth soccer players consisting of flexibility, balance, strength, plyometrics, and agility training for either a short (three months; n = 33) or long (nine months; n = 51) intervention period. Furthermore, a ‘retention’ LESS test was undertaken three months post-training to determine the effectiveness of each intervention. Pre-intervention LESS scores were 5.17 and 5.70 for the three- and nine-month groups, respectively. Post-intervention LESS scores improved to 3.39 and 4.07, demonstrating how motor control in landing mechanics improved from both interventions. However, the three-month group portrayed a mean retention score of 4.69 whereas the nine-month intervention group’s mean score was reported to be 4.20 (Padua et al. 2012). The authors deduced that three months may not be a long enough period to retain significant improvements in landing mechanics for high school and college athletes. Although speculative, it is logical to assume that athletes with a lower training age (such as high school athletes) will require longer for desired movement competency to be truly engrained. TABLE 13.5 The Landing Error Scoring System (LESS) score sheet for the modified version of the LESS (adapted from Padua et al. 2011) Observing from the front
Observing from the side
1. Stance width ~ Normal (0) ~ Wide (1) ~ Narrow (1)
6. Initial landing of feet ~ Toe-to-heel (0) ~ Heel-to-toe (1) ~ Flat feet (1)
2. Maximum foot rotation position ~ Normal (0) ~ Moderately externally rotated (1) ~ Slightly internally rotated (1)
7. Amount of knee flexion displacement ~ Large (0) ~ Average (1) ~ Small (2)
3. Initial foot contact ~ Symmetric (0) ~ Not symmetric (1)
8. Amount of trunk flexion displacement ~ Large (0) ~ Average (1) ~ Small (2)
4. Maximum knee valgus angle ~ None (0) ~ Small (1) ~ Large (2)
9. Total joint displacement (sagittal plane) ~ Soft (0) ~ Average (1) ~ Stiff (2)
5. Trunk lateral flexion ~ None (0) ~ Small to moderate (1)
10. Overall impression ~ Excellent (0) ~ Average (1) ~ Poor (2)
TOTAL SCORE =
In light of the evidence, the LESS would appear to be a reliable method for assessing landing mechanics, and has been shown to differentiate between subjects who have and have not suffered ACL trauma. Normative scores for this assessment would appear to fall within a range of ~4–6, with a key emphasis on trying to reduce this figure should it be continually used as part of a screening battery. Despite the information portrayed in favour of the LESS, results are subjective, which
although favourable to practitioners in the field, is likely to exhibit error with unfamiliar raters. Similar to the single leg squat, quantifying objective measures such as knee valgus or FPPA could be considered to enhance this screen, especially as video analysis is already a pre-requisite for test requirements and has been used across comparable landing tasks (Comfort et al. 2016) such as the drop jump. Finally, the LESS grades mechanics from only a single landing, and a test that interprets movement quality during repeated jumping actions may be able to identify landing dysfunctions that the LESS cannot.
TUCK JUMP ASSESSMENT The tuck jump assessment (TJA) requires subjects to perform tuck jumps on the spot repeatedly for ten seconds (Myer et al. 2011). This repeated nature may allow coaches to observe flaws in landing mechanics during a higher intensity plyometric exercise when compared to the LESS (Myer et al. 2011; Bishop et al. 2015). In addition, although the test only occurs over a ten-second timeframe, the repeated nature may induce some level of fatigue, a concept that is unlikely to play a part in other high-velocity screens. As per the LESS, a grading criterion was created by Myer et al. (2011) and can be viewed in Table 13.6. One of the first priorities when using any testing protocol is to assess its reliability in order to understand whether it can be repeatedly used (Bishop et al. 2015) and can detect true changes (Turner et al. 2015). Reliability of the TJA has been researched by Herrington et al. (2013) and Read et al. (2015). Herrington et al. (2013) used two raters to independently grade ten adult subjects and showed that the average agreement was 93%, with 100% agreement across five of the individual criteria. Read et al. (2015) screened 25 pre- and 25 post-peak height velocity elite youth soccer players with each player’s score graded retrospectively across two different sessions. The TJA was deemed highly reliable (ICC = 0.88) but when each criterion was analysed individually, knee valgus was the only one that reached a substantial agreement between testing sessions across both groups (Read et al. 2015). These results indicate that although the TJA may be a reliable measure for screening landing mechanics, caution should be taken when interpreting the sum score. TABLE 13.6 Grading criteria for the tuck jump assessment (adapted from Myer et al. 2011) Tuck jump assessment
Pre Mid Post
Knee & thigh motion 1. Lower extremity valgus at landing
_______________________
2. Thighs do not reach parallel (peak of jump)
_______________________
3. Thighs not equal side-to-side (during flight)
_______________________
Foot position during landing 4. Foot placement not shoulder-width apart
_______________________
5. Foot placement not parallel (front to back)
_______________________
6. Foot contact timing not equal
_______________________
7. Excessive landing contact noise
_______________________
Plyometric technique
Comments
8. Pause between jumps
_______________________
9. Technique declines prior to ten seconds
_______________________
10. Does not land in same foot-print (excessive in-flight motion)
_______________________
Total score
This is further supported by Lininger et al. (2015) who undertook an exploratory factor analysis of the TJA on college athletes. Previous literature from Myer et al. (2011) identified five risk factors that each of the ten grading criterion might fall into: ligament dominance, quadriceps dominance, leg dominance, trunk dominance, and technique perfection. Lininger’s analysis investigated the internal structure of the TJA via a psychometric examination, and results indicated that fatigue, distal landing pattern, and proximal control accounted for 46% of the variance. With nearly half the variance accounted for by three factors not outlined by Myer’s original suggestions, the authors suggested that the use of a sum score at the end the assessment may be questionable. Finally, Klugman et al. (2011) examined whether an in-season ten-week plyometric program improved TJA scores in 49 female high school soccer athletes. Subjects were split into intervention (n = 15) and control (n = 34) groups, but it was not specified how many sessions a week the intervention group performed; merely that they attended 95% of total training sessions. The intervention group showed a slight improvement in TJA scores (pre = 5.4, post = 4.9). However, the control group who received no additional training other than their regular soccer practices also made comparable improvements (pre = 5.8, post = 5.0) (Klugman et al. 2011). It was suggested that there may be a dose-response relationship from this type of training and that ten weeks may not have been enough to depict significant improvements in tuck jump performance. However, without knowing more specific details of the number of sessions undertaken, it is impossible to draw objective evaluations. In conclusion, the evidence from Herrington et al. (2013) and Read et al. (2015) would suggest that the TJA is a reliable screening method; however, using the sum score may not provide as much value to the coach as was perhaps first intended. Lack of consistency between which grading criteria repeatedly present themselves and the suggested modifiable risk factors would suggest that further research is almost certainly warranted with this screen. Furthermore, Myer et al. (2008) highlight the importance of an athlete’s neuromuscular control and suggested that the TJA has the capacity to repeatedly monitor this. Whilst this idea cannot be argued with, the practicalities of who to implement this with must be considered. Notable discrepancies in landing mechanics have been noted in the LESS from just a single landing, yet the repeated nature of the TJA will make this test a considerable progression. It is the advice of the author that coaches carefully consider whether an athlete is ready for such an advanced screening method. Perhaps the TJA would best be utilised as a progression from the LESS, with coaches incorporating it once all compensations have been rectified from a single landing. So far, the high-velocity screens discussed have both been bilateral in nature. Jones et al. (2014) suggested that injuries occur in a multitude of ways such as cutting and side-stepping, both of which occur in a unilateral environment. With this in mind, it is suggested that a high-velocity unilateral screen will also provide practitioners with some useful information.
SINGLE LEG HOP
Hop tests have been the subject of numerous research studies in the rehabilitation setting (Barber et al. 1990; Noyes et al. 1991; Ross et al. 2002; Reid et al. 2007; Munro and Herrington, 2011; Rohman et al. 2015), with a particular emphasis on their ability to differentiate performance between those who have and have not had ACL trauma and provide quantifiable data pertaining to return to activity post-ACL injury. Unlike many of the aforementioned screening methods, hop tests would not appear to have a specific grading criterion; moreover, their use appears to have been associated with asymmetry scores between limbs. These differences are often used to calculate a Limb Symmetry Index (LSI) score (see Equation 13.1), which acts as a percentage of symmetry between limbs on the associated test (Barber et al. 1990; Garrison et al. 2015). Equation 13.1 Limb Symmetry Index (%) = (Involved limb ÷ Uninvolved limb) × 100 The single leg hop (SLH) is performed for maximal distance achieved on one limb and requires no expensive equipment, thus, it can be used by coaches at all levels in the industry. The simplicity associated with the test is undoubtedly a reason as to its common inclusion in a research setting. Rohman et al. (2015) monitored changes in LSI scores for ten functional tests (including the SLH) in 122 subjects during the ACL rehabilitation process. The authors described how it was deemed necessary for subjects to demonstrate 90% symmetry between limbs on all tests to be considered ‘rehabilitated’. The SLH was first conducted 158 days post-surgery and demonstrated LSI scores of 78.2%, with the 90% threshold being reached 81 days later (Rohman et al. 2015). Although no specific details of the rehabilitation process were provided, it is useful to note that subjects reached the required symmetry scores eight months post-surgery. However, this 90% threshold has not always been suggested as the benchmark for symmetry between limbs. Earlier research from Barber et al. (1990) undertook a quantitative comparison of healthy subjects (n = 93) and those showing positive ACL symptoms (but who had not had surgery) (n = 35). Mean asymmetry scores never went higher than 5% in the healthy subjects, whereas the ACL group showed significantly greater (p = 0.001) asymmetries of 18% between limbs. Interestingly, ~92% of the healthy population reported LSI scores ≥ 85%, which led authors to suggest that this was an acceptable asymmetry threshold for healthy subjects. This has been further supported by Noyes et al. (1991) who also investigated lower body asymmetries determined by hop tests post-ACL injuries. Sixty-seven patients (male = 40; female = 27) performed the SLH, the triple hop for distance, crossover hop for distance, and 6m timed hop as methods for determining asymmetry levels. With abnormal LSI scores considered to be below 85%, the SLH showed 52% of subjects demonstrated greater imbalances than the suggested threshold and 49% showed greater asymmetries during the timed hop also (Noyes et al. 1991). It was concluded that hop tests offer a simple method for determining lower limb functional limitations and should be used in conjunction with other tests to complete the screening picture. Finally, further evidence is offered by Grindem et al. (2011) who used the SLH (and the triple hop, crossover hop, and 6m timed hop) as predictors of function in 91 subjects with an ACL injury. One year after diagnosis, the SLH was the only test able to detect asymmetries > 15% with a mean LSI of 83.6% in the ACL group (Grindem et al. 2011). Consequently, this led the authors to suggest that practitioners should use the SLH specifically as an assessment for lower limb function when returning from knee injury. In conclusion, it would appear from the literature that the SLH is a viable method for determining
inter-limb asymmetries, particularly for those who may be returning from injury. Despite its efficacy for injured populations, it is still suggested that the SLH is used for non-injured and athletic populations as a simple and effective screen for monitoring inter-limb differences. Considering a grading criterion does not currently exist for this test, it is prudent to use the LSI as a measure of determining such differences during a unilateral, high-velocity screen, and thus providing coaches with a tangible outcome to inform their practice. Should kinematic information wish to be investigated for this screen, then video analysis is required and, once again, objective information pertaining to knee valgus and FPPA could be considered if resources allow. If video analysis is used without accompanying objective measures, practitioners should consider focusing on knee/hip alignment and torso compensations in order to determine successful landing technique. Although different tests, the associated compensations often seen during the SLS test (Figures 13.11–13.15) may provide a useful starting point when subjectively interpreting movement competency during this screen.
PUTTING A SCREENING PACKAGE TOGETHER It is clear from the aforementioned evidence that the popular methods of assessing movement (overhead squat, FMS) require further support if coaches are to fully understand an athlete’s movement profile. Therefore, high-velocity screens and methods for determining asymmetries are likely useful methods that will show movement information that the former cannot account for. However, it must be acknowledged that not all coaches will have access to the equipment needed to optimise the reliability of some of the testing procedures. With this in mind, it would be useful for coaches to have alternative options for screening movement so that some useful information can be obtained from the process. It should be understood, however, that if the most reliable methods cannot be adhered to (such as using force plates and/or motion analysis), then some degree of error will likely accompany a coach’s interpretation of the results. Whilst this is far from perfect, it is also most likely unavoidable and, provided this is accepted by the coach, the margin for error will most likely reduce with continued practice. Therefore, ‘gold’, ‘silver’, and ‘bronze’ packages have been suggested when screening movement (see Table 13.7) and methods can be chosen to suit each practitioner’s situation. It is important to recognise that the screens themselves do not change between packages, rather the methods of analysis. The screens have been selected based off the aforementioned information presented in this chapter. In addition, it is the suggestion of the author that bilateral and unilateral screens under both low- and high-velocity conditions may help to provide coaches with a more complete picture of movement quality than any one screen alone. However, practitioners are encouraged to remember that, as always, any system requires flexibility, and if a given test is not deemed appropriate for the population in question, then alternatives may be more appropriate. TABLE 13.7 Proposed gold, silver, and bronze screening packages Gold Overhead squat
Silver
Conducted on twin force plates Recorded using smart phone to quantify vGRF video analysis (e.g.: Coach’s Eye) 3-D motion analysis used to quantify kinematic information Assessed retrospectively
Bronze Assessed in real-time
Single leg squat
3-D motion analysis used to quantify kinematic information EMG used to determine lower limb muscle activation
Recorded using smart phone video analysis (e.g.: Coach’s Eye)
Assessed in real-time
Assessed retrospectively
LESS
Conducted on twin force plates Recorded using smart phone to quantify landing forces video analysis (e.g.: Coach’s Eye) 3-D motion analysis used to quantify kinematic information Assessed retrospectively
Assessed in real-time
Single leg hop
Conducted on a force plate to quantify landing forces
Assessed in real-time
3-D motion analysis used to quantify kinematic information
Recorded using smart phone video analysis (e.g.: Coach’s Eye) Assessed retrospectively
Notes: LESS = Landing Error Scoring System, vGRF = vertical ground reaction force, EMG = electromyography
Naturally, the most accurate information from screening an athlete’s movement will come from the gold package, due to the higher reliability associated with the accompanying data analysis. Whilst these procedures may be optimal, they are perhaps limited to those at the highest level of elite sport who either have the equipment themselves or the finances to align themselves to an institution that does. Even then, the time needed to set up EMG and motion analysis equipment, as an example, not to mention the time required to assess the screens afterwards, may not make the gold package the most practically viable in the field. For the silver package, the screens are still graded retrospectively, and thus the time needed post-procedures is still a requirement. However, due to recording from devices such as tablets or the coach’s own recording equipment, procedures will take substantially less time to complete. This in itself holds the advantage of reducing the time the athlete is required to be there for testing, and thus any motivational issues affected by duration are likely to be less of a factor. Finally, with smart phones and tablets being so readily accessible to individuals these days, there is an argument to say that no coach should subject their screening methods to the ‘error of real-time’ and thus the bronze package. However, it still may have its place in the field. The margin for error when grading an athlete’s movement is likely to be less as coaches become more established at using them. Therefore, if large squads are being assessed across any of the suggested screens and the pressure of
providing an immediate report (despite its potential inaccuracies) is at the forefront of a coach’s agenda, then real-time grading may be the only option. Therefore, it is suggested that coaches grade each screen in real-time and retrospectively (to begin with) in an attempt to determine real-time accuracy. Once an acceptable level of agreement between the two methods is achieved, it may then be plausible to rely on the bronze package when time-efficient screening strategies are required.
CONCLUSION Movement screening has been a vogue topic in recent years, with many debating its usefulness and applicability in the field. The lack of association between a range of movement-based tests (FMS) and performance may suggest that time could be better spent on other screens. However, an impression of movement quality is still almost certainly required, and as such, an assessment that challenges the major areas in the kinetic chain should provide this, justifying the overhead squat’s position in a screening battery. As previously mentioned, the question of whether or not movement mechanics alter under load and/or speed must be considered. The LESS allows for both, and has the advantage of differentiating between subjects who have and have not experienced previous ACL trauma. Noting that many sporting actions occur unilaterally and are governed by a finite period of time, it makes sense to incorporate low- and high-velocity unilateral testing procedures to a screening battery. Consequently, the SLS and SLH may allow for these principles to be accounted for. Finally, it is always suggested that coaches should use whatever testing procedures best fits their practice. As such, a combination of bilateral and unilateral, low and high velocity, and using expensive equipment or real-time analysis should allow for the majority of coaches to gauge some useful information from their screening methods, regardless of the tests chosen.
REFERENCES Atkins, S.J., Hesketh, C., and Sinclair, J.K. (2013). The presence of bilateral imbalance of the lower limbs in elite youth soccer players of different ages. Journal of Strength and Conditioning Research, 30: 1007–1013. Banskota, B., Lewis, J., Hossain, M., Irvine, A., and Jones, M.W. (2008). Estimation of the accuracy of joint mobility assessment in a group of health professionals. European Journal of Orthopaedic Surgery & Traumatology, 18: 287–289. Barber, S.D., Noyes, F.R., Mangine, R.E., McCloskey, J.W., and Hartman, W. (1990). Quantitative assessment of functional limitations in normal and anterior cruciate ligament-deficient knees. Clinical Orthopaedics and Related Research, 255: 204–214. Beardsley, C. and Contreras, B. (2014). The Functional Movement Screen: A review. Strength and Conditioning Journal, 36: 72–80. Bell, D.R., Smith, M.D., Pennuto, A.P., Stiffler, M.R., and Olsen, M.E. (2014). Jump-landing mechanics after anterior cruciate ligament reconstruction: A landing error scoring system study. Journal of Athletic Training, 49: 435–441. Bell, D.R., Vesci, B.J., DiStefano, L.J., Guskiewicz, K.M., Hirth, C.J., and Padua, D.A. (2012). Muscle activity and flexibility in individuals with medial knee displacement during the overhead squat. Athletic Training and Sports Health Care, 4: 117–125. Beutler, A.I., Cooper, L.W., Kirkendall, D.T., and Garrett, W.E. (2002). Electromyographic analysis of single-leg closed chain exercises: Implications for rehabilitation after anterior cruciate ligament reconstruction. Journal of Athletic Training, 37: 13–18. Bishop, C., Edwards, M., and Turner, A. (2016). Screening movement dysfunctions using the overhead squat. Professional Strength & Conditioning Journal, 42: 22–30. Bishop, C., Read, P., Walker, S., and Turner, A. (2015). Assessing movement using a variety of screening tests. Professional Strength & Conditioning Journal, 37: 17–26. Boudreau, S.N., Dwyer, M.K., Mattacola, C.G., Lattermann, C., Uhl, T.L., and McKeon, J.M. (2009). Hip muscle activation during the lunge, single-leg squat and step-up-and-over exercises. Journal of Sport Rehabilitation, 18: 91–103. Butler, R.J., Contreras, M., Burton, L.C., Plisky, P.J., Goode, A., and Kiesel, K. (2011). Modifiable risk factors predict injuries in firefighters during training academies. Work: A Journal of Prevention, Assessment and Rehabilitation, 46: 11–17. Butler, R.J., Plisky, P.J., Southers, C., Scoma, C., and Kiesel, K.B. (2010). Biomechanical analysis of the different classifications of the Functional Movement Screen deep squat test. Sports Biomechanics, 9: 270–279.
Chorba, R.S., Chorba, D.J., Bouillon, L.E., Overmyer, C.A., and Landis, J.A. (2010). Use of a Functional Movement Screening tool to determine injury risk in female collegiate athletes. North American Journal of Sports Physical Therapy, 5: 47–54. Clark, M. and Lucett, S. (2010). NASM Essentials of Corrective Exercise Training. Lippincott Williams & Wilkins, Third Edition. Clark, M.A., Lucett, S.C., and Sutton, B.G. (2012). NASM Essentials of Personal Fitness Training. Lippincott Williams & Wilkins, Fourth Edition. Clifton, D.R., Grooms, D.R., and Onate, J.A. (2015). Overhead deep squat performance predicts Functional Movement Screen™ score. International Journal of Sports Physical Therapy, 10: 622–627. Comfort, P., Colclough, A., and Herrington, L. (2016). A comparison of frontal plane projection angle across landing tasks in female gymnasts. International Journal of Athletic Therapy and Training, 21: 42–47. Cook, G. (2004). Athletic Body in Balance – Optimal Movement Skills and Conditioning for Performance. Champaign, IL: Human Kinetics. Cook, G., Burton, L., Kiesel, K., Rose, G., and Bryant, M. F. (2010). Movement: Functional Movement Systems: Screening, Assessment, Corrective Strategies. Lotus Publishing. DiStefano, L.J., Blackburn, J.T., Marshall, S.W., and Padua, D.A. (2009). Gluteal muscle activation during common therapeutic exercises. Journal of Orthopaedic and Sports Physical Therapy, 39: 532–540. Fox, D., O’Malley, E., and Blake, C. (2013). Normative data for the Functional Movement Screen™ in male Gaelic field sports. Physical Therapy in Sport, 27: 458–462. Frost, D.M., Beach, T.A.C., Callaghan, J.P., and McGill, S. M. (2012). Using the Functional Movement Screen™ to evaluate the effectiveness of training. Journal of Strength and Conditioning Research, 26: 1620–1630. Frost, D.M., Beach, T.A.C., Callaghan, J.P., and McGill, S. M. (2014). FMS™ scores change with performers’ knowledge of the grading criteria – Are general whole body movement screens capturing ‘dysfunction’? Journal of Strength and Conditioning Research, Published ahead of print. Garrison, J.C., Bothwell, J.M., Wolf, G., Aryal, S., and Thigpen, C.A. (2015). Y Balance Test™ anterior reach symmetry at three months is related to single leg functional performance at time of return to sports following anterior cruciate ligament reconstruction. International Journal of Sports Physical Therapy, 10: 602–611. Grindem, H., Logerstedt, D., Eitzen, I., Moksnes, H., Axe, M.J., Snyder-Mackler, L., Engebretsen, L., and Risberg, M.A. (2011). Singlelegged hop tests as predictors of self-reported knee function in nonoperatively treated individuals with anterior cruciate ligament injury. American Journal of Sports Medicine, 39: 2347–2354. Herrington, L. (2014). Knee valgus angle during single leg squat and landing in patellofemoral pain patients and controls. The Knee, 21: 514–517. Herrington, L., Myer, G.D., and Munro, A. (2013). Intra and inter-tester reliability of the tuck jump assessment. Physical Therapy in Sport, 14: 152–155. Horn, R.R., Williams, A.M., and Scott, M.A. (2010). Learning from demonstrations: The role of visual search during observational learning from video and point-light models. Journal of Sports Sciences, 20: 253–269. Howe, L.P. and Blagrove, R.C. (2015). Shoulder function during overhead lifting tasks: Implications for screening athletes. Strength and Conditioning Journal, 37: 84–96. Jones, P.A., Herrington, L.C., Munro, A.G., and Graham-Smith, P. (2014). Is there a relationship between landing, cutting and pivoting tasks in terms of the characteristics of dynamic knee valgus. American Journal of Sports Medicine, 42: 2095–2102. Kazman, J.B., Galecki, J.M., Lisman, P., Deuster, P.A., and O’Connor, F. G. (2014). Factor structure of the Functional Movement Screen in marine officer candidates. Journal of Strength and Conditioning Research, 28: 672–678. Klugman, M.F., Brent, J.L., Myer, G.D., Ford, K.R., and Hewett, T. E. (2011). Does an in-season only neuromuscular training protocol reduce deficits quantified by the tuck jump assessment? Clinical Sports Medicine, 30(4): 825–840. Levinger, P., Gilleard, W., and Coleman, C. (2007). Femoral medial deviation angle during a one-leg squat test in individuals with patellofemoral pain syndrome. Physical Therapy in Sport, 8: 163–168. Li, Y., Wang, X., Chen, X., and Dai, B. (2015). Exploratory factor analysis of the functional movement screen in elite athletes. Journal of Sports Sciences, 33: 1166–1172. Lininger, M.R., Smith, C.A., Chimera, N.J., Hoog, P., and Warren, M. (2015). The tuck jump assessment: An exploratory factor analysis in a college age population. Journal of Strength & Conditioning Research, Published ahead of print. Lloyd, R.S., Oliver, J.L., Faigenbaum, A.D., Howard, R., De Ste Croix, M.B.A., Williams, C.A., Best, T.M., Alvar, B.A., Micheli, L.J., Thomas, D.P., Hatfield, D.L., Cronin, J.B., and Myer, G.D. (2015). Long-term athletic development – Part 1: A pathway for all youth. Journal of Strength and Conditioning Research, 29: 1439–1450. Macadam, P., Cronin, J., and Contreras, B. (2015). An examination of the gluteal muscle activity associated with dynamic hip abduction and hip external rotation exercise: A systematic review. International Journal of Sports Physical Therapy, 10: 573–591. Macrum, E., Bell, D., Boling, M., Lewek, M., and Padua, D. (2012). Effects of limiting ankle-dorsiflexion range of motion on lower extremity kinematics and muscle-activation patterns during a squat. Journal of Sport Rehabilitation, 21: 144–150. Mauntel, T.C., Post, E.G., Padua, D.A., and Bell, D.R. (2015). Sex differences during an overhead squat assessment. Journal of Applied Biomechanics, 31: 244–249. Munro, A.G., and Herrington, L.C. (2011). Between-session reliability of four hop tests and the agility t-test. Journal of Strength and
Conditioning Research, 25: 1470–1477. Munro, A., Herrington, L., and Carolan, M. (2012). Reliability of 2-Dimensional video assessment of frontal-plane dynamic knee valgus during common athletic screening tasks. Journal of Sport Rehabilitation, 21: 7–11. Myer, G.D., Brent, J.L., Ford, K.R., and Hewett, T.E. (2011). Real-time assessment and neuromuscular training feedback techniques to prevent anterior cruciate ligament injury in female athletes. Strength and Conditioning Journal, 33: 21–35. Myer, G.D., Kushner, A.M., Brent, J.L., Schoenfeld, B.J., Hugentobler, J., Lloyd, R.S., Vermeil, A., Chu, D.A., Harbin, J., and McGill, S.M. (2014). The back squat: A proposed assessment of functional deficits and technical factors that limit performance. Strength and Conditioning Journal, 36: 4–27. Myer, G.D., Ford, K.R., and Hewett, T.E. (2008). Tuck jump assessment for reducing anterior cruciate ligament injury risk. Athletic Therapy Today, 13: 39–44. Nakagawa, T.H., Moriya, E.T.U., Maciel, C.D., and Serrao, F.V. (2012). Trunk, pelvis, hip, and knee kinematics, hip strength, and gluteal muscle activation during a single-leg squat in males and females with and without patellofemoral pain syndrome. Journal of Orthopaedic and Sports Physical Therapy, 42: 491–501. Noehren, B., Barrance, P.J., Pohl, M.P., and Davis, I.S. (2012). A comparison of tibiofemoral and patellofemoral alignment during a neutral and valgus single leg squat: An MRI study. The Knee, 19: 380–386. Noyes, F.R., Barber, S.D., and Mangine, R.E. (1991). Abnormal lower limb symmetry determined by function hop tests after anterior cruciate ligament rupture. American Journal of Sports Medicine, 19: 513–518. O’Connor, F.G., Deuster, P.A., Davis, J., Pappas, C.G., and Knapik, J.J. (2011). Functional movement screening: Predicting injuries in officer candidates. Medicine and Science in Sports and Exercise, 43(12), 2224–2230. Okada, T., Huxel, K.C., and Nesser, T.W. (2011). Relationship between core stability, functional movement, and performance. Journal of Strength and Conditioning Research, 25: 252–2611. Padua, D.A., Boling, M.C., DiStefano, L.J., Onate, J.A., Beutler, A.I. and Marshall, S.W. (2011). Reliability of the Landing Error Scoring System-real time, a clinical assessment tool of jump-landing biomechanics. Journal of Sport Rehabilitation, 20, 145–156. Padua, D.A., DiStefano, L.J., Marshall, S.W., Beutler, A.I., De la Motte, S.J., and DiStefano, M.J. (2012). Retention of movement pattern changes after a lower extremity injury prevention program is affected by program duration. American Journal of Sports Medicine, 40: 300–306. Padua, D.A., Marshall, S.W., Boling, M.C., Thigpen, C.A., Garrett, W.E., and Beutler, A.I. (2009). The Landing Error Scoring System (LESS) is a valid and reliable clinical assessment tool of jump-landing biomechanics: The Jump-ACL study. American Journal of Sports Medicine, 37: 1996–2002. Parchmann, C.J., and McBride, J.M. (2011). Relationship between Functional Movement Screen and athletic performance. Journal of Strength & Conditioning Research, 25: 3378–3384. Read, P.J., Oliver, J.L., De Ste Croix, M.B.A., Myer, G.D., and Lloyd, R.S. (2015). Reliability of the tuck jump assessment injury risk screening assessment in elite male youth soccer players. Journal of Strength and Conditioning Research, 30: 1510–1516. Reid, A., Birmingham, T.B., Stratford, P.W., Alco*ck, G.K., and Giffin, J.R. (2007). Hop testing provides a reliable and valid outcome measure during rehabilitation after anterior cruciate ligament reconstruction. Physical Therapy, 87: 337–349. Rohman, E., Steubs, J.T., and Tompkins, M. (2015). Changes in involved and uninvolved limb function during rehabilitation after anterior cruciate ligament reconstruction: Implications for limb symmetry index measures. American Journal of Sports Medicine, 43: 1391– 1398. Ross, M.D., Langford, B., and Whelan, P.J. (2002). Test-retest reliability of 4 single-leg horizontal hop tests. Journal of Strength and Conditioning Research, 16: 617–622. Smith, H.C., Johnson, R.J., Shultz, S.J., Tourville, T., Holterman, L.A., Slauterbeck, J., Vacek, P.M., and Beynnon, B. D. (2012). A prospective evaluation of the Landing Error Scoring System (LESS) as a screening tool for anterior cruciate ligament injury risk. American Journal of Sports Medicine, 40: 521–526. Stergiou, N., Ristanis, S., Moraiti, C., and Georgoulis, C. (2007). Tibial rotation in anterior cruciate ligament (ACL)-deficient and reconstructed knees: A theoretical proposition for the development of osteoarthritis. Sports Medicine, 37: 601–613. Trulsson, A., Miller, M., Hansson, G.A., Gummesson, C., and Garwicz, M. (2015). Altered movement patterns and muscular activity during single and double leg squats in individuals with anterior cruciate ligament injury. BMC Musculoskeletal Disorders, 16: 28. Turner, A., Brazier, J., Bishop, C., Chavda, S., Cree, J., and Read, P. (2015). Data analysis for strength and conditioning coaches: Using Excel to analyse reliability, differences, and relationships. Strength and Conditioning Journal, 37: 76–83. Whiteside, D., Deneweth, J.M., Pohorence, M.A., Sandoval, B., Russell, J.R., McLean, S.G., Zernicke, R.F., and Goulet, G.C. (2014). Grading the Functional Movement Screen: A comparison of manual (real-time) and objective methods. Journal of Strength and Conditioning Research, 30: 924–933. Willy, R.W., Manal, K.T., Witvrouw, E.E., and Davis, I.S. (2012). Are mechanics different between male and female runners with patellofemoral pain? Medicine and Science in Sports and Exercise, 44: 2165–2171. Zeller, B.L., McCrory, J.L., Kibler, B., and Uhl, T.L. (2003). Differences inn kinematics and electromyographic activity between men and women during the single-legged squat. American Journal of Sports Medicine, 31: 449–456.
CHAPTER 14
Technical demands of strength training Timothy J. Suchomel and Paul Comfort INTRODUCTION There are a number of factors to consider when implementing various forms of resistance training. While some factors such as the range of motion (ROM) performed, grip/stance, and load placement appear to be simplistic, others such as rest intervals, the direction that force is produced during exercises, and the intent of the movement, may be overlooked by practitioners. Thus, it is important for practitioners to develop an understanding of how each factor may affect potential training adaptations.
SECTION 1 EXERCISE TECHNIQUE The technique used during a given exercise may largely alter the resultant training stimulus. Aside from an athlete’s anthropometrics and training age, an exercise may be modified through changes in the ROM performed or the grip or stance adopted. The following paragraphs will discuss each of the outlined topics and how they may affect the adaptations elicited from training.
Range of motion The ROM performed during an exercise describes the displacement of an athlete’s body mass and/or the external load being lifted. When prescribing exercises for athletes, practitioners must focus on not only the ability of athlete to perform the exercise, but teaching them to perform each exercise through a ROM that permits the safe/correct execution of the exercise and will ultimately elicit the desired training adaptations. There is little debate that performing an exercise with proper technique is more important than the weight that may be lifted, however, some athletes may sacrifice the ROM performed in order to ‘claim’ that they lifted a heavier load. While this practice may only occur during ‘max out’ sessions, it should not be encouraged due to the training implications that may result from chronic use (e.g., training to failure mindset, developing poor technique habits, etc.). Instead, practitioners should promote the execution of exercises through the full ROM an athlete is able to perform, taking into account existing constraints such as the athlete’s safety, flexibility, anthropometrics, and previous injuries that may hinder performance. By promoting such a practice, it is more likely that athletes will develop good training habits and positive training adaptations (e.g., increased strength and power, decreased injury risk, and improved/maintained ROM at the trained joints). Squatting variations (e.g., back squat, front squat, goblet squat, etc.) are one of the most commonly prescribed exercises within resistance training programs. Regardless of the variation, the method in which it is performed is often the subject of discussion when it comes to the desired ROM performed by athletes. Based on a practitioner’s coaching philosophy, he or she may desire that their athletes perform full squats, parallel squats, half-squats, quarter-squats, or any combination of those previously listed. Certain squat depths may be considered by some to be ‘more position specific’ or ‘safer’; however, the desired adaptations being sought may dictate the ROM performed. For example, previous research indicated that training with deep squats produced greater increases in quadriceps muscle cross-sectional area, lower extremity lean body mass, isometric knee extension strength, and jump height compared to shallow squats (Bloomquist et al., 2013). However, additional research indicated that training with quarter-squats produced greater improvements in sprint speed adaptations compared to full squats (Rhea et al., 2016). It is important to note that the ROM performed during an exercise may dictate the activation of specific musculature, the training adaptations elicited, or the specificity to a sport movement. Previous research has indicated that greater gluteus maximus activation occurs during deeper squats, but found no differences between partial, parallel, or deep squats in vastus medialis, vastus lateralis, or biceps femoris activation (Caterisano et al., 2002). Similarly, Gorsuch et al. (2013) displayed that
greater activation of the rectus femoris and erector spinae muscles was produced during parallel squats compared to partial squats, but noted no differences in biceps femoris or lateral gastrocnemius activation between squat variations. Additional literature supports these findings for the rectus femoris (Pereira et al., 2010), moreover, Bryanton et al. (2012) suggested that greater relative muscular effort was produced at greater squat depths for both hip and knee extensors. While practitioners may have their opinions on what ROM should be performed, the decision to increase or decrease the ROM performed may be justified if the athlete is returning from injury or within specific training periods where larger or smaller volume-loads may be needed to elicit specific training adaptations. A further description of this will be discussed in Section 2 below.
Grip and stance variation The grip or stance used during a given exercise may modify the training stimulus by changing the muscle activation patterns of the muscles being trained. For example, a wider grip during a bench press may increase the amount of activation of the sternoclavicular portion of the pectoralis major while decreasing the activation of the triceps brachii and anterior deltoid (Lehman, 2005, Barnett et al., 1995), however, such a grip may increase risk of shoulder injuries. Similarly, a wider squat stance may increase the activation of the adductor muscles (McCaw and Melrose, 1999), while a wider deadlift stance may increase vastus medialis, vastus lateralis, and tibialis anterior activation (Escamilla et al., 2002). Whether referring to a bench press, squat, or deadlift variation, different activation patterns may alter the extent to which the musculature is activated, which may ultimately affect potential architectural or neuromuscular adaptations. Previous literature has discussed this idea in greater detail for the bench press (Green and Comfort, 2007) and pull-up/lat pull-down (Leslie and Comfort, 2013) exercises. Another grip consideration that has been previously discussed is the use of the ‘hook grip’ (Favre and Peterson, 2012). The hook grip is frequently used during the traditional weightlifting movements (e.g., snatch, clean and jerk) and their derivatives (e.g., clean pull from the floor, hang power snatch, mid-thigh pull, etc.). The idea behind the hook grip is that by wrapping additional fingers around the thumb, the athlete may prevent grip from being a limiting factor when it comes to the weight that can be lifted for single and multiple repetitions.
MECHANICAL DEMANDS OF EXERCISES Force-velocity characteristics The nature of each exercise partially determines the force-velocity characteristics that an athlete trains. For example, the back squat serves as a force-dominant exercise in which the primary goal is to develop muscular strength. In contrast, the jump squat is a velocity-dominant exercise that may be used to develop high-velocity/power characteristics. Cormie et al. (2010a) displayed that relatively weak men may improve their athletic performance by training with either a strength or ballistic training emphasis. However, the authors also noted specific adaptations (i.e., greater strength vs. greater velocity adaptations) based on the type of training used. While it is important to emphasise high-force movements or high-velocity movements during certain periods of the training year, previous literature has promoted the use of combined loading (Haff and Nimphius, 2012) where
athletes train and develop both the force and velocity sides of their force-velocity profile, although altering the primary focus periodically. Training in such a manner may ultimately lead to favorable adaptations in rate of force development (RFD) and power (Cormie et al., 2007). A recent review discussed how this method of training can be implemented using a sequenced progression of weightlifting derivatives (Suchomel et al., 2017).
Stretch-shortening cycle The inclusion/exclusion of the stretch-shortening cycle (SSC) within a movement may impact the training stimulus an athlete receives. The SSC may allow for the activation of the stretch-reflex, optimisation of length-tension muscle factors, optimisation of muscle activation, and the concentric muscle action beginning at a higher force output (Aagaard et al., 2000, Komi, 2000, Komi, 1986, Cormie et al., 2010b). By using the SSC, an athlete may produce greater magnitudes and rates of force production, potentially allowing for heavier loads to be lifted or a given load being lifted at a higher velocity. In contrast, movements that exclude the SSC may require unique neuromuscular demands. For example, an exercise performed using a static start position may require a greater RFD compared to a movement that includes the SSC because an athlete must overcome the inertia of the training load from a dead-stop position compared to having developed a given magnitude of force previously. This has been observed in research that examined weightlifting derivatives (Comfort et al., 2011b, Comfort et al., 2011a). The inclusion/exclusion of the SSC may place varying demands on athletes, and thus, practitioners should consider each athlete’s sport/event when programming exercises to allow for maximum transfer of training.
Load placement Similar to the ROM discussed above, the placement of the load during different exercise variations (e.g., front squat vs. back squat) may modify the activation of specific musculature. One study indicated that the front squat produced greater vastus lateralis activation during the ascending phase and entire movement, while the back squat produced greater semitendinosus activation during the ascending phase (Yavuz et al., 2015). In contrast, two other studies reported no differences in muscle activation between the front squat and back squat (Gullett et al., 2009, Contreras et al., 2016a, Yavuz et al., 2015). Additional research demonstrated that greater peak force, velocity, and power were achieved using a hexagonal bar deadlift compared to a traditional deadlift (Swinton et al., 2011). While the previous example discusses exercises that are typically used for strength development, similar results have been shown with ballistic jumping movements. Previous research discussed the acute kinetic and kinematic differences between the jump squat and hexagonal bar jump (Swinton et al., 2012). Their results indicated that the hexagonal bar jump produced greater force, RFD, and jump heights at several different loads. Both studies by Swinton et al. (2011, 2012) noted that the differences displayed may have been due to more favourable moment arms based on the load being closer to the lifter’s centre of mass, ultimately allowing for more efficient vertical force production.
Force production vectors Muscular strength has been defined as the ability to produce force against an external resistance; however, when it comes to exercise selection, the direction in which the force is produced may alter
an athlete’s training outcomes. Recent research has examined the effects of training with exercises that emphasise more vertical force vectors compared to horizontal (Contreras et al., 2016b) or unilateralmultidirectional (Gonzalo-Skok et al., 2016). Contreras et al. (2016b) indicated that adolescent rugby and rowing athletes who trained with either the front squat or barbell hip thrust for six weeks demonstrated specific force vector adaptations. Specifically, those who trained with the front squat displayed greater improvements in the vertical jump, while the hip thrust group displayed greater improvements in the horizontal jump and 10m and 20m sprint times. Similarly, Gonzalo-Skok et al. (2016) indicated that amateur/semiprofessional team-sport athletes who trained with squats produced greater unilateral and bilateral vertical jump and 25m sprint adaptations compared to those who trained with unilateral-multidirectional versapulley. In addition, those who trained using the versapulley produced greater improvements in lateral and horizontal jumps and change of direction tasks. Considering the above results, practitioners may note that the application of force during various exercises may produce specific adaptations. DeWeese et al. (2016) discussed this idea regarding resistance training practices for developing sprint speed. Although the above studies contradicted each other with what training method produced superior results, it is important that practitioners understand the orientation of the athlete when they are generating force.
Ballistic and non-ballistic exercises The nature of the exercise(s) performed may result in a different training stimulus experienced by the athlete based on the intent of the movement. As noted above and in Chapter 2, this may include modifications in the force-velocity characteristics of the exercise. Previous work by Lake et al. (2012) and Newton et al. (1996) has highlighted the differences between lower and upper body exercises performed in a ballistic manner (i.e., acceleration throughout the entire movement) and exercises performed quickly (i.e., intentionally fast with a negative acceleration at the end of the movement). Taken together, these studies indicated that exercises performed in a ballistic manner produced greater force, velocity, power, and muscle activation compared to the same exercises performed quickly. Practitioners may choose from a variety of ballistic exercises that may provide an effective training stimulus. Regarding the development of lower body explosive strength, the exercises that first come to mind may be the weightlifting movements and their derivatives due to their ability to improve force-velocity characteristics to a greater extent compared to other training methods (Hoffman et al., 2004, Tricoli et al., 2005, Otto III et al., 2012, Teo et al., 2016, Arabatzi and Kellis, 2012, Chaouachi et al., 2014, Channell and Barfield, 2008). This is likely due to movement specificity, but also the ability to accelerate a moderate-heavy load in a jumping movement with ballistic intent. Greater detail on how practitioners can use weightlifting movements to enhance sport performance will be covered in Chapter 15. While weightlifting movements provide an effective ballistic training stimulus, it should be noted that exercises like the jump squat (Cormie et al., 2010a), kettlebell swing (Lake and Lauder, 2012), and ballistic squat can also provide an effective training stimulus for the improvement of lower body explosive strength. Regarding ballistic upper body exercises, practitioners may be more limited with their exercise selection. Typical upper body ballistic exercises may include the bench press throw, plyometric pushup, and medicine ball throw. Newton et al. (1996) indicated that a ballistic bench press throw may produce greater force, power, and muscle activation compared to a bench press performed quickly. The extent of these differences can be explained by the velocity of the movement throughout its
completion. The previous study noted that the velocity of the ballistic bench press throw was accelerated throughout the entire movement whereas the traditional bench press decelerated at the end of the movement. Taking these results into account, the traditional bench press may serve as more of a foundational exercise to develop strength, while the bench press throw may be used to develop RFD and power characteristics (Soriano et al., 2016). Similarly, Vossen et al. (2000) indicated that plyometric push-ups result in greater improvements in strength and power compared to traditional push-ups. As noted above, the ability of ballistic exercises to improve a strength/power training stimulus is well documented. An additional benefit of ballistic exercises may be their ability to be used as a potentiation stimulus, as noted by Maloney et al. (2014). Previous research indicated that ballistic, concentric-only half-squats produced a larger and faster potentiation effect compared to those performed in a non-ballistic manner (Suchomel et al., 2016c, Suchomel et al., 2016d). This may be due to the ability of ballistic exercises to recruit high threshold motor units (van Cutsem et al., 1998), which display greater potentiation compared to smaller lower threshold motor units (Hamada et al., 2000).
REST INTERVALS Inter-set rest intervals Previous literature has indicated that rest intervals as short as 30 seconds (Sheppard and Triplett, 2016) or one minute (Kraemer et al., 2002) may be used to stimulate adaptations in muscle hypertrophy. While a greater metabolic demand may be present following high volume exercise sets (Gorostiaga et al., 2012, Gorostiaga et al., 2010), an athlete’s ability to recover during a short rest interval is limited, and thus, their capacity to tolerate the same loads or heavier loads becomes diminished as the number of sets increases (de Salles et al., 2009, Buresh et al., 2009). This is likely due to decreased adensosine triphosphate (ATP), phosphocreatine (PCr), and glycogen concentrations as well as increases in lactate concentrations due to repetitive high volume sets (Gorostiaga et al., 2012, Gorostiaga et al., 2010). As noted in Chapter 4, shorter rest intervals may induce elevations in anabolic hormones such as growth hormone (Kraemer et al., 1990, Kraemer et al., 1993, Boroujerdi and Rahimi, 2008). However, shorter rest intervals may also produce greater elevations in cortisol (Kraemer et al., 1993, Rahimi et al., 2010a, Rahimi et al., 2010b, Buresh et al., 2009), which may ultimately attenuate the effect that growth hormone and possibly testosterone (Rahimi et al., 2011) have on muscle hypertrophy. Despite previous recommendations, additional literature indicated that longer rest intervals (1.5–3 minutes) may produce superior muscle hypertrophy and strength adaptations compared to shorter inter-set rest intervals (0.5–1 minute) (Schoenfeld et al., 2016, Robinson et al., 1995). This may be due to a number of factors; however, one must consider not only the quantity of work, but the quality of work. For example, previous research indicated that subjects were unable to complete four sets of ten repetitions during the back squat with 70% 1RM and two minutes of inter-set rest (Oliver et al., 2016). In response to the failed sets, the authors noted that they decreased the load performed within the remaining sets, which likely decreased the overload placed on the athlete. Longer inter-set rest periods may allow for an athlete to replenish their ATP stores and lessen the metabolic fatigue experienced to a greater extent prior to a subsequent set compared to shorter rest periods. Ultimately,
this may lead to a higher quality of work performed through the continued use of the prescribed loads, and possible increased loads, during all sets, potentially leading to greater physiological adaptations (e.g., work capacity and muscle cross-sectional area). Collectively, it appears that while shorter rest intervals have the potential to produce a hypertrophic response, peak adaptations in trained individuals may be limited due to the loads that may be maintained over multiple exercise sets. Moreover, if the ultimate goal is to increase the muscular power of the athlete, training with shorter rest intervals may result in an endurance effect, which may interfere with long-term hypertrophy adaptations (Hawley, 2009, Baar, 2006). It should be noted that if practitioners are concerned with the increase in the overall training time associated with longer inter-set rest intervals, they may consider short rest intervals within a set to spilt up and maintain the work performed. This approach to training, termed cluster set training (Haff et al., 2008), will be discussed in greater detail below. Much of the existing literature suggests that longer rest intervals may produce superior adaptations in muscular strength and power. As mentioned above, Robinson et al. (1995) indicated that longer rest intervals (1.5–3 minutes) produced greater strength and power adaptations during a high-volume program. Additional research indicated that longer rest intervals (2.5–5 minutes) resulted in a greater volume of work to be performed during a workout (Willardson and Burkett, 2005, Willardson and Burkett, 2008), greater ability to train with heavier loads (Willardson and Burkett, 2006), and greater strength increases (de Salles et al., 2010, Pincivero et al., 1997, Robinson et al., 1995) compared to shorter rest intervals (0.5–2 minutes). While another study indicated that no statistical differences in strength gains were found between two and four minute rest intervals (Willardson and Burkett, 2008), those who trained using longer rest intervals produced a larger practical effect compared to those who trained with shorter rest intervals (i.e., Cohen’s d = 2.96, very large vs. d = 1.96, large) (Hopkins, 2014). The discussed research is in line with previous rest interval recommendations for improving muscular strength and power (i.e., 2–5 minutes) (Sheppard and Triplett, 2016, Kraemer et al., 2002, de Salles et al., 2009). It should be noted that the range in rest interval length may exist due to the training age (Willardson and Burkett, 2008), fibre type composition of the athletes, and the loads implemented in training. Rest interval recommendations are summarised in Table 14.1.
Intra-set/inter-repetition rest intervals A growing body of literature has investigated inter-repetition rest within a set of exercise. Specifically, research has examined the effect that cluster sets (Haff et al., 2008) have on kinetic, kinematic, and technique characteristics during various repetition schemes. A cluster set may be defined as a traditional exercise set that is split into smaller sets of repetitions (i.e., clusters) that are separated by rest intervals. One of the first studies examining cluster sets investigated the effect of various set configurations (i.e., traditional, undulating, and cluster) on clean pull performance (Haff et al., 2003). Their results indicated that a cluster set configuration may result in greater barbell velocity and displacement and power-generating capacity across an entire set. A similar series of studies examined the effect of rest interval length between repetitions within several sets on various power clean performance variables (Hardee et al., 2013, Hardee et al., 2012b, Hardee et al., 2012a). Collectively, their results indicated that cluster set configurations using 20–40 seconds of rest between repetitions allowed the subjects to maintain power output, technique, and lower their perceived exertion.
TABLE 14.1 Rest interval length to achieve specific training goals. Rest interval length may vary based on the type of exercise, load, repetition scheme, and training status of the athlete Training goal
Rest interval length
Hypertrophy
1.5–3 minutes
Strength
2–5 minutes
Power
2–5 minutes
Additional literature examined the effect of cluster set configurations on higher repetition sets that focus on muscle hypertrophy. A series of studies reported that high repetition sets with inter-repetition rest resulted in greater gains in strength and power, while producing similar gains in lean body mass (Oliver et al., 2013), greater total volume load and power, similar anabolic hormonal response, and decreased metabolic stress (Oliver et al., 2015), and maintained force, velocity, and power (Oliver et al., 2016) compared to traditional sets. Additional research indicated that cluster sets that utilised 30 second rest intervals between either two or four repetitions within a set of 12 maintained force, velocity, and power (Tufano et al., 2016c), and allowed for greater force, total work, and time under tension (Tufano et al., 2016b). Considering the metabolic demand that high repetition sets place on the body (Gorostiaga et al., 2012, Gorostiaga et al., 2010), which may limit the utilisation of specific loads as the number of sets increases (de Salles et al., 2009, Buresh et al., 2009), the benefits of using cluster sets should not be overlooked. Practitioners must take note of the amount of total training time required if certain rest intervals are implemented within cluster set configurations. For example, previous research noted that performing six, two repetition clusters for a set of 12 total repetitions may take longer than performing three, four repetition clusters (Tufano et al., 2016c). Smaller clusters require a larger amount of training time due to the increased amount of rest taken within a set. Considering that some sport governing bodies set strict guidelines on the amount of time for team activities, it is important for practitioners interested in using cluster sets to choose cluster set configurations that are both time efficient and effective at managing fatigue. For a more thorough discussion on the theoretical and practical applications of cluster sets, readers are directed to a recent review (Tufano et al., 2016a). Cluster set rest interval recommendations are summarised in Table 14.2.
Potentiation complex rest intervals While the previously discussed rest intervals may be specific to traditional resistance training exercises, unique rest intervals may exist when implementing potentiation complexes. There are a number of factors that may affect the magnitude of potentiation expressed (Suchomel et al., 2016a, Tillin and Bishop, 2009). However, a portion of the existing potentiation literature has focused on examining the effect that various rest intervals have on the magnitude of potentiation expressed. Following a potentiating stimulus, both a state of fatigue and potentiation exist (Fowles and Green, 2003, Rassier and Macintosh, 2000, Hodgson et al., 2005, Sale, 2002). The interplay between fatigue and potentiation may be acutely modeled on the fitness-fatigue paradigm (Zatsiorsky, 1995), where the subsequent performance is the result of the interaction between fatigue and the fitness after-effects that are the result of an exercise stimulus. While meta-analyses indicated that rest intervals ranging three to seven minutes, seven to ten minutes (Wilson et al., 2013), and eight to twelve minutes
(Gouvêa et al., 2013) produced positive moderate practical effects, additional literature indicated that the type, intensity, and duration of the exercise may determine whether fatigue or potentiation is dominant over the other (Masiulis et al., 2007). Thus, it should come as no surprise that certain protocols may produce positive moderate practical effects as early as two minutes post-stimulus (Suchomel et al., 2016c) or as late as 15 or 20 minutes post-stimulus (Gilbert and Lees, 2005). Therefore, practitioners should consider that each individual potentiation complex possesses unique characteristics and may therefore have its own ‘optimal’ rest interval. TABLE 14.2 Cluster set rest interval length to achieve specific training goals. Adapted from Haff (2016) Training goal
Cluster set rest interval length
Hypertrophy
5–15 seconds
Strength
20–25 seconds
Power
30–40 seconds
Another factor that may affect the rest interval during various potentiation complexes is the relative strength of the individuals completing the protocol. Previous literature has indicated that strong relationships exist between an individual’s relative strength and the magnitude of potentiation expressed (Suchomel et al., 2016d, Seitz et al., 2014, Suchomel et al., 2016b). This idea is supported by the notion that stronger individuals may be able to tolerate a more fatiguing protocol given their frequent exposure to high intensity loading during training (Stone et al., 2008). Moreover, additional literature noted that stronger individuals potentiate earlier (Suchomel et al., 2016d, Seitz et al., 2014, Jo et al., 2010) and to a greater extent compared to weaker individuals. Thus, when designing potentiation complexes for athletes, practitioners should ensure that they take the athlete’s relative strength into account.
SECTION 2 – PRACTICAL APPLICATIONS MODIFICATIONS FOR APPROPRIATE EXERCISE PERFORMANCE Appropriate modifications/alternatives may need to be made in order for an athlete to safely perform a specific exercise or receive a given training stimulus. Whether it may be inexperience with an exercise or a lack of quality coaching, some athletes have difficulty performing certain exercises. Thus, it is important to provide athletes with consistent coaching modifications to help them learn and/or improve their technique in order to perform exercises correctly. Previous recommendations were made to maximise leg muscle activation and minimise the risk of injury during the back squat (Comfort and Kasim, 2007). Briefly, an athlete’s feet should be wider than shoulder-width apart with a natural foot position (McCaw and Melrose, 1999, Ninos et al., 1997), unrestricted movement of the knees while the heels maintain contact with the floor (Fry et al., 2003), a forward or upward gaze (Donnelly et al., 2006), and full ROM (115–125° of knee flexion) (Caterisano et al., 2002, Ninos et al., 1997) as long as the athlete is able to maintain a lordotic curve or neutral spine. Some athletes may have difficulty reaching the desired squat depth due to several potential issues (e.g., inexperience, stance, lack of flexibility, balance, etc.). Some common methods to implement that may help an athlete achieve the desired squat depth may be to modify their stance width and/or rotating their toes out (i.e., hip external rotation). These modifications will open up the hip joints and allow for greater displacement of the athlete’s body. While the above provides one example, additional technique recommendations have been made for the bench press (Green and Comfort, 2007) and pull-up/lat pull-down (Leslie and Comfort, 2013) exercises.
Footwear While some athletes may be able to effectively squat to the desired depth by adjusting their stance width or turning their toes out, a pre-existing anatomical limitation or lack of flexibility within the ankle may still prevent an athlete from performing a good squat. An additional consideration may be to slightly elevate the heels of athletes in order to lessen the effect that this limitation has on their squat performance. This may be accomplished by placing small weights under an athlete’s heels or by purchasing weightlifting shoes. Previous literature has indicated that weightlifting shoes may allow for a greater squat depth, an upright torso, and greater stability to be achieved (Legg et al., 2017, Hughes and Prescott, 2015). Further work has suggested that weightlifting shoes may reduce the forward trunk lean of individuals, reducing potential shear stress in the spine, and also increase knee extensor muscle activation compared to running shoes (Sato et al., 2012). While the addition of weightlifting shoes will not inherently fix poor squat technique by themselves, it appears that they may allow athletes to achieve a greater squat depth, allow for a more vertical torso, improve stability, and increase muscle activation, which may lead to improvements in strength and potential reductions in injuries.
Weightlifting movements The weightlifting movements (i.e., snatch and clean and jerk) and their derivatives are popular exercises within resistance training programs. However, they are often described as technically
complex movements that are difficult to teach and for athletes to learn. Practitioners may find that some of their athletes may have difficulty learning a particular aspect of a full weightlifting movement (e.g., performing the first pull to the knee, transitioning to the second pull starting position, properly executing the catch phase, etc.). While this may deter some practitioners from prescribing weightlifting movements within their athletes’ training programs, it should be noted that a number of derivatives exist that serve as effective substitutes (Suchomel et al., 2017). Scenarios that a practitioner may face when it comes to choosing an alternative weightlifting movement are displayed in Figures 14.1 and 14.2.
FIGURE 14.1
Scenario requiring weightlifting alternatives for the snatch.
FIGURE 14.2
Scenario requiring weightlifting alternatives for the hang power clean.
Unilateral training alternatives Although the back squat exercise is a popular choice for lower extremity strength development, it is not without its limitations. As mentioned above, it is possible that the back squat may result in a greater forward lean compared to the front squat. Moreover, this may result in greater shear forces in the spine experienced by athletes. While proper technique modifications with the potential assistance of weightlifting shoes may mediate these issues, practitioners should also note that unilateral exercises, such as the rear foot elevated split squat, may serve as effective exercise alternatives. Previous literature indicated that unilateral training resulted in similar improvements in strength and power adaptations (McCurdy et al., 2005), as well as sprint speed and agility (Speirs et al., 2016). Further research indicated that a modified split squat resulted in greater gluteus medius, hamstring, and quadriceps activation compared to a bilateral squat (McCurdy et al., 2010). These authors also noted that the modified split squat also maintained a more upright torso, which may potentially decrease shear force stress in an athlete’s lower back. This notion is supported by large effect size
differences in left and right erector spinae activation between the rear foot elevated split squat and back squat exercise (Bellon et al., 2013). Collectively, the previous literature that has compared the effects of unilateral and bilateral lower extremity exercises indicates that unilateral exercises may be suitable alternatives for practitioners to prescribe, especially if an athlete is hampered by lower back pain. However, it should be noted that unilateral exercises may be best implemented as assistance exercises to bilateral lifts due to the decreased stability of a single limb being used.
CUEING AND FEEDBACK Sport and strength and conditioning coaches traditionally have their own methods of cueing and providing feedback to athletes. While this is done to get athletes to perform an exercise or task in a certain manner, practitioners should note that how they provide cues and feedback may have a profound effect on the training stimulus that athletes receive.
Cueing Previous work by Wulf (2007) indicates that cues and feedback that are external (i.e., athlete focuses on movement effect) are much more effective than those that are internal (i.e., athlete focuses on his or her body movements) when it comes to how motor skills are performed, learned, and retained. A recent review that discussed instructions and cues for improving sprint performance echoed these sentiments, suggesting that cueing should provide an external focus for the athlete (Benz et al., 2016). The authors suggested that coaches should consider providing external and/or neutral cues at a 100% frequency while keeping the quantity of instructions low. A similar strategy may be applied when cueing athletes in the weight room. For example, if an athlete is performing an overhead press and the training emphasis is speed-strength, an appropriate external cue may be: ‘Make the bar rattle at the top.’ Compared to an internal cue of: ‘Contract your arms faster to push the weight.’ From the athlete’s perspective, the external cue gives them the goal based on a sound that would indicate that they moved the weight quickly. As athletes become more experienced, smaller cueing phrases may be used. At this point, an athlete and their coach understand what a specific cue means for them compared to another athlete. A common cue used in the weight room that can be applied to many scenarios is: ‘Stay tight!’ As previously mentioned, this cue may be sufficient for a more experienced athlete; however, it may also mean something different to two different athletes. It is recommended that practitioners apply an external focus strategy when it comes to cueing exercises, keeping in mind that the amount of information provided should be concise and specific to each athlete.
Feedback Similar to coaching cues, research supports the use of providing external feedback to athletes as opposed to internal feedback. Coaches can provide feedback in a variety of ways including audio (e.g., verbal discussions), visual (e.g., video analysis and/or demonstrations), and quantitative (e.g., data display). Previous research demonstrated that augmented feedback (including coaching and 2-D video analysis) resulted in greater kinetic and kinematic adaptations during the power snatch exercise compared to a control group (Winchester et al., 2009). While this method was effective, another study examined the use of the method of amplification of error (MAE) and how it affected snatch
performance compared to traditional coaching feedback (Milanese et al., 2017). Briefly, MAE allows athletes to learn to correct their movements by understanding how to perform the movement incorrectly. The authors indicated that the MAE group produced greater kinematic improvements of snatch technique compared to direct instruction only. Finally, a practical example of quantitative feedback may be through the use of velocity-based training (Mann et al., 2015). In order to achieve a specific velocity during training, the athlete may need to be provided with immediate velocity feedback. Using current technologies, an athlete may see the velocity they produced and adjust the weight accordingly in order to meet the goal of that particular training session. The amount of feedback given to an athlete may be based on their training age. However, practitioners should be cautious as to how much feedback is provided at any given time. Athletes may not be able to receive multiple pieces of information and perform an exercise effectively, especially if feedback is provided after every repetition. In order to effectively provide feedback to an athlete, practitioners should choose one point of emphasis that an athlete can work on during subsequent training sets. Practitioners should focus on the most important aspect that is hindering appropriate exercise performance before fine-tuning technique with smaller corrections. This is especially true if an athlete is putting themselves at risk for injury.
RANGE OF MOTION SPECIFICITY EXAMPLE While practitioners may have their opinions on what ROM should be performed (full or partial), the decision to increase or decrease the ROM may be justified if the athlete is returning from injury or training within specific training periods where larger or smaller volume-loads may be needed to elicit specific training adaptations. The most obvious instance would include an athlete’s return from an injury. In this situation, practitioners may not be as focused on improvements that will transfer to the athlete’s sport/event, but instead may be focused on having the athlete regain the competency of an exercise using a reduced ROM. Some of this training may be dictated by the sports medicine staff; however, strength and conditioning practitioners should be aware and involved in some capacity as well. Ultimately, once an athlete again achieves the desired ROM during a given exercise, strength and conditioning practitioners may take over and transition the athlete into a return to fitness phase. While the above scenario certainly occurs, it should be noted that it may be practical to reduce the ROM of a given exercise during certain times of the training year in order to maintain certain abilities or reach peak adaptations. For example, it may be preferable during certain times of year to perform half-squats or quarter-squats in order to dissipate any accumulated fatigue and to peak for a certain event. If a practitioner is working with a sprinter, reducing the ROM of the work sets may be advantageous from multiple aspects. For example, it may be practical to progress a sprinter from performing full squats and adding in half-squats and quarter-squats during certain phases of training (Bazyler et al., 2014). Using a progression may not only reduce an athlete’s neuromuscular fatigue due to less eccentric work performed, but partial squats may also increase the mechanical specificity of their training for maximum velocity. This notion is supported by recent research that indicated that training with quarter-squats resulted in greater improvements in 40-yard sprint time and vertical jump height compared to training with full and half-squats (Rhea et al., 2016). However, it should be noted that additional literature has suggested that the complete removal of full ROM squats in trained individuals may result in a plateau and possible reductions in 1RM strength (Harris et al., 2000, Painter et al., 2012). Thus, practitioners should consider prescribing a combination of both full and
partial ROM squats in order to improve/maintain overall and angle-specific strength.
SUMMARY While there are a number of factors that a practitioner must consider when prescribing resistance training exercises to their athletes, each individual factor should not be overlooked. Exercise technique considerations such as the ROM performed and the grip/stance used may alter the training stimulus for athletes. In addition, practitioners must consider mechanical demands of each exercise including their force-velocity characteristics, the inclusion/exclusion of the SSC, load placement, direction in which the force is produced, and ballistic/non-ballistic nature. Finally, the rest intervals used, whether they are inter-set, intra-set, or within potentiation complexes, should be specific to the characteristics that are being developed within each phase of training. From a practical standpoint, practitioners should implement appropriate modifications to exercises in order to provide an effective training stimulus for their athletes. In addition, consistent external coaching cues combined with specific feedback will improve the learning and retention of challenging tasks. Finally, practitioners should note that a decreased ROM combined with a sufficient load may provide an effective training stimulus that is more specific to positions achieved during different phases of sport training.
REFERENCES Aagaard, P., Simonsen, E. B., Andersen, J. L., Magnusson, S. P., Halkjaer-Kristensen, J. & Dyhre-Poulsen, P. 2000. Neural inhibition during maximal eccentric and concentric quadriceps contraction: effects of resistance training. J Appl Physiol, 89, 2249–2257. Arabatzi, F. & Kellis, E. 2012. Olympic weightlifting training causes different knee muscle-coactivation adaptations compared with traditional weight training. J Strength Cond Res, 26, 2192–2201. Baar, K. 2006. Training for endurance and strength: lessons from cell signaling. Med Sci Sports Exerc, 38, 1939–1944. Barnett, C., Kippers, V. & Turner, P. 1995. Effects of variations of the bench press exercise on the EMG activity of five shoulder muscles. J Strength Cond Res, 9, 222–227. Bazyler, C. D., Sato, K., Wassinger, C. A., Lamont, H. S. & Stone, M. H. 2014. The efficacy of incorporating partial squats in maximal strength training. J Strength Cond Res, 28, 3024–3032. Bellon, C. R., Leigh, S. & Suchomel, T. J. A comparison of muscle activation of the lower back and legs between a back squat and a rear foot elevated split squat exercise. In: Beckham, G. K. & Swisher, A., eds. 8th Annual Coaches and Sport Science College, December 13–14, 2013. Johnson City, TN. 17–19. Benz, A., Winkleman, N., Porter, J. & Nimphius, S. 2016. Coaching instructions and cues for enhancing sprint performance. Strength Cond J, 38, 1–11. Bloomquist, K., Langberg, H., Karlsen, S., Madsgaard, S., Boesen, M. & Raastad, T. 2013. Effect of range of motion in heavy load squatting on muscle and tendon adaptations. Eur J Appl Physiol, 113, 2133–2142. Boroujerdi, S. S. & Rahimi, R. 2008. Acute GH and IGF-I responses to short vs. long rest period between sets during forced repetitions resistance training system. South African J Res Sport, Phys Ed Rec, 30, 31–38. Bryanton, M. A., Kennedy, M. D., Carey, J. P. & Chiu, L. Z. F. 2012. Effect of squat depth and barbell load on relative muscular effort in squatting. J Strength Cond Res, 26, 2820–2828. Buresh, R., Berg, K. & French, J. 2009. The effect of resistive exercise rest interval on hormonal response, strength, and hypertrophy with training. J Strength Cond Res, 23, 62–71. Caterisano, A., Moss, R. E., Pellinger, T. K., Woodruff, K., Lewis, V. C., Booth, W. & Khadra, T. 2002. The effect of back squat depth on the EMG activity of 4 superficial hip and thigh muscles. J Strength Cond Res, 16, 428–432. Channell, B. T. & Barfield, J. P. 2008. Effect of Olympic and traditional resistance training on vertical jump improvement in high school boys. J Strength Cond Res, 22, 1522–1527. Chaouachi, A., Hammami, R., Kaabi, S., Chamari, K., Drinkwater, E. J. & Behm, D. G. 2014. Olympic weightlifting and plyometric training with children provides similar or greater performance improvements than traditional resistance training. J Strength Cond Res, 28, 1483–1496. Comfort, P., Allen, M. & Graham-Smith, P. 2011a. Comparisons of peak ground reaction force and rate of force development during
variations of the power clean. J Strength Cond Res, 25, 1235–1239. Comfort, P., Allen, M. & Graham-Smith, P. 2011b. Kinetic comparisons during variations of the power clean. J Strength Cond Res, 25, 3269–3273. Comfort, P. & Kasim, P. 2007. Optimizing squat technique. Strength Cond J, 29, 10–13. Contreras, B., Vigotsky, A. D., Schoenfeld, B. J., Beardsley, C. & Cronin, J. 2016a. A comparison of gluteus maximus, biceps femoris, and vastus lateralis electromyography amplitude in the parallel, full, and front squat variations in resistance-trained females. J Appl Biomech, 32, 16–22. Contreras, B., Vigotsky, A. D., Schoenfeld, B. J., Beardsley, C., McMaster, D. T., Reyneke, J. & Cronin, J. 2016b. Effects of a six-week hip thrust versus front squat resistance training program on performance in adolescent males: a randomized-controlled trial. J Strength Cond Res, Epub ahead of print. Cormie, P., McCaulley, G. O. & McBride, J. M. 2007. Power versus strength-power jump squat training: influence on the load-power relationship. Med Sci Sports Exerc, 39, 996–1003. Cormie, P., McGuigan, M. R. & Newton, R. U. 2010a. Adaptations in athletic performance after ballistic power versus strength training. Med Sci Sports Exerc, 42, 1582–1598. Cormie, P., McGuigan, M. R. & Newton, R. U. 2010b. Changes in the eccentric phase contribute to improved stretch-shorten cycle performance after training. Med Sci Sports Exerc, 42, 1731–1744. de Salles, B. F., Simao, R., Miranda, F., Da Silva Novaes, J., Lemos, A. & Willardson, J. M. 2009. Rest interval between sets in strength training. Sports Med, 39, 765–777. de Salles, B. F., Simão, R., Mirand, H., Bottaro, M., Fontana, F. & Willardson, J. M. 2010. Strength increases in upper and lower body are larger with longer inter-set rest intervals in trained men. J Sci Med Sport, 13, 429–433. DeWeese, B. H., Bellon, C. R., Magrum, E., Taber, C. B. & Suchomel, T. J. 2016. Strengthening the springs. Technique Magazine. Donnelly, D. V., Berg, W. P. & Fiske, D. M. 2006. The effect of the direction of gaze on the kinematics of the squat exercise. J Strength Cond Res, 20, 145–150. Escamilla, R. F., Francisco, A. C., Kayes, A. V., Speer, K. P. & Moorman III, C. T. 2002. An electromyographic analysis of sumo and conventional style deadlifts. Med Sci Sports Exerc, 34, 682–688. Favre, M. & Peterson, M. D. 2012. Teaching the first pull. Strength Cond J, 34, 77–81. Fowles, J. R. & Green, H. J. 2003. Coexistence of potentiation and low-frequency fatigue during voluntary exercise in human skeletal muscle. Can J Physiol Pharmacol, 81, 1092–1100. Fry, A. C., Smith, J. C. & Schilling, B. K. 2003. Effect of knee position on hip and knee torques during the barbell squat. J Strength Cond Res, 17, 629–633. Gilbert, G. & Lees, A. 2005. Changes in the force development characteristics of muscle following repeated maximum force and power exercise. Ergonomics, 48, 1576–1584. Gonzalo-Skok, O., Tous-Fajardo, J., Valero-Campo, C., Berzosa, C., Bataller, A. V., Arjol-Serrano, J. L., Moras, G. & MendezVillanueva, A. 2016. Eccentric overload training in team-sports functional performance: constant bilateral vertical vs. variable unilateral multidirectional movements. Int J Sports Physiol Perform, Epub ahead of print. Gorostiaga, E. M., Navarro-Amézqueta, I., Calbet, J. A. L., Hellsten, Y., Cusso, R., Guerrero, M., Granados, C., González-Izal, M., Ibáñez, J. & Izquierdo, M. 2012. Energy metabolism during repeated sets of leg press exercise leading to failure or not. PloS One, 7, e40621. Gorostiaga, E. M., Navarro-Amézqueta, I., Cusso, R., Hellsten, Y., Calbet, J. A. L., Guerrero, M., Granados, C., González-Izal, M., Ibáñez, J. & Izquierdo, M. 2010. Anaerobic energy expenditure and mechanical efficiency during exhaustive leg press exercise. PloS One, 5, e13486. Gorsuch, J., Long, J., Miller, K., Primeau, K., Rutledge, S., Sossong, A. & Durocher, J. J. 2013. The effect of squat depth on multiarticular muscle activation in collegiate cross-country runners. J Strength Cond Res, 27, 2619–2625. Gouvêa, A. L., Fernandes, I. A., César, E. P., Silva, W. A. B. & Gomes, P. S. C. 2013. The effects of rest intervals on jumping performance: a meta-analysis on post-activation potentiation studies. Journal of Sports Sciences, 31, 459–467. Green, C. M. & Comfort, P. 2007. The affect of grip width on bench press performance and risk of injury. Strength Cond J, 29, 10–14. Gullet, J. C., Tillman, M. D., Gutierrez, G. M. & Chow, J. W. 2009. A biomechanical comparison of back and front squats in healthy trained individuals. J Strength Cond Res, 23, 284–292. Haff, G. G. 2016. Cluster sets - Current methods for introducing variations to training sets. 39th National Strength and Conditioning Association National Conference and Exhibition, New Orleans, LA. Haff, G. G., Hobbs, R. T., Haff, E. E., Sands, W. A., Pierce, K. C. & Stone, M. H. 2008. Cluster training: a novel method for introducing training program variation. Strength Cond J, 30, 67–76. Haff, G. G. & Nimphius, S. 2012. Training principles for power. Strength Cond J, 34, 2–12. Haff, G. G., Whitley, A., McCoy, L. B., O’Bryant, H. S., Kilgore, J. L., Haff, E. E., Pierce, K. & Stone, M. H. 2003. Effects of different set configurations on barbell velocity and displacement during a clean pull. J Strength Cond Res, 17, 95–103. Hamada, T., Sale, D. G., MacDougall, J. D. & Tarnopolsky, M. A. 2000. Postactivation potentiation, fiber type, and twitch contraction time in human knee extensor muscles. J Appl Physiol, 88, 2131–2137. Hardee, J. P., Lawrence, M. M., Utter, A. C., Triplett, N. T., Zwetsloot, K. A. & McBride, J. M. 2012a. Effect of inter-repetition rest on
ratings of perceived exertion during multiple sets of the power clean. Eur J Appl Physiol, 112, 3141–3147. Hardee, J. P., Lawrence, M. M., Zwetsloot, K. A., Triplett, N. T., Utter, A. C. & McBride, J. M. 2013. Effect of cluster set configurations on power clean technique. J Sports Sci, 31, 488–496. Hardee, J. P., Triplett, N. T., Utter, A. C., Zwetsloot, K. A. & McBride, J. M. 2012b. Effect of interrepetition rest on power output in the power clean. J Strength Cond Res, 26, 883–889. Harris, G. R., Stone, M. H., O’Bryant, H. S., Proulx, C. M. & Johnson, R. L. 2000. Short-term performance effects of high power, high force, or combined weight-training methods. Journal of Strength and Conditioning Research, 14, 14–20. Hawley, J. A. 2009. Molecular responses to strength and endurance training: are they incompatible? Appl Physiol Nutr Metab, 34, 355– 361. Hodgson, M., Docherty, D. & Robbins, D. 2005. Post-activation potentiation: underlying physiology and implications for motor performance Sports Med, 35, 585–595. Hoffman, J. R., Cooper, J., Wendell, M. & Kang, J. 2004. Comparison of Olympic vs. traditional power lifting training programs in football players. J Strength Cond Res, 18, 129–135. Hopkins, W. G. 2014. A scale of magnitude for effect statistics. Available: http://sportsci.org/resource/stats/effectmag.html. Hughes, G. & Prescott, S. Effects of footwear on sagittal plane kinematics and centre of pressure excursion during the barbell back squat. In: Calloud, F., Domalain, M. & Monnet, T., eds. XXXIIIrd International Conference on Biomechanics in Sports, June 29–July 3, 2015, Poitiers, France. 612–615. Jo, E., Judelson, D. A., Brown, L. E., Coburn, J. W. & Dabbs, N. C. 2010. Influence of recovery duration after a potentiating stimulus on muscular power in recreationally trained individuals. J Strength Cond Res, 24, 343–347. Komi, P. V. 1986. Training of muscle strength and power: interaction of neuromotoric, hypertrophic, and mechanical factors. Int J Sports Med, 7, S10–S15. Komi, P. V. 2000. Stretch-shortening cycle: a powerful model to study normal and fatigued muscle. J Biomech, 33, 1197–1206. Kraemer, W. J., adams, K., Cafarelli, E., Dudley, G. A., Dooly, C., Feigenbaum, M. S., Fleck, S. J., Franklin, B., Fry, A. C., Hoffman, J. R., Newton, R. U., Potteiger, J., Stone, M. H., Ratamess, N. A. & Triplett-McBride, T. 2002. American College of Sports Medicine position stand. Progression models in resistance training for healthy adults. Med Sci Sports Exerc, 34, 364–380. Kraemer, W. J., Fleck, S. J., Dziados, J. E., Harman, E. A., Marchitelli, L. J., Gordon, S. E., Mello, R., Frykman, P. N., Koziris, L. P. & Triplett, N. T. 1993. Changes in hormonal concentrations after different heavy-resistance exercise protocols in women. J Appl Physiol, 75, 594–604. Kraemer, W. J., Marchitelli, L., Gordon, S. E., Harman, E., Dziados, J. E., Mello, R., Frykman, P., McCurdy, D. & Fleck, S. J. 1990. Hormonal and growth factor responses to heavy resistance exercise protocols. J Appl Physiol, 69, 1442–1450. Lake, J. P. & Lauder, M. A. 2012. Kettlebell swing training improves maximal and explosive strength. J Strength Cond Res, 26, 2228– 2233. Lake, J. P., Lauder, M. A., Smith, N. A. & Shorter, K. A. 2012. A comparison of ballistic and non-ballistic lower-body resistance exercise and the methods used to identify their positive lifting phases. J Appl Biomech, 28, 431–437. Legg, H. S., Glaister, M., Cleather, D. J. & Goodwin, J. E. 2017. The effect of weightlifting shoes on the kinetics and kinematics of the back squat. J Sports Sci, 35, 508–515. Lehman, G. J. 2005. The influence of grip width and forearm pronation/supination on upper-body myoelectric activity during the flat bench press. J Strength Cond Res, 19, 587–591. Leslie, K. L. M. & Comfort, P. 2013. The effect of grip width and hand orientation on muscle activity during pull-ups and the lat pulldown. Strength Cond J, 35, 75–78. Maloney, S. J., Turner, A. N. & Fletcher, I. M. 2014. Ballistic exercise as a pre-activation stimulus: a review of the literature and practical applications. Sports Med, 44, 1347–1359. Mann, J. B., Ivey, P. A. & Sayers, S. P. 2015. Velocity-based training in football. Strength Cond J, 37, 52–57. Masiulis, N., Skurvydas, A., Kamandulis, S., Kudirkaité, J., Sukockas, V., Valys, E., Jurevicˇiené, V. & Kamanduliené, L. 2007. Postactivation potentiation and fatigue of quadriceps muscle after continuous isometric contractions at maximal and submaximal intensities. Ugdymas Küno Kultüra Sportas, 4, 56–63. McCaw, S. T. & Melrose, D. R. 1999. Stance width and bar load effects on leg muscle activity during the parallel squat. Med Sci Sports Exerc, 31, 428–436. McCurdy, K. W., Langford, G. A., Doscher, M. W., Wiley, L. P. & Mallard, K. G. 2005. The effects of short-term unilateral and bilateral lower-body resistance training on measures of strength and power. J Strength Cond Res, 19, 9–15. McCurdy, K. W., O’Kelley, E., Kutz, M., Langford, G., Ernest, J. & Torres, M. 2010. Comparison of lower extremity EMG between the 2-leg squat and modified single-leg squat in female athletes. J Sport Rehabil, 19, 57–70. Milanese, C., Cavedon, V., Corte, S. & Agostini, T. 2017. The effects of two different correction strategies on the snatch technique in weightlifting. J Sports Sci, 35, 476–483. Newton, R. U., Kraemer, W. J., Häkkinen, K., Humphries, B. & Murphy, A. J. 1996. Kinematics, kinetics, and muscle activation during explosive upper body movements. J Appl Biomech, 12, 31–43. Ninos, J. C., Irrgang, J. J., Burdett, R. & Weiss, J. R. 1997. Electromyographic analysis of the squat performed in self-selected lower extremity neutral rotation and 30 of lower extremity turn-out from the self-selected neutral position. J Orthop Sports Phys Ther, 25,
307–315. Oliver, J. M., Jagim, A. R., Sanchez, A. C., Mardock, M. A., Kelly, K. A., Meredith, H. J., Smith, G. L., Greenwood, M., Parker, J. L. & Riechman, S. E. 2013. Greater gains in strength and power with intraset rest intervals in hypertrophic training. J Strength Cond Res, 27, 3116–3131. Oliver, J. M., Kreutzer, A., Jenke, S. C., Phillips, M. D., Mitchell, J. B. & Jones, M. T. 2015. Acute response to cluster sets in trained and untrained men. Eur J Appl Physiol, 115, 2383–2393. Oliver, J. M., Kreutzer, A., Jenke, S. C., Phillips, M. D., Mitchell, J. B. & Jones, M. T. 2016. Velocity drives greater power observed during back squat using cluster sets. J Strength Cond Res, 30, 235–243. Otto III, W. H., Coburn, J. W., Brown, L. E. & Spiering, B. A. 2012. Effects of weightlifting vs. kettlebell training on vertical jump, strength, and body composition. J Strength Cond Res, 26, 1199–1202. Painter, K. B., Haff, G. G., Ramsay, M. W., McBride, J., Triplett, T., Sands, W. A., Lamont, H. S., Stone, M. E. & Stone, M. H. 2012. Strength gains: block versus daily undulating periodization weight training among track and field athletes. Int J Sports Physiol Perform, 7, 161–169. Pereira, G. R., Leporace, G., Das Virgens Chagas, D., Furtado, L. F. L., Praxedes, J. & Batista, L. A. 2010. Influence of hip external rotation on hip adductor and rectus femoris myoelectric activity during a dynamic parallel squat. J Strength Cond Res, 24, 2749–2754. Pincivero, D. M., Lephart, S. M. & Karunakara, R. G. 1997. Effects of rest interval on isokinetic strength and functional performance after short-term high intensity training. Br J Sports Med, 31, 229–234. Rahimi, R., Ghaderi, M., Mirzaei, B. & Faraji, H. 2010a. Acute IGF-1, cortisol and creatine kinase responses to very short rest intervals between sets during resistance exercise to failure in men. World Appl Sci J, 8, 1287–1293. Rahimi, R., Ghaderi, M., Mirzael, B., Ghaeni, S., Faraji, H., Vatani, D. S. & Rahmani-Nia, F. 2010b. Effects of very short rest periods on immunoglobulin A and cortisol responses to resistance exercise in men. J Hum Sport Exerc, 5, 146–157. Rahimi, R., Rohani, H. & Ebrahimi, M. 2011. Effects of very short rest periods on testosterone to cortisol ratio during heavy resistance exercise in men. Apunt Med l’Esport, 46, 145–149. Rassier, D. E. & MacIntosh, B. R. 2000. Coexistence of potentiation and fatigue in skeletal muscle. Braz J Med Biol Res, 33, 499–508. Rhea, M. R., Kenn, J. G., Peterson, M. D., Massey, D., Simão, R., Marin, P. J., Favero, M., Cardozo, D. & Krein, D. 2016. Joint-angle specific strength adaptations influence improvements in power in highly trained athletes. Hum Mov, 17, 43–49. Robinson, J. M., Stone, M. H., Johnson, R. L., Penland, C. M., Warren, B. J. & Lewis, R. D. 1995. Effects of different weight training exercise/rest intervals on strength, power, and high intensity exercise endurance. J Strength Cond Res, 9, 216–221. Sale, D. G. 2002. Postactivation potentiation: role in human performance. Exerc Sport Sci Rev, 30, 138–143. Sato, K., Fortenbaugh, D. & Hydock, D. S. 2012. Kinematic changes using weightlifting shoes on barbell back squat. J Strength Cond Res, 26, 28–33. Schoenfeld, B. J., Pope, Z. K., Benik, F. M., Hester, G. M., Sellers, J., Nooner, J. L., Schnaiter, J. A., Bond-Williams, K. E., Carter, A. S. & Ross, C. L. 2016. Longer inter-set rest periods enhance muscle strength and hypertrophy in resistance-trained men. J Strength Cond Res, 30, 1805–1812. Seitz, L. B., De Villareal, E. S. S. & Haff, G. G. 2014. The temporal profile of postactivation potentiation is related to strength level. J Strength Cond Res, 28, 706–715. Sheppard, J. M. & Triplett, N. T. 2016. Program design for resistance training. In: Haff, G. G. & Triplett, N. T. (eds.) Essentials of Strength Training and Conditioning. 4th ed. Champaign, IL: Human Kinetics. Soriano, M. A., Suchomel, T. J. & Marin, P. J. 2016. The optimal load for improving maximal power production during upper-body exercises: a meta-analysis. Sports Med, Epub ahead of print. Speirs, D. E., Bennett, M. A., Finn, C. V. & Turner, A. P. 2016. Unilateral vs. bilateral squat training for strength, sprints, and agility in academy rugby players. J Strength Cond Res, 30, 386–392. Stone, M. H., Sands, W. A., Pierce, K. C., Ramsey, M. W. & Haff, G. G. 2008. Power and power potentiation among strength-power athletes: preliminary study. Int J Sports Physiol Perform, 3, 55–67. Suchomel, T. J., Comfort, P. & Lake, J. P. 2017. Enhancing the force-velocity profile of athletes using weightlifting derivatives. Strength Cond J, Epub ahead of print. Suchomel, T. J., Lamont, H. S. & Moir, G. L. 2016a. Understanding vertical jump potentiation: a deterministic model. Sports Med, 46, 809–828. Suchomel, T. J., Nimphius, S. & Stone, M. H. 2016b. The importance of muscular strength in athletic performance. Sports Med, 46, 1419–1449. Suchomel, T. J., Sato, K., DeWeese, B. H., Ebben, W. P. & Stone, M. H. 2016c. Potentiation effects of half-squats performed in a ballistic or non-ballistic manner. J Strength Cond Res, 30, 1652–1660. Suchomel, T. J., Sato, K., DeWeese, B. H., Ebben, W. P. & Stone, M. H. 2016d. Potentiation following ballistic and non-ballistic complexes: the effect of strength level. J Strength Cond Res, 30, 1825–1833. Swinton, P. A., Stewart, A., Agouris, I., Keogh, J. W. & Lloyd, R. 2011. A biomechanical analysis of straight and hexagonal barbell deadlifts using submaximal loads. J Strength Cond Res, 25, 2000–2009. Swinton, P. A., Stewart, A. D., Lloyd, R., Agouris, I. & Keogh, J. W. 2012. Effect of load positioning on the kinematics and kinetics of weighted vertical jumps. J Strength Cond Res, 26, 906–913.
Teo, S. Y., Newton, M. J., Newton, R. U., Dempsey, A. R. & Fairchild, T. J. 2016. Comparing the effectiveness of a short-term vertical jump versus weightlifting program on athletic power development. J Strength Cond Res, 30, 2741–2748. Tillin, N. A. & Bishop, D. 2009. Factors modulating post-activation potentiation and its effect on performance of subsequent explosive activities. Sports Med, 39, 147–166. Tricoli, V., Lamas, L., Carnevale, R. & Ugrinowitsch, C. 2005. Short-term effects on lower-body functional power development: weightlifting vs. vertical jump training programs. J Strength Cond Res, 19, 433–437. Tufano, J. J., Brown, L. E. & Haff, G. G. 2016a. Theoretical and practical aspects of different cluster set structures: a systematic review. J Strength Cond Res, Epub ahead of print. Tufano, J. J., Conlon, J. A., Nimphius, S., Brown, L. E., Banyard, H. G., Williamson, B. D., Bishop, L. G., Hopper, A. J. & Haff, G. G. 2016b. Cluster sets permit greater mechanical stress without decreasing relative velocity. Int J Sports Physiol Perform, Epub ahead of print, 1–24. Tufano, J. J., Conlon, J. A., Nimphius, S., Brown, L. E., Seitz, L. B., Williamson, B. D. & Haff, G. G. 2016c. Cluster sets maintain velocity and power during high-volume back squats. Int J Sports Physiol Perform, 11, 885–892. van Cutsem, M., Duchateau, J. & Hainaut, K. 1998. Changes in single motor unit behaviour contribute to the increase in contraction speed after dynamic training in humans. J Physiol, 513, 295–305. Vossen, J. F., Kraemer, J. E., Burke, D. G. & Vossen, D. P. 2000. Comparison of dynamic push-up training and plyometric push-up training on upper-body power and strength. J Strength Cond Res, 14, 248–253. Willardson, J. M. & Burkett, L. N. 2005. A comparison of 3 different rest intervals on the exercise volume completed during a workout. J Strength Cond Res, 19, 23–26. Willardson, J. M. & Burkett, L. N. 2006. The effect of rest interval length on bench press performance with heavy vs. light loads. J Strength Cond Res, 20, 396–399. Willardson, J. M. & Burkett, L. N. 2008. The effect of different rest intervals between sets on volume components and strength gains. J Strength Cond Res, 22, 146–152. Wilson, J. M., Duncan, N. M., Marin, P. J., Brown, L. E., Loenneke, J. P., Wilson, S. M., Jo, E., Lowery, R. P. & Ugrinowitsch, C. 2013. Meta-analysis of postactivation potentiation and power: effects of conditioning activity, volume, gender, rest periods, and training status. J Strength Cond Res, 27, 854–859. Winchester, J. B., Porter, J. M. & McBride, J. M. 2009. Changes in bar path kinematics and kinetics through use of summary feedback in power snatch training. J Strength Cond Res, 23, 444–454. Wulf, G. 2007. Attention and Motor Skill Learning, Champaign, IL: Human Kinetics. Yavuz, H. U., Erdag˘, D., Amca, A. M. & Aritan, S. 2015. Kinematic and EMG activities during front and back squat variations in maximum loads. J Sports Sci, 33, 1058–1066. Zatsiorsky, V. 1995. Science and Practice of Strength Training, Champaign, IL: Human Kinetics.
CHAPTER 15
Weightlifting for sports performance Timothy J. Suchomel and Paul Comfort INTRODUCTION This chapter should provide the reader with information regarding the existing literature on weightlifting movements and the theoretical rationale as to why they are used in athletes’ training programs (Section 1). Section 2 will then provide practical examples to allow the reader to implement weightlifting movements and their derivatives using an evidence-based approach. The term ‘weightlifting’ refers to the sport in which competitors perform the snatch and the clean and jerk, attempting to lift the maximum amount of weight. Weightlifting in this sense is different from the general term ‘resistance training’, which refers to all other forms of training in which an individual is moving against a resistive load. However, the weightlifting movements (i.e., snatch, clean, and jerk) and their derivatives may also be used within resistance training programs in order to train the strength and power characteristics of athletes who are not competing in the sport of weightlifting.
SECTION 1 THE EFFECTIVENESS OF WEIGHTLIFTING MOVEMENTS While both weightlifting and other forms of resistance training may improve an athlete’s lower body strength and power, research suggests that weightlifting movements and their derivatives may provide superior training effects compared to other methods (Hoffman et al., 2004; Tricoli et al., 2005; Otto III et al., 2012; Teo et al., 2016; Arabatzi and Kellis, 2012; Chaouachi et al., 2014; Channell and Barfield, 2008). These findings are attributed to two primary reasons, movement specificity and the overload that the athlete can be subjected to.
Movement specificity The most common movement in sports is the coordinated extension of the hip, knee, and ankle joints (plantar flexion), termed ‘triple extension’. Jumping, sprinting, and change of direction tasks require the completion of the triple extension movement. A similar coordinated triple extension movement takes place during the second pull phase of weightlifting movements (see ‘Weightlifting Technique’), which allows these movements to transfer to sports performance. Due to the similarities between the triple extension of sports movements and the second pull of weightlifting movements, it should come as no surprise that better performance of weightlifting movements is related to better performance during sprinting and jumping (Carlock et al., 2004; Hori et al., 2008).
Overload Weightlifting exercises are coordinated movements in which an athlete moves a moderate-heavy load with ballistic intent. While other resistance training methods may be used to train lower body strength and power (e.g., free weights, plyometrics, kettlebells, etc.), these methods are typically not performed in the same manner as weightlifting movements. For example, training with the back squat may produce high forces but with less velocity, whereas plyometric exercise may produce high velocities but with less force. This is supported by previous literature that has demonstrated that the power outputs of the snatch, and clean and jerk were superior to core exercises such as the squat and deadlift (Garhammer, 1980; Garhammer, 1991). Additional literature indicated that standard resistance training exercises resulted in reduced force production (i.e., deceleration) during as much as 45% of the range of motion (Newton et al., 1996).
WEIGHTLIFTING TECHNIQUE During the snatch in a weightlifting competition, the lifter must lift the barbell from the floor to an overhead position, receiving the weight with the arms fully extended, in one continuous motion (Figures 15.2–15.7). The clean is characterised by lifting the barbell from the floor to a resting position across the front of the lifter’s shoulders (Figures 15.2–15.7). As a continuation of the clean, the jerk is completed by lifting the barbell from the shoulders to an overhead position, receiving the weight with the arms fully extended (Figures 15.8–15.13). The technique of each lift is described
below.
Snatch/clean first pull The first pull refers to the initial movement of the barbell from the floor to a position just above the knee. The starting position of each athlete will be based on their anthropometric characteristics such as their height, body mass, and somatotype as well as their range of motion and flexibility. Athletes should position themselves so that they are centered on the bar with their feet flat and positioned about hip-width apart and the barbell positioned over the middle of their feet. The recommended grip to use with weightlifting movements is the hook grip (Figure 15.1). Whether performing a clean or snatch variation, the hands may be positioned more closely together or farther apart, respectively. The elbows should be pointed outward to prevent excess elbow flexion that may hinder the transfer of force to the barbell. The barbell should almost be in contact with the athlete’s lower leg, their knees should be in line with their feet, and their hips should be slightly higher than their knees. The position of the upper body should include extended arms, shoulders in front of the bar, an elevated chest, shoulder blades pulled back, and a slightly arched (natural curve) or flat back. Finally, the athlete’s head should be neutral with their eyes looking forward (Figure 15.2).
FIGURE 15.1
Hook grip – thumb wraps under the bar with the fingers wrapped around the thumb and bar.
FIGURE 15.2
Starting position for the snatch (left) and clean (right).
FIGURE 15.3
The end of the first pull for the snatch (left) and clean (right).
After reaching the correct starting position, athletes should inhale to increase their intra-abdominal pressure and remove any slack that may still exist within their arms. The athlete should then begin the lift by pushing into the ground through the centre of their feet while elevating their hips and shoulders at the same rate and maintaining the angle of their back, shoulders over the barbell, and fully extended arms. While elevating the barbell, the knees move backward while the lower legs reach a near vertical position, resulting in a shift of the centre of pressure from the mid-foot to the heels (Figure 15.3).
Snatch/clean transition The transition phase refers to the movement of the barbell from a position just above the knee to the mid-thigh ‘power’ position in preparation for the second pull. An effective transition phase requires the athlete to re-bend their knees to a position in front of the barbell as it moves from the knee to the mid-thigh shifting the centre of pressure from the heels to the mid-foot. The athlete’s hips should move over their ankles, resulting in a vertical torso, extended arms, and knees bent to approximately 125– 135° (Figure 15.4).
FIGURE 15.4
Mid-thigh (power) position side view for the snatch (left) and oblique view for the clean (right).
Snatch/clean second pull Upon reaching the mid-thigh position, athletes perform the second pull movement by pushing into the ground and rapidly extending their hips, knees, and ankles (plantar flexion) and shrugging their shoulders (Figure 15.5). This movement causes the barbell to rise vertically and results in the greatest force, rate of force development (RFD), velocity, and power (Enoka, 1979; Garhammer, 1980; Garhammer, 1982). Athletes should keep their arms extended for as long as possible during the second pull to ensure maximum force transfer to the barbell. However, the athlete’s arms will bend due to the upward momentum of the barbell and the failure to elevate the torso any higher. It should be noted that while the second pull results in the completion of certain weightlifting derivatives (see Weightlifting Pulling Derivatives below), others require the athlete to catch or receive the weight.
Snatch/clean catch Following the second pull, a snatch variation requires the athlete to rotate their hands and elbows around the barbell, moving from a vertical position above the barbell into a position below the barbell. Simultaneously, the athlete will flex their hips, knees, and ankles (dorsiflexion), drop and pull themselves into an overhead squat position while their feet may move slightly outward to a more stable position. The athlete should receive the barbell in an overhead squat position with their elbows locked out at the same time as their feet land flat on the ground in the desired squat depth while maintaining an upright torso and normal lumbar curve (Figure 15.6). Figure 15.7 displays a power snatch catch variation.
FIGURE 15.5
Second pull of the snatch (left) and clean (right).
A clean variation requires the athlete to rotate their elbows around the barbell from a position above the barbell into a horizontal position in front of the barbell. The athlete will flex their hips, knees, and ankles (dorsiflexion), drop and pull themselves into a front squat position while their feet may move slightly outward to a more stable position. The athlete should receive the barbell in a front squat position on the front of their shoulders with their elbows pointed forward, their upper arm nearly parallel with the ground, and a relaxed grip at the same time their feet land flat on the ground in the desired squat depth while maintaining an upright torso and normal lumbar curve (Figure 15.6). Figure 15.7 displays a power clean catch variation.
FIGURE 15.6
Catch position of the snatch (left) and clean (right).
FIGURE 15.7
Power snatch (left) and power clean (right) catch positions.
Snatch/clean recovery After becoming stable in the desired squat depth for snatch and clean variations, the recovery phase requires the athlete to return to a standing position maintaining the overhead or front squat position (Figure 15.8). The athlete should maintain an upright torso while extending their hips and knees to return to a standing position.
Jerk starting position As a continuation of the clean exercise, or from a rack or training blocks, the athlete should start in standing position with their feet approximately shoulder-width apart, an upright torso, and the barbell racked across the front of their shoulders with their upper arms nearly parallel to the floor. The athlete’s eyes should be forward and their chin tucked (Figure 15.9). An alternative variation would allow the athletes to start with the barbell resting on their upper back, similar to a back squat.
Jerk dip Before the athlete begins the lift, the athlete should take a deep breath in order to elevate the rib cage,
brace the other trunk musculature, and create intra-abdominal pressure. Following the breath, the athlete will simultaneously flex their hip and knee joints and descend to a quarter-squat position where the knees are flexed to approximately 125–135° (Figure 15.10). As the athlete descends, they should keep their elbows elevated so as to not let the barbell move away from their centre of mass. This common error may result in the athlete pushing the barbell more forward rather than vertically during the drive phase. The dip phase should be completed fairly rapidly without pausing in the bottom position in order to receive the greatest stretch-shortening cycle benefits (i.e., greater use of stored elastic energy and less force dissipation).
FIGURE 15.8
Recovery position for the snatch (left) and clean (right).
FIGURE 15.9
Starting position for a jerk variation.
FIGURE 15.10 Completion of the dip phase of the jerk.
FIGURE 15.11
The drive phase of the jerk.
FIGURE 15.12 Split jerk receiving position.
Jerk drive Upon reaching the bottom of the dip phase, the athlete should immediately, without pausing, rapidly extend their hip, knee, and ankle joints in order to drive the barbell up vertically (Figure 15.11). The triple extension movement should cause the barbell to elevate off the athlete’s shoulders and pass in front of their face. It is important to remind the athlete to tuck their chin during the drive phase in order to prevent possible injury. As the barbell continues to elevate, the athlete should grasp it with an overhand grip. Simultaneously, the athlete’s feet are either beginning to split forward and backward (split jerk) or laterally (power jerk). The athlete’s torso should remain upright and rigid in preparation to receive the load overhead.
Jerk receiving positions Depending on the variation used, split jerk or power jerk, the athlete’s feet will continue to split forward and backward or laterally. Coaches should note that the splitting of the feet should not be a jumping motion, but rather a continuation of the drive phase. During the split jerk (Figure 15.12), the athlete should ‘jab’ the front foot forward so that it is flat on the ground with the pressure on the heel.
The athlete’s front knee should flex and remain in line with their toes. Simultaneously, the athlete’s back foot moves backward and is planted on the ball of their foot with their heel off the ground. The back leg should be slightly bent to allow for the absorption of force as the load is received overhead. As the athlete splits their legs, they should also continue the drive phase by pushing the barbell vertically and receiving it overhead with their elbows in a locked position. The barbell should be received with a braced torso in a position where the barbell is directly above the back of the head (Figure 15.12).
FIGURE 15.13 Power jerk receiving position.
FIGURE 15.14 Jerk recovery.
A power jerk variation follows a similar sequence of movements through the drive phase. Instead of splitting the feet forward and backward, the athlete moves their feet slightly laterally and flexes their hips and knees into a quarter-squat position. At this point, the athlete continues to drive the barbell upward before receiving in the previously described overhead position (Figure 15.13).
Jerk recovery In order to recover from a split jerk position, the athlete should first step backwards with their front foot until it is close to the body and then step forward with the back foot until the legs are together all while maintaining an upright posture and the barbell held overhead with locked arms (Figure 15.14). The movements of the legs should be completed in this order to allow for the centre of mass to be
moved backwards against a braced back leg rather than creating forward momentum by moving towards the front leg. Once in a stable receiving position during the power jerk, the athlete should extend their hips and knees while maintaining an upright torso and holding the barbell overhead with locked arms to return to a standing position (Figure 15.14).
WEIGHTLIFTING DERIVATIVES As mentioned above, the primary weightlifting movements are the snatch, clean, and jerk. However, it should be noted that there are a number of partial lifts (i.e., weightlifting derivatives) that exclude part of the full snatch, clean, or jerk movements. Despite removing an aspect of the lift, weightlifting derivatives may also be effectively implemented into resistance training programs for athletes. It should be noted that weightlifting derivatives may be further sub-divided into weightlifting catching and pulling derivatives.
Weightlifting catching derivatives Practitioners often refer to weightlifting derivatives that include catching the load overhead as described during a snatch derivative or across the shoulders as performed during a clean derivative. In addition to producing high power outputs during the triple extension movement, it is generally believed that the catch phase will train an athlete to decelerate an external load. The ability to decelerate a load is an important characteristic for athletes in sports such as rugby, American football, and wrestling, and thus, the benefits of a proper catch phase should not be discounted. Previous research has indicated that weightlifting catching derivatives may be used as a training tool to improve landing characteristics (Moolyk et al., 2013). As with any exercise, the athlete’s technique is vital to receive the optimal training stimulus and prevent injury. This is especially true when it comes to weightlifting movements and their derivatives as they are highly complex with regard to technique. A number of studies have examined factors that may influence the proper completion of the snatch and clean and jerk exercises. Researchers have examined the effect that loading has on snatch and clean and jerk technique (Häkkinen et al., 1984), snatch technique of weightlifters at different levels (Harbili and Alptekin, 2014; Schilling et al., 2002; Kauhanen et al., 1984), technique changes following feedback (Winchester et al., 2009), and the technique differences between successful and unsuccessful snatch attempts (Gourgoulis et al., 2009; Stone et al., 1998). These findings are beneficial in that they may help improve coaching cues and the focus on critical aspects of each lift. The most common snatch and clean derivatives prescribed are the power clean/snatch and hang power clean/snatch. Thus, in an attempt to aid practitioners and their programming decisions, researchers have examined these exercises by attempting to find the load that produces the greatest magnitude of power (i.e., the optimal load). This research has indicated that loads ranging from 70– 80% one repetition maximum (1RM) may provide the optimal training load for the power clean (Comfort et al., 2012a) and hang power clean (Kilduff et al., 2007; Kawamori et al., 2005). Interestingly, a paucity of research has examined the optimal training load for snatch catching derivatives. However, the information presented within the literature surrounding the optimal training loads of weightlifting catching derivatives is important for practitioners when it comes to prescribing
loads during various training phases. However, practitioners should consider the sport/event of their athlete(s) as the optimal load may be specific to the system (athlete and load), barbell, or joint (McBride et al., 2011). Thus, practitioners should determine which magnitude of power is specific to the athlete’s sport/event. For example, power applied to the barbell is essential for weightlifters, whereas power applied to the system is arguably more important in terms of assessing the development of lower body power. A recent review discussed optimal loading ranges for lower body exercises and concluded that a range of loads should be prescribed when training for maximal power output (Soriano et al., 2015). Additional literature supports this notion (Haff and Nimphius, 2012). A third aspect of the extant literature focuses on different cluster set configurations when it comes to implementing weightlifting catching derivatives. The results of these studies indicate that the use of cluster sets offset the increase in perceived effort (Hardee et al., 2012a), allowed for technique to be maintained (Hardee et al., 2013), and also allowed power output to be maintained throughout the set (Hardee et al., 2012b). From a practical standpoint, it appears that 20–40 seconds of inter-repetition rest may allow the athlete to experience a better training stimulus when training with the clean derivatives.
Weightlifting pulling derivatives Weightlifting pulling derivatives, as the name suggests, are weightlifting derivatives that remove the catch phase and finish with the completion of the second pull (Figure 15.5). Examples of weightlifting pulling derivatives discussed within the literature include the clean/snatch mid-thigh pull, pull from the knee, pull from the floor, countermovement shrug, hang high pull, and jump shrug (Suchomel et al., 2017a). Some of the benefits of the above derivatives include decreased exercise complexity regarding technique, a potential decreased learning and teaching time for the movements, a potential reduced impact on specific joints, and a greater ability to overload the triple extension movement (Suchomel et al., 2015b). Due to the number of benefits that may enhance the abilities of athletes, research has examined weightlifting pulling derivatives in several capacities including comparisons with weightlifting catching derivatives, loading effects, and different set configurations. Results of previous research have indicated that weightlifting pulling derivatives may produce a comparable (Comfort et al., 2011b, 2011a) or superior (Suchomel and Sole, 2017; Suchomel et al., 2014b; Kipp et al., 2016) training stimulus compared to weightlifting catching derivatives with regard to peak force, velocity, power, RFD, and impulse. Further research indicated that the load absorption demands (work, mean force, duration) of weightlifting pulling derivatives are similar or greater compared to weightlifting catching derivatives (Suchomel et al., 2017b; Comfort et al., 2016). It should be noted that the previous studies are cross-sectional studies, and thus, further research is warranted to determine if longitudinal training with catching or pulling derivatives would produce different results. However, it is clear that practitioners must consider the potential benefits of using weightlifting pulling derivatives when it comes to enhancing the force production characteristics of their athletes. Similar to weightlifting catching derivatives, much of the research that focuses on weightlifting pulling derivatives has examined the effect that the external load has on various kinetic and kinematic variables. Through examining different loads, sport scientists and practitioners can determine which loads provide the optimal training stimulus for athletes within the context of each exercise. Furthermore, these findings may then be applied within resistance training programs. For example, the goals of maximal strength and absolute strength training blocks are to enhance the maximal force
production capacity of the athlete and to begin the initial stages of enhancing their RFD characteristics against heavy external loads. Thus, weightlifting pulling derivatives that allow for the use of heavier training loads may aid in the development of the desired characteristics. Previous research has demonstrated that the mid-thigh pull (Comfort et al., 2015; Comfort et al., 2012b) and pull from the floor (Haff et al., 2003) may use loads in excess of an athlete’s 1RM power clean because these derivatives do not require athletes to drop under the barbell and catch the load. Specifically, practitioners may prescribe loads up to approximately 120–140% of their 1RM power clean, as long as proper technique is maintained. Based on these findings, it is clear that weightlifting pulling derivatives may enhance an athlete’s force production characteristics. In fact, implementing the mid-thigh pull and pull from the floor may result in force production gains that may not occur if the practitioner only implements weightlifting catching derivatives as the latter exercises cannot exceed loads beyond their 1RM. Another example would be selecting exercises that maximise power production during speedstrength training blocks. While high force production is emphasised during maximal strength and absolute strength training blocks, the goals of a speed-strength training block are to peak the RFD and power characteristics of athletes prior to competition. Thus, weightlifting pulling derivatives that are the most ballistic in nature may be useful exercises that may aid in the development of these characteristics. Previous research has examined the effect that load has on the jump shrug (Suchomel et al., 2013) and hang high pull (Suchomel et al., 2015a). The results of these loading studies indicated that the lightest loads examined (i.e., 30 and 45% of 1RM hang power clean) produced the greatest magnitudes of velocity and power. In contrast to exercises such as the mid-thigh pull and pull from the floor, it is clear that the jump shrug and hang high pull may fall on the opposite end of the loading spectrum, but may still be useful during certain phases of training (Suchomel et al., 2017a). A third area that is lacking in depth for weightlifting pulling derivatives is research that examines different set configurations. For example, the aforementioned studies may provide the practitioner with the choice of exercise and the potential loads that coincide as an effective training stimulus, however, only one study to date has examined different set configurations (traditional, undulating, and cluster) when performing a weightlifting pulling derivative (Haff et al., 2003). The results of this study indicated that the use of a cluster set may result in greater barbell velocity and displacement during the clean pull from the floor compared to a traditional set. From a practical standpoint, this type of information is crucial as it may alter the training stimulus an athlete experiences, namely the quality of work. However, further research is needed in this area before concrete conclusions can be drawn.
SECTION 2 – PRACTICAL APPLICATIONS DEVELOPING AN ATHLETE’S FORCE-VELOCITY PROFILE As described in Chapter 2, one of the primary goals of a strength and conditioning practitioner is to develop the force-velocity profile of their athletes in order to enhance important force production characteristics such as impulse, RFD, and power. Haff and Nimphius (2012) indicated that the most effective way to develop an athlete’s force-velocity profile is through the use of training methods that will develop both the force and velocity ends of the spectrum. While this process can be completed using different set and repetition schemes, warm-up and warm-down sets, and various intensities during core exercises (squat, bench press, etc.), a sequenced progression of weightlifting derivatives may also develop the entire force-velocity profile of an athlete (Suchomel et al., 2017a). Figure 15.15 displays the theoretical force-velocity relationship specific to weightlifting derivatives.
FIGURE 15.15 Theoretical force-velocity (power) curve with respect to weightlifting derivatives; modified from Suchomel et al. (2017a). 1RM = one repetition maximum, HPC = hang power clean, PC = power clean.
The previously discussed literature supports the notion that weightlifting derivatives such as the midthigh pull, countermovement shrug, pull from the knee, and pull from the floor may all be used to develop high force production characteristics due to the decreased displacement of the load during each movement. On the opposite end of the force-velocity curve are weightlifting derivatives that are characterised by higher velocities. The jump shrug, hang high pull, mid-thigh clean/snatch, and
countermovement (hang) clean/snatch are weightlifting derivatives that are highly ballistic and are typically programmed with low-moderate loads. While the placement of derivatives within Figure 15.15 is supported by evidence, it should be noted that the load prescribed may influence the position of each exercise on the force-velocity curve. For example, while the mid-thigh pull enables athletes to use the heaviest loads (i.e., 140% of 1RM power clean), power production and velocity were maximised with the lightest load (i.e., 40% of 1RM power clean) (Comfort et al., 2015, Comfort et al., 2012b). (Please see Table 15.1 on pp. 267–269.) As discussed in Chapter 8, previous literature suggests that a sequenced progression of training phases promotes the optimal development of an athlete’s force-velocity profile (Minetti, 2002; Zamparo et al., 2002; Stone et al., 1982). Briefly, increases in work capacity and muscle crosssectional area produced during a strength-endurance (hypertrophy) phase enhance an athlete’s ability to increase their muscular strength. From here, increases in muscular strength will then enhance an athlete’s potential to improve their RFD and power characteristics. A similar approach can be taken when prescribing weightlifting derivatives because certain lifts place greater emphasis on either force or velocity. Thus, specific weightlifting catching and pulling derivatives may be prescribed during resistance training phases in order to meet the goals of each phase and develop the forcevelocity profile of the athlete. The following will discuss the implementation of weightlifting derivatives into various resistance training phases to promote the optimal development of an athlete’s force-velocity profile.
Strength-endurance The strength-endurance phase is characterised by a high volume of repetitions (usually 8–12) in exercises that use moderately heavy loads (60–70% 1RM). The purpose of this phase is to increase the athlete’s work capacity, stimulate increases in muscle cross-sectional area, and refine exercise technique for subsequent training phases. Regarding the use of weightlifting derivatives within this phase, it is suggested that practitioners implement the clean/snatch pull from the floor, pull to the knee, and clean grip shoulder shrug for several reasons. First, the suggested derivatives serve as foundational exercises that enable the progression to more complex weightlifting movements. The inability to perform these exercises may lead to improper exercise technique of more complex derivatives, potentially impacting the training stimulus. Second, the clean/snatch pull from the floor enables athletes to overload the triple extension movement without experiencing the additional stress and complexity of performing the catch phase every repetition as fatigue develops. While the catch phase of certain weightlifting derivatives may enable the athlete to develop additional performance characteristics as mentioned above, the high volume experienced during the strength-endurance phase may lead to a deterioration in form due to acute fatigue. Moreover, a decline in technique may alter catch phase mechanics and increase the likelihood of injury or compression stress. Finally, the suggested derivatives enable the development of important lower and upper body musculature that will be used to enhance the force-velocity profile during later training phases in tandem with exercises such as squatting, pressing, and pulling movements. It should be noted that the athletic population may dictate which weightlifting movements are prescribed in a strength-endurance training block. For example, the clean/snatch pull from the floor may only be implemented with an athletic population whose technique is more stable and resilient to fatigue. Practitioners may also consider prescribing cluster sets of either two or five repetitions for the clean/snatch pull from the floor due to the high volume within the strength-endurance phase. As
discussed in Chapter 14, the use of cluster sets may enable the athlete to maintain their technique, force production, and power output throughout each set leading to high quality work, enhanced work capacity, and force production adaptations with a high volume of repetitions. Moreover, the interrepetition rest interval may allow the coach to provide additional feedback to the athlete.
Maximal strength A maximal strength phase is used to increase an athlete’s force production capacity using sets of four to six repetitions and moderately heavy to heavy loads (i.e., 80–90% 1RM, although potentially slightly higher with pulling derivatives). During this phase, practitioners should shift their focus to exercises that emphasise force production and enable the use of heavier loads. With this in mind, a limitation to weightlifting catching derivatives is that practitioners cannot prescribe loads greater than the athlete’s 1RM. This however, is not the case for weightlifting pulling derivatives as exercises such as the clean/snatch pull from the floor, pull from the knee, and mid-thigh pull allow for loads greater than the athlete’s 1RM to be used due to the elimination of the catch phase and decreased displacement of the load. The use of these exercises combined with heavier loads will emphasise force production and train the high force portion of the force-velocity curve.
Absolute strength Similar to the maximal strength phase, the goals of the absolute strength phase are to enhance the athlete’s low repetition (two to three) force production (both magnitude and rate) characteristics using near maximal loads (90–95% 1RM or potentially as high as 120–140% 1RM with pulling derivatives). While the same exercises from the maximal strength phase may be prescribed to retain the athlete’s capacity for high force production, additional derivatives that include a strength-speed component should be introduced to begin the enhancement of RFD. These exercises might include the hang power clean/snatch (Suchomel et al., 2014a), power clean/snatch, mid-thigh clean/snatch (Comfort et al., 2011b, 2011a), and the full clean and snatch. The combination of high force movements and introducing high velocity movements will ultimately contribute to the athlete’s ability to further develop impulse, RFD, and power characteristics.
Strength-speed The primary goals of the strength-speed phase are to further increase RFD and power, while also maintaining or potentially increasing the athlete’s strength. Because previous literature has indicated that RFD and power are two of the most important characteristics regarding an athlete’s performance (Stone et al., 2002; Morrissey et al., 1995), it is important to prepare the athlete to maximise these adaptations using the previously discussed training phases. Based on the phasic progression of resistance training phases, increases in muscular strength (Suchomel et al., 2016b) and RFD (Taber et al., 2016) from the previous training phases should, in theory, enhance the athlete’s ability to augment their power characteristics. Regarding the programming of weightlifting derivatives during the strength-speed phase, RFD and power characteristics may be enhanced using a combination of heavy and light loads. However, the emphasis within this phase is to move relatively heavy loads quickly in order to enhance RFD characteristics. Thus, the mid-thigh clean/snatch, countermovement clean/snatch, and power
clean/snatch from the knee (Suchomel et al., 2016a) may be used to develop the high velocity portion of the force-velocity curve, while the power clean, clean/snatch pulls from the floor, knee, and midthigh may develop the high force end of the force-velocity curve.
Speed-strength The goals of the speed-strength phase are to produce peak adaptations in RFD and power prior to competition. In order to peak these abilities, a wide variety of weightlifting derivatives may be prescribed. Many of the previously described derivatives may be prescribed; however, the speed at which the movement is performed, and therefore the load, must be considered. For this reason, the jump shrug and hang high pull may be highlighted during the speed-strength phase due to their ballistic nature. A combined approach of prescribing heavy and light loaded derivatives should be implemented to optimise RFD and power adaptations. Thus, practitioners may prescribe a combination of the clean/snatch mid-thigh pull or pull from the floor and the jump shrug and hang high pull to focus on training each end of the force-velocity curve. Varying neurological demands will be placed on the athlete as the above combination will simulate overcoming the inertia of an external load from a static start (e.g., mid-thigh pull) and ustilise the stretch-shortening cycle (e.g., jump shrug), allowing them to optimise impulse, RFD, and power characteristics. Another aspect to consider during the speed-strength phase is the load implemented with each exercise. Previous literature has suggested training at or near the loads that maximise power (Kawamori and Haff, 2004). As discussed above, loads of approximately 70–80% 1RM may provide the optimal training load for the power clean and hang power clean, while lighter loads (i.e., 30–45% 1RM of hang power clean) may optimise training stimuli for the jump shrug and hang high pull. Finally, additional literature has indicated that loads of approximately 90% of an athlete’s 1RM power clean (Haff et al., 2003) or full clean/snatch (Ermakov, 1980) may optimise the training stimulus for the clean/snatch pull from the floor.
SPEED DEVELOPMENT A sequenced progression of programming weightlifting derivatives may aid in the development of an athlete’s speed characteristics (DeWeese et al., 2016). Using the methods described above, specific weightlifting derivatives may be programmed during specific strength training phases that coincide with speed development phases (Figure 15.16). The following will discuss the rationale of prescribing a sequenced progression of weightlifting derivatives to enhance an athlete’s sprint speed.
General preparation phase As displayed in Figure 15.10, the general preparation phase is focused on improving the accelerative abilities of an athlete. Coaches may choose to program resisted runs (i.e., inclines and towing) at this point to develop high propulsive forces into the ground, while in the weight room a strengthendurance phase serves to develop the athlete’s work capacity and cross-sectional area in order to enhance their muscular strength and power in later training phases (Stone et al., 1982). As mentioned above, practitioners may program the clean/snatch pull to knee, pull from the floor, and shoulder shrug. Each of these movements can be used to strengthen the athlete’s musculature at specific angles
that relate to their posture during various acceleration phases. For example, the first pull requires athletes to start from a knee angle of approximately 90° and extend the knees to about 120°, angles that coincide with a sprinter’s knee angles in the starting blocks (Cˇoh et al., 1998).
FIGURE 15.16 Sequenced progressions of speed and strength-power development with the weightlifting derivatives that may be used within each phase. Adapted from DeWeese et al. (2014).
Special preparation phase Upon entering the special preparation phase of training, the training emphasis builds upon the enhanced acceleration characteristics from the previous phase to build top speed characteristics. Coaches may program running drills such as acceleration holds, low-load resisted runs, and longer segment accelerations during this phase before introducing maximum velocity sprinting drills (e.g., fly-in sprints and in-and-outs). Concurrently in the weight room, the focus of training shifts to improving the athlete’s strength characteristics. The clean/snatch pull from the floor, pull from the knee, and mid-thigh pull exercises serve to develop vertical force production through the ranges of motion experienced during the acceleration and transition to upright running phases. Moreover, these movements overload the athlete in a position that is relative to top speed mechanics (i.e., 120–140° knee angle, tall torso, and shortened range of motion) (DeWeese et al., 2015). In addition, exercises like the hang power clean/snatch, power clean/snatch, mid-thigh clean/snatch, and the full clean and snatch may be programmed during this phase to introduce a strength-speed component that will aid in the development of the athlete’s RFD characteristics. TABLE 15.1 Reported relative kinetic variables across power clean derivatives
Early-mid competition phase Leading into the start of the season, coaches will typically prescribe drills that will retain an athlete’s accelerative and top speed abilities through short sprint work as well as training sessions specific to the sprint distances of the athlete’s sport/event. Within the weight room, an early emphasis should be placed on strength-speed. Thus, weightlifting derivatives that focus on moving heavier loads quickly should be programmed. The suggested exercises within this phase include the mid-thigh pull and the power clean/snatch. The mid-thigh pull in this case will maintain high force production characteristics as practitioners may program up to 140% 1RM, while the power clean/snatch enables athletes to utilise the stretch-shortening cycle that occurs during the double knee bend as described above. The latter will allow athletes to generate large vertical forces in an upright position that may counteract those experienced during the stance phase of sprinting. Finally, the emphasis may shift to incorporating speed-strength exercises which move lighter loads quickly. Such exercises may include the countermovement clean/snatch, mid-thigh clean/snatch, hang high pull, and jump shrug.
Late competition/taper phase Upon reaching the latter stages of competition, the emphasis in weight room training aims to emphasise speed-strength characteristics while retaining strength-speed characteristics. Practitioners may elect to implement a variety of ballistic movements such as potentiation complexes, lightweighted jump squats, plyometrics, etc.; however, regarding weightlifting derivatives, the countermovement clean/snatch, mid-thigh clean/snatch, hang high pull, and jump shrug should be implemented during this phase of training. In addition, practitioners may consider implementing the mid-thigh pull to continue to retain strength-speed qualities. In fact, the mid-thigh pull could be programmed prior to one of the previously mentioned exercises in order to potentiate the power output of the latter exercise.
SUMMARY Weightlifting movements and their derivatives are effective training tools that may be used to enhance an athlete’s lower body ‘explosiveness’ and load absorption capacity. Weightlifting catching and pulling derivatives both provide useful training stimuli and may be programmed to meet the specific goals of various resistance training phases. A sequenced progression of weightlifting catching and pulling derivatives may be used to optimally develop the force-velocity profile and speed of an athlete.
REFERENCES Arabatzi, F. & Kellis, E. 2012. Olympic weightlifting training causes different knee muscle-coactivation adaptations compared with traditional weight training. J Strength Cond Res, 26, 2192–2201. Carlock, J. M., Smith, S. L., Hartman, M. J., Morris, R. T., Ciroslan, D. A., Pierce, K. C., Newton, R. U., Harman, E. A., Sands, W. A. & Stone, M. H. 2004. The relationship between vertical jump power estimates and weightlifting ability: a field-test approach. J Strength Cond Res, 18, 534–539. Channell, B. T. & Barfield, J. P. 2008. Effect of Olympic and traditional resistance training on vertical jump improvement in high school boys. J Strength Cond Res, 22, 1522–1527. Chaouachi, A., Hammami, R., Kaabi, S., Chamari, K., Drinkwater, E. J. & Behm, D. G. 2014. Olympic weightlifting and plyometric
training with children provides similar or greater performance improvements than traditional resistance training. J Strength Cond Res, 28, 1483–1496. Cˇoh, M., Jošt, B., Škof, B., Tomažin, K. & Dolenec, A. 1998. Kinematic and kinetic parameters of the sprint start and start acceleration model of top sprinters. Gymnica, 28, 33–42. Comfort, P., Allen, M. & Graham-Smith, P. 2011a. Comparisons of peak ground reaction force and rate of force development during variations of the power clean. J Strength Cond Res, 25, 1235–1239. Comfort, P., Allen, M. & Graham-Smith, P. 2011b. Kinetic comparisons during variations of the power clean. J Strength Cond Res, 25, 3269–3273. Comfort, P., Fletcher, C. & McMahon, J. J. 2012a. Determination of optimal loading during the power clean, in collegiate athletes. J Strength Cond Res, 26, 2970–2974. Comfort, P., Jones, P. A. & Udall, R. 2015. The effect of load and sex on kinematic and kinetic variables during the mid-thigh clean pull. Sports Biomech, 14, 139–156. Comfort, P., Udall, R. & Jones, P. A. 2012b. The effect of loading on kinematic and kinetic variables during the midthigh clean pull. J Strength Cond Res, 26, 1208–1214. Comfort, P., Williams, R., Suchomel, T. J. & Lake, J. P. 2017. A comparison of catch phase force-time characteristics during clean deriatives from the knee. J Strength Cond Res, 31, 1911–1918. DeWeese, B. H., Bellon, C. R., Magrum, E., Taber, C. B. & Suchomel, T. J. 2016. Strengthening the springs. Techniques, 9, 8–20. DeWeese, B. H., Sams, M. L., Williams, J. H. & Bellon, C. R. 2015. The nature of speed: enhancing sprint abilities through a short to long training approach. Techniques, 8, 8–22. Enoka, R. M. 1979. The pull in Olympic weightlifting. Med Sci Sports, 11, 131–137. Garhammer, J. 1980. Power production by Olympic weightlifters. Med Sci Sports Exerc, 12, 54–60. Garhammer, J. 1982. Energy flow during Olympic weight lifting. Med Sci Sports Exerc, 14, 353–360. Garhammer, J. 1991. A comparison of maximal power outputs between elite male and female weightlifters in competition. Int J Sport Biomech, 7, 3–11. Gourgoulis, V., Aggeloussis, N., Garas, A. & Mavromatis, G. 2009. Unsuccessful vs. successful performance in snatch lifts: a kinematic approach. J Strength Cond Res, 23, 486–494. Haff, G. G. & Nimphius, S. 2012. Training principles for power. Strength Cond J, 34, 2–12. Haff, G. G., Whitley, A., McCoy, L. B., O’Bryant, H. S., Kilgore, J. L., Haff, E. E., Pierce, K. & Stone, M. H. 2003. Effects of different set configurations on barbell velocity and displacement during a clean pull. J Strength Cond Res, 17, 95–103. Häkkinen, K., Kauhanen, H. & Komi, V. P. 1984. Biomechanical changes in the Olympic weightlifting technique of the snatch and clean and jerk from submaximal to maximal loads. Scand J Sport Sci, 6, 57–66. Harbili, E. & Alpteking, A. 2014. Comparative kinematic analysis of the snatch lifts in elite male adolescent weightlifters. J Sports Sci Med, 13, 417–422. Hardee, J. P., Lawrence, M. M., Utter, A. C., Triplett, N. T., Zwetsloot, K. A. & McBride, J. M. 2012a. Effect of inter-repetition rest on ratings of perceived exertion during multiple sets of the power clean. Eur J Appl Physiol, 112, 3141–3147. Hardee, J. P., Lawrence, M. M., Zwetsloot, K. A., Triplett, N. T., Utter, A. C. & McBride, J. M. 2013. Effect of cluster set configurations on power clean technique. J Sports Sci, 31, 488–496. Hardee, J. P., Triplett, N. T., Utter, A. C., Zwetsloot, K. A. & McBride, J. M. 2012b. Effect of interrepetition rest on power output in the power clean. J Strength Cond Res, 26, 883–889. Hoffman, J. R., Cooper, J., Wendell, M. & Kang, J. 2004. Comparison of Olympic vs. traditional power lifting training programs in football players. J Strength Cond Res, 18, 129–135. Hori, N., Newton, R. U., Andrews, W. A., Kawamori, N., McGuigan, M. R. & Nosaka, K. 2008. Does performance of hang power clean differentiate performance of jumping, sprinting, and changing of direction? J Strength Cond Res, 22, 412–418. Kauhanen, H., Häkkinen, K. & Komi, P. V. 1984. A biomechanical analysis of the snatch and clean & jerk techniques of Finnish elite and district level weightlifters. Scand J Sports Sci, 6, 47–56. Kawamori, N., Crum, A. J., Blumert, P. A., Kulik, J. R., Childers, J. T., Wood, J. A., Stone, M. H. & Haff, G. G. 2005. Influence of different relative intensities on power output during the hang power clean: identification of the optimal load. J Strength Cond Res, 19, 698–708. Kawamori, N. & Haff, G. G. 2004. The optimal training load for the development of muscular power. J Strength Cond Res, 18, 675– 684. Kilduff, L. P., Bevan, H., Owen, N., Kingsley, M. I., Bunce, P., Bennett, M. & Cunningham, D. 2007. Optimal loading for peak power output during the hang power clean in professional rugby players. Int J Sports Physiol Perform, 2, 260–269. Kipp, K., Malloy, P. J., Smith, J., Giordanelli, M. D., Kiely, M. T., Geiser, C. F. & Suchomel, T. J. 2016. Mechanical demands of the hang power clean and jump shrug: a joint-level perspective. J Strength Cond Res, Epub ahead of print. McBride, J. M., Haines, T. L. & Kirby, T. J. 2011. Effect of loading on peak power of the bar, body, and system during power cleans, squats, and jump squats. J Sports Sci, 29, 1215–1221. Minetti, A. E. 2002. On the mechanical power of joint extensions as affected by the change in muscle force (or cross-sectional area), ceteris paribus. Eur J Appl Physiol, 86, 363–369.
Moolyk, A. N., Carey, J. P. & Chiu, L. Z. F. 2013. Characteristics of lower extremity work during the impact phase of jumping and weightlifting. J Strength Cond Res, 27, 3225–3232. Morrissey, M. C., Harman, E. A. & Johnson, M. J. 1995. Resistance training modes: specificity and effectiveness. Med Sci Sports Exerc, 27, 648–660. Newton, R. U., Kraemer, W. J., Häkkinen, K., Humphries, B. & Murphy, A. J. 1996. Kinematics, kinetics, and muscle activation during explosive upper body movements. J Appl Biomech, 12, 31–43. Otto III, W. H., Coburn, J. W., Brown, L. E. & Spiering, B. A. 2012. Effects of weightlifting vs. kettlebell training on vertical jump, strength, and body composition. J Strength Cond Res, 26, 1199–1202. Schilling, B. K., Stone, M. H., O’Bryant, H. S., Fry, A. C., Coglianese, R. H. & Pierce, K. C. 2002. Snatch technique of collegiate national level weightlifters. J Strength Cond Res, 16, 551–555. Soriano, M. A., Jiménez-Reyes, P., Rhea, M. R. & Marín, P. J. 2015. The optimal load for maximal power production during lower-body resistance exercises: a meta-analysis. Sports Med, 45, 1191–1205. Stone, M. H., Moir, G., Glaister, M. & Sanders, R. 2002. How much strength is necessary? Phys Ther Sport, 3, 88–96. Stone, M. H., O’Bryant, H., Garhammer, J., McMillan, J. & Rozenek, R. 1982. A theoretical model of strength training. Strength Cond J, 4, 36–39. Stone, M. H., O’Bryant, H. S., Williams, F. E., Johnson, R. L. & Pierce, K. C. 1998. Analysis of bar paths during the snatch in elite male weightlifters. Strength Cond J, 20, 30–38. Suchomel, T. J. & Sole, C. J. 2017. Force-time curve comparison between weightlifting derivatives. Int J Sports Physiol Perform, 12, 431–439. Suchomel, T. J., Beckham, G. K. & Wright, G. A. 2013. Lower body kinetics during the jump shrug: impact of load. J Trainol, 2, 19–22. Suchomel, T. J., Beckham, G. K. & Wright, G. A. 2014a. The impact of load on lower body performance variables during the hang power clean. Sports Biomech, 13, 87–95. Suchomel, T. J., Beckham, G. K. & Wright, G. A. 2015a. Effect of various loads on the force-time characteristics of the hang high pull. J Strength Cond Res, 29, 1295–1301. Suchomel, T. J., Comfort, P. & Lake, J. P. 2017a. Enhancing the force-velocity profile of athletes using weightlifting derivatives. Strength Cond J, 39,10–20. Suchomel, T. J., Comfort, P. & Stone, M. H. 2015b. Weightlifting pulling derivatives: rationale for implementation and application. Sports Med, 45, 823–839. Suchomel, T. J., DeWeese, B. H. & Serrano, A. J. 2016a. The power clean and power snatch from the knee. Strength Cond J, 38, 98– 105. Suchomel, T. J., Lake, J. P. & Comfort, P. 2017b. Load absorption force-time characteristics following the second pull of weightlifting derivatives. J Strength Cond Res, 31, 1644–1652. Suchomel, T. J., Nimphius, S. & Stone, M. H. 2016b. The importance of muscular strength in athletic performance. Sports Med, 46, 1419–1449. Suchomel, T. J., Wright, G. A., Kernozek, T. W. & Kline, D. E. 2014b. Kinetic comparison of the power development between power clean variations. J Strength Cond Res, 28, 350–360. Taber, C. B., Bellon, C. R., Abbott, H. & Bingham, G. E. 2016. Roles of maximal strength and rate of force development in maximizing muscular power. Strength Cond J, 38, 71–78. Teo, S. Y., Newton, M. J., Newton, R. U., Dempsey, A. R. & Fairchild, T. J. 2016. Comparing the effectiveness of a short-term vertical jump versus weightlifting program on athletic power development. J Strength Cond Res, 30, 2741–2748. Tricoli, V., Lamas, L., Carnevale, R. & Ugrinowitsch, C. 2005. Short-term effects on lower-body functional power development: weightlifting vs. vertical jump training programs. J Strength Cond Res, 19, 433–437. Winchester, J. B., Porter, J. M. & McBride, J. M. 2009. Changes in bar path kinematics and kinetics through use of summary feedback in power snatch training. J Strength Cond Res, 23, 444–454. Zamparo, P., Minetti, A. & Di Prampero, P. 2002. Interplay among the changes of muscle strength, cross-sectional area and maximal explosive power: theory and facts. Eur J Appl Physiol, 88, 193–202.
CHAPTER 16
Plyometric training Christopher J. Sole
SECTION 1 Plyometric training (PT) is a classification of strength training exercise consisting mainly of various forms of jumping. These exercises are commonly integrated into a training process to enhance impulsive qualities of muscular performance such as speed-strength and reactive-strength. Depending on the goal of training, PT exercises may come in various forms. However, jumping exercises such as countermovement jumps, bounding, drop and depth jumps are some of the more common. Plyometric training however, is not limited to lower-extremity exercise, with various exercises developed for training the upper-extremities and trunk (Wilk et al., 1993, Potach and Chu, 2016). Whether implemented independently or in combination with other training methods, PT has been found to enhance a variety of components of athletic performance such as jumping, sprinting, and change of direction ability (Booth and Orr, 2016, Markovic and Mikulic, 2010). Consequently, PT has become increasingly popular among strength and conditioning practitioners. However, in order to effectively incorporate PT into practice, practitioners must possess a basic understanding of the underlying science and empirical evidence supporting this training modality. Therefore, the purpose of this chapter will be to provide (1) a brief review of the mechanisms underpinning plyometric training, (2) a brief discussion of the physiological and performance adaptations elicited through plyometric training, and (3) an evidence-based discussion of the programing and periodization of plyometric training.
STRETCH-SHORTENING CYCLE The coupling of eccentric and concentric muscle actions results in a natural function of muscle known as a stretch-shortening cycle (SSC) (Komi, 2000, Norman and Komi, 1979, Komi, 2008). During an SSC, the eccentric action enhances subsequent concentric action resulting in increased force, power, and efficiency, referred to as SSC potentiation. An SSC consists of three distinct phases: (1) the eccentric phase, (2) the amortization phase, and (3) the concentric phase. The eccentric phase is characterized by the active lengthening or stretch of the musculotendinous unit (MTU). The amortization phase represents the brief time interval between eccentric and concentric muscle action and involves an isometric action. The concentric or propulsive phase consists of concentric muscle action. Plyometric training has become synonymous with an SSC (Wilt, 1978, Wilk et al., 1993), as SSC action is a key characteristic of all PT exercises. Therefore, a basic understanding of the mechanisms underpinning SSC potentiation/performance is crucial as they form the basis of all PT. Several mechanisms of SSC potentiation have been proposed, and can be classified as either mechanical or neurophysiological in nature. The following will provide a brief review of these mechanisms, as a basic understanding of such is required for a complete discussion of the demands of PT. For an exhaustive review of the SSC and proposed mechanisms, see Chapter 3 and Turner and Jeffreys (2010). From a mechanical perspective, SSC potentiation is attributed to the utilization of stored elastic energy. In this explanation, the MTU behaves similarly to a damped spring (Figure 16.1a) (Hill, 1938). During the eccentric action, or prestretch, energy is stored in the elastic components of the MTU then utilized in the following concentric action, ultimately enhancing force and power output. Multiple structures within the MTU collectively referred to as the series elastic component (SEC)
and parallel elastic component (PEC) are capable of storing elastic energy. However, the SEC, namely tendon, is believed to be the primary contributor during SSC function (Kubo et al., 1999, Lichtwark and Wilson, 2005). In addition to mechanical factors, several neurophysiological mechanisms have been suggested to explain SSC potentiation. Involuntary nervous processes such as the stretch reflex (Figure 16.1b) have been implicated in contributing to SSC potentiation (Dietz et al., 1979, Bosco et al., 1981). Briefly, the prestretch of the MTU initiates a reflex action via the muscle spindles. When the muscle spindles detect a rapid increase in muscle length, a neural impulse is relayed to the spinal cord via type Ia afferent fibers. Type Ia afferent fibers then synapse with the alpha motor neuron resulting in a reflexive muscle action (Kandel et al., 2000). If appropriately timed, it is believed the pairing of voluntary and involuntary (reflexive) actions results in supramaximal concentric activation of the agonist muscle.
FIGURE 16.1
(a) Mechanical and (b) neurophysiological models of stretch-shortening cycle potentiation. SEC = series elastic component, CC = contractile component, PEC = parallel elastic component. MS = muscle spindles, EF = extrafusal fibers.
Additional theories have suggested that during SSC movements, the eccentric action of the prestretch results in an increase of the active state of the muscle (Bobbert and Casius, 2005), decreasing the time required to produce force by shortening the electromechanical delay or time interval between excitation and mechanical output (Cavanagh and Komi, 1979). This in turn results in an increase of the working range of the muscle, where greater force and impulse can be generated throughout the concentric phase of the movement. It has also been speculated that a prestretch and subsequent lengthening may place the muscle in a more optimal region of the length-tension relationship (Gordon et al., 1966a, Gordon et al., 1966b) resulting in improved force production at initiation and throughout concentric action (Ettema et al., 1992).
Although there still exists some debate over the exact mechanism responsible SSC potentiation, in general the potentiating effect of an SSC is likely attributed to a combination of these mechanical and neurophysiological properties of the neuromuscular system. However, the relative contributions of each mechanism in SSC potentiation remains unknown (Potach and Chu, 2016), and is likely to vary between exercises. Relevant to both mechanical and neurophysiological perspectives is the time interval between prestretch and shorting, or amortization phase. In order for the stored elastic energy to be utilized, concentric action must immediately follow the stretch. If not, any energy stored in the elastic components will dissipate as heat. Similarly, too long of an interval between prestretch and concentric action will limit the contribution of the reflex action in concentric performance. An additional consideration is the rate and magnitude of the prestretch. A large and rapid stretch has been demonstrated to result in greater SSC potentiation and improved performance (McCaulley et al., 2007, McBride et al., 2008, Kilani et al., 1989, Váczi et al., 2013). Therefore, altering the prestretch through modifying characteristics of the exercise (e.g., velocity of descent, height dropped, etc.) may be viewed as one method for manipulating both the intensity and performance outcomes of PT exercises. The above consideration will be discussed in further detail in Section 2 as it relates to the application of PT.
ADAPTATIONS TO PLYOMETRIC TRAINING Plyometric training interventions have been found to elicit a variety of neuromuscular adaptations related to enhanced SSC function and consequently enhanced athletic performance (Markovic and Mikulic, 2010). The following will review primary physiological and performance adaptations reported in the extant literature. Plyometric training is most commonly associated with qualitative changes in muscle function. However, some evidence exists demonstrating quantitative improvements following PT such as whole muscle (Struminger et al., 2013, Chelly et al., 2010, Kubo et al., 2007, Vissing et al., 2008) and individual fiber hypertrophy (Malisoux et al., 2006a, Malisoux et al., 2006b, Potteiger et al., 1999), albeit predominantly in untrained individuals. For example, Malisoux and colleagues (2006a) reported increases in fiber diameter of 11% in type I, 10% in type IIa, and 15% in type IIa/IIx following a PT training intervention. From a qualitative standpoint, PT has been found to alter the contractile properties of individual fibers. Increases in peak fiber force of 19–35% in type I, 15–25% in type IIa, and 16–57% in type IIa/IIx fibers have been found following PT. Additionally, increases in maximal shortening velocity of 18%, 29%, and 22% were observed in type I, IIa, and IIa/IIx, respectively (Malisoux et al., 2006a, Malisoux et al., 2006b). It is important to note that the alterations in contractile properties cited above were observed in addition to statistical improvements in lower-extremity functional performance, namely vertical jump, leg press, and shuttle run. Plyometric training is believed to result in a shift in muscle fiber type. However, limited evidence (Malisoux et al., 2006a) exists supporting this claim. Conversely, studies by Potteiger and colleagues (1999) and Kyröläinen and colleagues (2005) have suggested that fiber type transitions are not observed following PT alone. In addition to adaptations to the muscle itself, performance improvements following PT may be attributed, at least in part, to adaptations to the nervous system. However, specific knowledge of the influence of PT on neural adaptation is limited. Proposed neural adaptations following PT include
increased firing rate, motor unit recruitment, and reflex excitability, as well as improved intermuscular coordination (Markovic and Mikulic, 2010). Furthermore, it is speculated that PT may reduce protective inhibitory reflex action originating from proprioceptors such as the Golgi tendon organ, resulting in improved performance under high-load conditions. Muscular strength is a primary target adaptation of many training programs as it is believed to be a key component of many aspects of athletic performance (Suchomel et al., 2016). When implemented alone, PT has been found to increase strength in a variety of populations (Saez-Saez de Villarreal et al., 2010, Malisoux et al., 2006a, Vissing et al., 2008). These improvements are believed to be attributed to a combination of both neural and muscular adaptations (Markovic and Mikulic, 2010). However, as with muscular hypertrophy, an individual’s training status may dictate the magnitude of strength adaptations following PT. For example, when examining the effect sizes reported in a metaanalysis by Saez-Saez de Villarreal and associates (2010), strength improvements following PT appear to be of a greater magnitude in lesser-trained individuals as compared to studies involving trained individuals. Muscular strength seems to be most affected when PT is implemented in combination with resistance training (Saez-Saez de Villarreal et al., 2013, Adams et al., 1987, Fatouros et al., 2000, Markovic and Mikulic, 2010, Booth and Orr, 2016). Although evidence does exist citing improved muscular strength, it is likely PT more strongly influences specific elements of strength such as reactive strength and impulsive ability. For example, when comparing conventional resistance training with PT, Vissing et al. (2008) reported similar improvements in maximal strength between the two modalities; however, PT seemed to have a stronger influence on impulsive abilities such as countermovement jump performance and a ballistic-style leg press. Plyometric training and resistance training may also be combined within a single set. This pairing of high-intensity dynamic resistance training exercises with biomechanically similar PT exercises has been termed complex training (Ebben, 2002, Docherty et al., 2004). Vertical jump is a fundamental athletic movement common in the performance of many sports, and PT has been demonstrated to improve vertical jump height in a variety of individuals across various types of vertical jump tests (Markovic, 2007, Saez-Saez de Villarreal et al., 2009). Previous literature, such as a meta-analysis performed by Markovic (2007), has cited mean improvements in jump height of approximately 5% in static and depth jumps, and up to 9% in countermovement jumps over training periods of 8.6 ± 2.7 weeks and 8.6 ± 3.4 weeks, respectively. Therefore, it seems adequate empirical evidence exists supporting the use of PT for improving jumping ability. In addition to improving jump height, recent meta-analyses (Saez-Saez de Villarreal et al., 2012, Asadi et al., 2016) have provided evidence suggesting PT may be successfully implemented to enhance performance in other key components of sport performance such as sprinting and change of direction (COD) movements. For example, according to Saez-Saez de Villarreal and colleagues (2012), performing 80 high-intensity jumps two times per week over ten weeks was effective in eliciting improvements in sprint performance. Moreover, a meta-analysis performed by Asadi and colleagues (2016) concluded that performing moderate intensity PT including multiple forms of jumping is effective in improving COD ability over seven weeks. This result provides evidence demonstrating the key role of lower-extremity neuromuscular qualities such as SSC function (i.e., efficient coupling of eccentric and concentric muscle actions) in COD performance. Interestingly, in addition to adaptations in strength and impulsive ability, PT has also demonstrated adaptations in neuromuscular efficiency such as improved running economy. Several studies have observed improvements in endurance performance following PT independent of any improvements in aerobic fitness (Spurrs et al., 2003, Saunders et al., 2006, Turner et al., 2003). These performance
improvements may be explained by an overall improved efficiency of the muscular system through improved eccentric-concentric coupling as well as more effective utilization of stored elastic energy. Therefore, performance benefits achieved through enhanced SSC performance are not limited to strength-power athletes. Finally, considering the primary mode of PT is variations of jumping exercises, the bulk of the literature is focused on adaptations to the lower-extremities. However, several upper-extremity PT exercises have been developed (Wilk et al., 1993), including ballistic push-up variations, medicine ball throws, and depth push-ups (Potach and Chu, 2016). Although there is a paucity of research investigating upper-extremity PT, some empirical evidence does exist supporting the effectiveness of upper-extremity PT (Carter et al., 2007, Schulte-Edelmann et al., 2005).
SECTION 2: PRACTICAL APPLICATION OF PLYOMETRIC TRAINING As illustrated in Section 1, integrating PT into an athlete’s training program can result in the enhancement of various aspects of athletic performance including improved jumping, sprinting, and change of direction ability. However, for effective implementation of PT, practitioners must possess adequate knowledge of programming including methods of appropriate progression, variation, and overload of PT. Furthermore, effective programing must take into consideration the athlete’s needs, training history, and most importantly, how this training modality fits into the broader picture that is the training process.
MODE AND SPECIFICITY OF PLYOMETRIC TRAINING An initial step in the programing of any exercise is identifying the most appropriate mode of training. The mode of PT exercise must be carefully selected based on the demands of the sport and/or player position, as well as the needs and history of the individual athlete. In general, PT can be divided into lower-extremity, upper-extremity, and trunk exercises (Potach and Chu, 2016). In many cases one may implement only one mode of PT (e.g., lower-extremity), on the other hand, a practitioner may determine several modes of PT are appropriate for their athlete(s). Examples of common PT exercises are provided in Table 16.1. Specificity of training is among the most important considerations when designing a training program, as the most specific training exercises should result in the greatest transfer of training effect. Commonly, an exercise’s specificity is determined through “face validity” or the outward appearance of the gross mechanics of the exercise, rather than the specific adaptations that are required. In order to choose the most appropriate methods of progression, overload, and variation, practitioners must possess a thorough understanding of the impact of specificity on PT. In addition to the gross mechanics of the movement, practitioners should consider the magnitude of the forces produced, rates at which forces are developed, velocity and acceleration characteristics, and temporal characteristics of the exercise (Stone et al., 2007). Although specificity is crucial to adaptation, overly specific training, which is not specific to the required adaptive response, can also lead to deleterious training stimuli. For example, one may sacrifice speed of movement or rate of force development in effort to mimic a highly specific sporting movement. An example the role of specificity in transfer of training is provided by Nagahara and associates (2014) who examined the relationships between acceleration during a 60-meter sprint and various jumping tasks. The analysis revealed markedly different correlation coefficients when comparing jumping tests and acceleration across each phase of the sprint. For example, the static jump was most strongly related to early acceleration phase, whereas the ankle jump (a continuous rebound jump performed using only plantar flexion) was most strongly related to maximum velocity sprinting. In other words, the kinetic and kinematic characteristics of exercise must be carefully examined to ensure they are in line with the mechanical characteristics of the movements you are trying to enhance. Consider an additional example, a typical ground contact time during the high jump take-off is ≈ 175 ms (Aura and Viitasalo, 1989). If given the choice between a countermovement jump and a drop jump as a training exercise, the drop jump would be the most appropriate, as contact times for this exercise are ≈ 136–222 ms (Walsh et al., 2004) as compared to a movement time > 250 ms (generally 400– 600 ms) experienced in the countermovement jump. Moreover, the characteristics of the prestretch
between these two exercises are drastically different, with a much greater rate and magnitude of stretch experienced during the drop jump. An often overlooked element of specificity relates to the instructions and coaching cues given during training. Motor learning research has indicated that instructions regarding the goal and attentional focus of the exercise can markedly influence performance outcomes (Hodges and Franks, 2004, Wulf, 2007). Application of this element of specificity has been recently highlighted in a review of coaching cues for sprinting (Benz et al., 2016). Specifically related to PT, studies have reported instructions to be a key factor influencing the kinematic and kinetic characteristics of the several common PT jumping exercises (Young et al., 1995, Talpey et al., 2016, Louder et al., 2015). Talpey and colleagues (2016) reported that instructing participants to “minimize ground contact time” as compared to “maximize jump height” in the depth jump resulted in not only decreased ground contact times, but also increased peak force, mean acceleration, and propulsive impulse during the exercise. Consequently, ensuring proper instructions are provided during PT should be a key specificity consideration, as it can have an impact on the stimulus and resultant adaptation of the exercise. TABLE 16.1 Examples of common plyometric training exercises Mode
Exercises Stationary jumps
• • • •
Standing jumps
• • •
Lower-extremity Multiple jumps/bounding
• • • • • • •
Box jumps
• • • • • • •
Upper-extremity
• •
Ankle hop unilateral)
Intensity (bilateral
and • •
Squat jump Countermovement jump
• •
Split jumps Broad jump Static jump over barrier Countermovement jump barrier
• • over •
Hops (bilateral and unilateral) Repeat broad jump Alternate-leg bound Power skip Single-leg bound Side skip Zig-zag bound (speed skaters)
• • • • • • •
Static jump onto a box
• Countermovement jump onto a • box • Land and stick • Depth jump • Drop jump • Depth jump to Box Depth jump over barrier
•
Chest pass
• •
Underhand toss for height
Low Low Low Low/moderate Moderate Moderate Moderate Low Low-moderate Moderate/high Moderate/high High Low/moderate Low/moderate Moderate Moderate Low-moderate High High High High Moderate Moderate
Trunk
• •
Single-arm chest pass
• •
Delivery toss
•
Depth push-up Chop Sit-up throw
• •
Moderate/high
• •
Moderate
•
Moderate/high Moderate Low/moderate
FREQUENCY AND RECOVERY Training frequency is typically expressed as the number of training sessions per microcycle (week). As with all training, the frequency of PT will vary depending on the specific phase of the training year. Factors influencing PT frequency include: primary focus of the training phase, competition schedule, and proportion of training time devoted to sport practice, among others. Limited research exists as to optimal PT frequency. However, based on the results of meta-analyses investigating jumping (Saez-Saez de Villarreal et al., 2009), sprinting (Saez-Saez de Villarreal et al., 2012), and change of direction (Asadi et al., 2016) totaling 106 studies, two sessions per week appears to be a sufficient training stimulus. In addition to the aforementioned factors, PT frequency is ultimately determined by betweensession recovery time. Considering the high-intensity nature of PT, between 48 and 72 hours has been suggested as an appropriate recovery time between sessions. Therefore, between two and three PT sessions per microcycle seems to be the upper limit. It is important to note that recovery time from PT sessions may be highly variable based on several factors. The volume, intensity, as well as individual athlete factors such as training status should be considered when deciding optimal recovery. Moreover, many sports are inherently “plyometric” such as basketball, volleyball, and netball. This presents a logistical problem for practitioners attempting to appropriately program PT sessions while taking into consideration recovery from both practice as well as previous training sessions. Therefore, it is highly recommended that practitioners carefully track volume and intensity of both training and sport practice as well as implement monitoring interventions in order to judge recovery and ensure an optimal training stimulus. Recovery within the training session itself, or intraset and interset recovery interval, is also an important programing consideration. When determining the intraset and interset recovery periods, the practitioner should again consider the volume and intensity of the training exercise. Although by definition most PT exercises are high intensity, some are performed at a lower intensity and therefore may require less recovery. For example, the interset and intraset recovery when performing lowamplitude bilateral hops would be much less than when performing a set of 40cm drop jumps considering the marked differences in kinetic and kinematic characteristics between the two exercises (Figure 16.2). In general, the practitioner should keep in mind the overall goal of PT, which is to enhance impulsive and reactive qualities. Therefore, each repetition should be performed in a highquality manner. General recommendations for work to rest ratios for PT range from 1:5 to 1:10 depending on the specific exercise (Potach and Chu, 2016).
FIGURE 16.2
Illustrates the force-time histories of a bilateral ankle hop (dashed line) and a drop jump from 40 centimeters (solid line). Note the differences in rate and magnitude of force production as well as impulse (area under the curve) between the two exercises.
VOLUME AND INTENSITY In traditional resistance training the most commonly used measures of training “dosage” are volume and intensity. Training volume refers to the amount of work performed by the athlete during training, and can be quantified for a set, session, week, etc. Several methods of quantifying PT volume have been suggested (Potach and Chu, 2016, Chu, 1998). In general, the simplest methods are usually the most practical. For example, in horizontal PT exercises (e.g., alternate-leg bound, single-leg bound) volume can be expressed as the total distance covered during the session. Using this method, a set of four alternate-leg bounds performed over 25m would result in a total volume of 100m. Although this method may be sufficient, it would be difficult to equate across athletes on account of differences in limb length and ability. A more effective method may be to express volume as the total number of ground contacts, or throws/catches in upper-extremity, and trunk exercises. Counting contacts or throws is also preferable considering a large number of PT exercises are performed in place (Table 16.1). When prescribing PT volumes, factors such as experience level and specific training focus should be carefully considered. If prescribing based on experience level, experts have suggested between 80–100, 100–120, and 120–140 contacts per session for beginners, intermediate, and advanced athletes, respectively (Potach and Chu, 2016). It should be noted, however, that the primary factor determining volume would be exercise intensity, with an inverse relationship existing between the two training components. Training intensity is typically indicative of the rate of work performed during an exercise. However, in PT it can also be related to the mechanical demands (rate and magnitude of loading) placed on the associated musculature during the exercise. Intensity of PT can be indirectly quantified in a variety of ways. In many cases intensity is inherent to the specific exercise. General guidelines for determining the intensity of a specific exercise include (1) the speed of the movement, (2) the points of contact (i.e., single vs. double leg hopping), (3) the amplitude of the movement, and (4) the body weight of the athlete or amount of added resistance (Turner and Jeffreys, 2010, Jeffreys, 2007). Approximate intensity levels are provided for the exercise listed in Table 16.1. Recently, with the
increased availability of technology such as force platforms, authors have suggested using the movement’s kinetics as the most valid method for objectively quantifying and tracking the demands of PT. Using this approach, variables such as peak force and rate of force development can be used to gauge exercise intensity, whereas impulse may be used to quantify volume (Jarvis et al., 2016). When it comes to manipulating intensity, the practitioner can choose from variety of options. Common methods for manipulating intensity include: manipulating jump height or box height in the case of box jumps and drop and depth jumps, the addition of an external load, or manipulating the speed of the movement and/or rate at which work is performed (e.g., jumps/throws per minute). Considering some PT exercises are inherently more intense than others, perhaps the simplest method of manipulating exercise intensity is changing the exercise itself. Careful attention should be placed on appropriate increases in intensity, as increasing the intensity beyond a certain level may alter the movement and training stimulus. In many cases, standards can be identified and intensity can be prescribed relative to maximum or criterion performance outcome such as peak power output (Di Giminiani and Petricola, 2016) or maximum jump height (Chu, 1998). Jumping exercises can also be performed effectively using added resistance such as a weighted vest (Khlifa et al., 2010). However, there is limited evidence supporting the effectiveness of loaded PT. It is important to note, however, that PT is high-intensity in nature, thus reducing the intensity of an exercise below a specific threshold may result in an unintended training stimulus. Conversely, inappropriate increases in intensity may unintentionally alter the exercise, such as increasing ground contact time or altering movement mechanics. Therefore, the practitioner must exercise caution when manipulating PT intensity and pay close attention to the quality of the movement ensuring that it is not sacrificed as intensity increases.
PROGRESSION Proper progression and variation of PT exercise is a key factor of effectively implementing PT, in addition to the more commonly known rationale for progression and variation: avoiding monotonous training and staleness. A traditional approach would be to progress from more general low-intensity to more specific high-intensity PT exercises. Progression plays a key role teaching athletes effective mechanics, which is believed to influence the safety and effectiveness of PT. For example, Turner and Jeffreys (2010) suggest a specific progression for beginners focusing on first jumping then landing and load absorption mechanics before complete SSC movements are performed. The general consensus is that if appropriately implemented, PT is safe for most individuals including adolescents. However, due to the high-intensity nature of PT, several training texts have outlined pre-training considerations to be addressed prior to implementing PT, most notably learning proper landing mechanics (Potach and Chu, 2016). Interestingly, several authors have also suggested one should possess a relative strength level equivalent to a back squat of 1.5 × bodyweight prior to initiating lower-extremity PT (Potach and Chu, 2016). Although controversial, this recommendation may be viewed as intuitive from an injury prevention standpoint (Radin, 1986). Furthermore, evidence suggests that increasing strength may optimize PT performance and therefore adaptation (Barr and Nolte, 2014, Suchomel et al., 2016). Overall the practitioner should use their judgment in determining whether or not the athlete is prepared to initiate PT.
PERIODIZATION OF PLYOMETRIC TRAINING
Periodization can be broadly defined as the planned distribution and variation of training stimuli in order to maximize fitness and improve the likelihood of competitive success. When considering periodization strategies for PT, practitioners should be reminded that effective periodization involves the integration of all training modalities into a complimentary sequence (i.e., the training process). Therefore, the following will discuss basic considerations for the proper progression and periodization of PT in context of the training process. Furthermore, considering empirical data from long-term training studies involving multiple mesocycles are scarce, much of the following information has been deduced from multiple studies and expert intuition. Given its high-intensity nature, focusing on PT year-round would be inappropriate. Furthermore, fatigue can have profound effects on SSC performance, negatively impacting mechanical characteristics of the movement and likely altering the training stimulus. Consequently, PT may best be implemented in training phases where overall training volume is low and there is an emphasis on movement quality (e.g., strength, and impulsive “explosive” phases). However, PT may be used in high-volume training phases to familiarize the athlete with PT and progress technique, perhaps through integrating low-intensity PT into elements of the training preparatory routine, with jump training-based warm ups shown to improve lower-extremity landing mechanics, which may reduce injury risk (Herrington, 2010, Myer et al., 2012, Herrington et al., 2015, Herrington and Comfort, 2013). A key component of periodization is the logical and complimentary sequencing of training phases and fitness characteristics. With this in mind, information from several sources promotes emphasizing strength and maximal strength through heavy resistance training (> 85% 1RM) prior to PT in order to maximize the net effectiveness of this training modality. The adaptations to the MTU experienced following heavy resistance should result in optimized stiffness and force generation in subsequent PT. Additionally, an increase in strength of muscle and connective tissue should reduce the likelihood of injury. In addition to optimizing acute performance and reducing the likelihood of injury, evidence suggests that emphasizing strength training prior to PT may maximize the net effectiveness of the overall training process. Briefly, according to data provided by Minetti (2002) and Zamparo and colleauges (2002), if impulsive ability or “explosiveness” is the target training adaptation, this type of training (i.e., PT) should be preceded by blocks of strength-focused training, where strengthendurance, hypertrophy, and maximal strength are the primary training emphasis. In other words, optimizing adaptation to PT can be achieved through a specific sequence of complementary training phases (Figure 16.3). This model of training is based on the concept of phase potentiation and has been integrated in several periodization schemes (Stone et al., 2007, Harris et al., 2000, Bompa and Haff, 2009).
FIGURE 16.3
Illustration of a generic periodization model where the target training adaptation is impulsive ability or “explosiveness”. Note the emphasis on plyometric training is greatest during periods of low-volume and high-intensity training. Additionally, plyometric training is emphasized following periods of strength and maximum strength focused training.
Collectively, we can conclude the following related to the integration of PT in one’s periodization scheme: (1) to maximize effectiveness, PT should be emphasized during periods of training where fatigue is low and movement quality is emphasized, (2) based on the available evidence, it appears performing heavy resistance training prior to PT should maximize performance and reduce the risk of injury, and (3) if the ultimate training goal is to maximizing impulsive ability or “explosiveness”, emphasizing strength and maximal strength prior to focused PT training will likely result in the greatest net training effect. Examples of how to structure PT sessions for different mesocycles are presented in Figures 16.4–16.6.
SUMMARY • • • •
Plyometric training is a form of explosive resistance training comprised of various jumping and throwing exercises. As nearly all plyometric training exercises are considered to involve a stretch-shortening cycle, knowledge of the underlying mechanisms of this muscle function will aid the practitioner in effectively implementing plyometric training. A large body of empirical evidence exists supporting the effectiveness of plyometric training in enhancing a variety of elements of athletic performance. Practitioners considering adding plyometric exercises into their athlete’s training should not only consider the basic principles of training, but also possess an understanding of how this training modality can be integrated into the training process as a whole.
FIGURE 16.4
Displays a generic example of how PT may be programed during a general preparation or strength-endurance mesocycle(s). In this example, the primary role of PT is to facilitate the learning of proper technique through exposing the athlete to a progression of simple exercises. In turn, general work capacity is established as well as a foundation for more advanced and higher intensity PT exercises. Plyometric training during this phase could be easily integrated into the warm up routine. Depending on the overall goals of the training process, as well as the training history of the athlete(s), a PT program such as this may not need to span eight weeks.
FIGURE 16.5
Displays a generic example of how PT may be programed during a basic or maximum strength mesocycle(s). The athlete is progressively exposed to increased stretch and loading conditions in order to prepare for higher intensity PT exercises aimed to fully exploit SSC potentiation. As force production capacity improves, PT exercises progress from partial to more complete SSC movements. Considering training volume and intensity are typically high during strengthfocused mesocycles, practitioners must carefully plan the integration of PT into the training process.
FIGURE 16.6
Displays a generic example of how PT may be programed during a mesocycle(s) where the primary training focus is developing impulsive ability or “explosiveness”. In this phase the primary focus of PT is to exploit SSC potentiation in order to provide a maximal training stimulus. Plyometric training exercises may also be paired with other resistance training exercises in the form of complex training. Intensity should remain high throughout and volume may fluctuate depending on the training process as well as sport practice and training schedules.
REFERENCES Adams, T., Worley, D. & Throgmartin, D. 1987. The effects of selected plyometric and weight training on muscular leg power. Track & Field Quarterly Review, 87, 45–47. Asadi, A., Arazi, H., Young, W. & Saez, D. V. E. 2016. The effects of plyometric training on change of direction ability: A meta-analysis. International Journal of Sports Physiology & Performance, 11, 563–573. Aura, O. & Viitasalo, J. T. 1989. Biomechanical characteristics of jumping. International Journal of Sport Biomechanics, 5. Barr, M. J. & Nolte, V. W. 2014. The importance of maximal leg strength for female athletes when performing drop jumps. The Journal of Strength & Conditioning Research, 28, 373–380. Benz, A., Winkelman, N., Porter, J. & Nimphius, S. 2016. Coaching Instructions and Cues for Enhancing Sprint Performance. Strength & Conditioning Journal, 38, 1–11. Bobbert, M. F. & Casius, L. J. 2005. Is the effect of a countermovement on jump height due to active state development? Medicine & Science in Sports & Exercise, 37, 440–446. Bompa, T. O. & Haff, G. G. 2009. Periodization: Theory and Methodology of Training. Champaign, IL: Human Kinetics. Booth, M. A. & Orr, R. 2016. Effects of plyometric training on sports performance. Strength & Conditioning Journal, 38, 30–37. Bosco, C., Komi, P. V. & Ito, A. 1981. Prestretch potentiation of human skeletal muscle during ballistic movement. Acta Physiologica Scandinavica, 111, 135–140. Carter, A. B., Kaminski, T. W., Douex Jr., A. T., Knight, C. A. & Richards, J. G. 2007. Effects of high volume upper extremity plyometric training on throwing velocity and functional strength ratios of the shoulder rotators in collegiate baseball players. The Journal of Strength & Conditioning Research, 21, 208–215. Cavanagh, P. R. & Komi, P. V. 1979. Electromechanical delay in human skeletal muscle under concentric and eccentric contractions. European Journal of Applied Physiology & Occupational Physiology, 42, 159–163. Chelly, M. S., Ghenem, M. A., Abid, K., Hermassi, S., Tabka, Z. & Shephard, R. J. 2010. Effects of in-season short-term plyometric training program on leg power, jump-and sprint performance of soccer players. The Journal of Strength & Conditioning Research, 24, 2670–2676. Chu, D. A. 1998. Jumping into Plyometrics. Champaign, IL: Human Kinetics. Di Giminiani, R. & Petricola, S. 2016. The power output-drop height relationship to determine the optimal dropping intensity and to monitor the training intervention. The Journal of Strength & Conditioning Research, 30, 117–125. Dietz, V., Schmidtbleicher, D. & Noth, J. 1979. Neuronal mechanisms of human locomotion. Journal of Neurophysiology, 42, 1212– 1222. Docherty, D., Robbins, D. & Hodgson, M. 2004. Complex training revisited: A review of its current status as a viable training approach. Strength & Conditioning Journal, 26, 52–57. Ebben, W. 2002. Complex training: A brief review. Journal of Sports Science & Medicine, 1, 42–46. Ettema, G. J., Huijing, P. A. & De Haan, A. 1992. The potentiating effect of prestretch on the contractile performance of rat gastrocnemius medialis muscle during subsequent shortening and isometric contractions. Journal of Experimental Biology, 165, 121–136. Fatouros, I. G., Jamurtas, A. Z., Leontsini, D., Taxildaris, K., Aggelousis, N., Kostopoulos, N. & Buckenmeyer, P. 2000. Evaluation of plyometric exercise training, weight training, and their combination on vertical jumping performance and leg strength. The Journal of Strength & Conditioning Research, 14, 470–476. Gordon, A. M., Huxley, A. F. & Julian, F. J. 1966a. Tension development in highly stretched vertebrate muscle fibres. The Journal of Physiology, 184, 143–169. Gordon, A. M., Huxley, A. F. & Julian, F. J. 1966b. The variation in isometric tension with sarcomere length in vertebrate muscle fibres. The Journal of Physiology, 184, 170–192. Harris, G. R., Stone, M. H., O’Bryant, H. S., Proulx, C. M. & Johnson, R. L. 2000. Short-term performance effects of high power, high force, or combined weight-training methods. The Journal of Strength & Conditioning Research, 14, 14–20. Herrington, L. 2010. The effects of 4 weeks of jump training on landing knee valgus and crossover hop performance in female basketball players. The Journal of Strength & Conditioning Research, 24, 3427–3432. Herrington, L., Munro, A. & Comfort, P. 2015. A preliminary study into the effect of jumping–landing training and strength training on frontal plane projection angle. Manual Therapy, 20, 680–685. Herrington, L. C. & Comfort, P. 2013. Training for prevention of ACL injury: Incorporation of progressive landing skill challenges into a
program. Strength & Conditioning Journal, 35, 59–65. Hill, A. 1938. The heat of shortening and the dynamic constants of muscle. Proceedings of the Royal Society of London B: Biological Sciences, 126, 136–195. Hodges, N. J. & Franks, I. M. 2004. Instructions, demonstrations and the learning process. Skill acquisition in sport: Research, theory and practice, 145–174. Jarvis, M. M., Graham-Smith, P. & Comfort, P. 2016. A methodological approach to quantifying plyometric intensity. The Journal of Strength & Conditioning Research, 30, 2522–2532. Jeffreys, I. 2007. Total Soccer Fitness, Coaches Choice. Kandel, E. R., Schwartz, J. H., Jessell, T. M., Siegelbaum, S. A. & Hudspeth, A. 2000. Principles of neural science, New York: McGraw-Hill. Khlifa, R., Aouadi, R., Hermassi, S., Chelly, M. S., Jlid, M. C., Hbacha, H. & Castagna, C. 2010. Effects of a plyometric training program with and without added load on jumping ability in basketball players. The Journal of Strength & Conditioning Research, 24, 2955–2961. Kilani, H., Palmer, S., Adrian, M. & Gapsis, J. 1989. Block of the stretch reflex of vastus lateralis during vertical jumps. Human Movement Science, 8, 247–269. Komi, P. V. 2000. Stretch-shortening cycle: A powerful model to study normal and fatigued muscle. Journal of Biomechanics, 33, 1197– 1206. Komi, P. V. 2008. Stretch-shortening cycle. Strength and Power in Sport, 3, 184–202. Kubo, K., Kawakami, Y. & f*ckunaga, T. 1999. Influence of elastic properties of tendon structures on jump performance in humans. Journal of Applied Physiology, 87, 2090–2096. Kubo, K., Morimoto, M., Komuro, T., Yata, H., Tsunoda, N., Kanehisa, H. & f*ckunaga, T. 2007. Effects of plyometric and weight training on muscle-tendon complex and jump performance. Medicine & Science in Sports & Exercise, 39, 1801–1810. Kryöläinen, H., Avela, J., McBride, J. M., Koskinen, S., Andersen, J., Sipilä, S., Takala, T. & Komi, P. 2005. Effects of power training on muscle structure and neuromuscular performance. Scandinavian Journal of Medicine & Science in Sports, 15, 58–64. Lichtwark, G. A. & Wilson, A. 2005. In vivo mechanical properties of the human Achilles tendon during one-legged hopping. Journal of Experimental Biology, 208, 4715–4725. Louder, T., Bressel, M. & Bressel, E. 2015. The kinetic specificity of plyometric training: Verbal cues revisited. Journal of Human Kinetics, 49, 201–208. Malisoux, L., Francaux, M., Nielens, H., Renard, P., Lebacq, J. & Theisen, D. 2006a. Calcium sensitivity of human single muscle fibers following plyometric training. Medicine & Science in Sports & Exercise, 38, 1901–1908. Maliscoux, L., Francaux, M., Nielens, H. & Theisen, D. 2006b. Stretch-shortening cycle exercises: An effective training paradigm to enhance power output of human single muscle fibers. Journal of Applied Physiology, 100, 771–779. Markovic, G. 2007. Does plyometric training improve vertical jump height? A meta-analytical review. British Journal of Sports Medicine, 41, 349–355. Markovic, G. & Mikulic, P. 2010. Neuro-musculoskeletal and performance adaptations to lower-extremity plyometric training. Sports Medicine, 40, 859–895. McBride, J. M., McCaulley, G. O. & Cormie, P. 2008. Influence of preactivity and eccentric muscle activity on concentric performance during vertical jumping. The Journal of Strength & Conditioning Research, 22, 750–757. McCaulley, G. O., Cormie, P., Cavill, M. J., Nuzzo, J. L., Urbiztondo, Z. G. & McBride, J. M. 2007. Mechanical efficiency during repetitive vertical jumping. European Journal of Applied Physiology, 101, 115–123. Minetti, A. E. 2002. On the mechanical power of joint extensions as affected by the change in muscle force (or cross-sectional area), ceteris paribus. European Journal of Applied Physiology, 86, 363–369. Myer, G. D., Ford, K. R., Brent, J. L. & Hewett, T. E. 2012. An integrated approach to change the outcome part II: Targeted neuromuscular training techniques to reduce identified ACL injury risk factors. The Journal of Strength & Conditioning Research, 26, 2272–2292. Ngahara, R., Naito, H., Miyashiro, K., Morin, J. & Zushi, K. 2014. Traditional and ankle-specific vertical jumps as strength-power indicators for maximal sprint acceleration. Journal of Sports Medicine & Physical Fitness, 54, 691–699. Norman, R. W. & Komi, P. V. 1979. Electromechanical delay in skeletal muscle under normal movement conditions. Acta Physiologica Scandinavica, 106, 241–248. Potach, D. H. & Chu, D. A. 2016. Program design and technique for plyometric training. In G. G. Haff & N. T. Triplett (Eds.), Essentials of strength training and conditioning. Champaign, IL: Human Kinetics, 471–520. Potteiger, J. A., Lockwood, R. H., Haub, M. D., Dolezal, B. A., Almuzaini, K. S., Schroeder, J. M. & Zebas, C. J. 1999. Muscle power and fiber characteristics following 8 weeks of plyometric training. The Journal of Strength & Conditioning Research, 13, 275–279. Radin, E. L. 1986. Role of muscles in protecting athletes from injury. Acta Medica Scandinavica, 711, 143–147. Saez-Saez de Villarreal, E., Kellis, E., Kraemer, W. J. & Izquierdo, M. 2009. Determining variables of plyometric training for improving vertical jump height performance: A meta-analysis. The Journal of Strength & Conditioning Research, 23, 495–506. Saez-Saez de Villarreal, E., Requena, B. & Cronin, J. B. 2012. The effects of plyometric training on sprint performance: A metaanalysis. The Journal of Strength & Conditioning Research, 26, 575–584.
Saez-Saez de Villarreal, E., Requena, B., Izquierdo, M. & Gonzalez-Badillo, J. J. 2013. Enhancing sprint and strength performance: Combined versus maximal power, traditional heavy-resistance and plyometric training. Journal of Science & Medicine in Sport, 16, 146–150. Saez-Saez de Villarreal, E., Requena, B. & Newton, R. U. 2010. Does plyometric training improve strength performance? A metaanalysis. Journal of Science & Medicine in Sport, 13, 513–522. Saunders, P. U., Telford, R. D., Pyne, D. B., Peltola, E. M., Cunningham, R. B., Gore, C. J. & Hawley, J. A. 2006. Short-term plyometric training improves running economy in highly trained middle and long distance runners. The Journal of Strength & Conditioning Research, 20, 947–954. Schulte-Edelmann, J. A., Davies, G. J., Kernozek, T. W. & Gerberding, E. D. 2005. The effects of plyometric training of the posterior shoulder and elbow. The Journal of Strength & Conditioning Research, 19, 129–134. Spurrs, R. W., Murphy, A. J. & Watsford, M. L. 2003. The effect of plyometric training on distance running performance. European Journal of Applied Physiology, 89, 1–7. Stone, M. H., Stone, M. E. & Sands, W. A. 2007. Principles and Practice of Resistance Training. Champaign, IL: Human Kinetics. Struminger, A. H., Lewek, M. D., Goto, S., Hibberd, E. & Blackburn, J. T. 2013. Comparison of gluteal and hamstring activation during five commonly used plyometric exercises. Clinical Biomechanics, 28, 783–789. Suchomel, T. J., Nimphius, S. & Stone, M. H. 2016. The importance of muscular strength in athletic performance. Sports Medicine, 46, 1419–1449. Talpey, S., Young, W. & Beseler, B. 2016. Effect of instructions on selected jump squat variables. The Journal of Strength & Conditioning Research, Publish Ahead of Print, 10.1519/JSC.0000000000000435. Turner, A. M., Owings, M. & Schwane, J. A. 2003. Improvement in running economy after 6 weeks of plyometric training. The Journal of Strength & Conditioning Research, 17, 60–67. Turner, A. N. & Jeffreys, I. 2010. The stretch-shortening cycle: Proposed mechanisms and methods for enhancement. Strength & Conditioning Journal, 32, 87–99. Váczi, M., Rácz, L., Hortobágyi, T. & Tihanyi, J. 2013. Dynamic contractility and efficiency impairments in stretch-shortening cycle are stretch-load-dependent after training-induced muscle damage. The Journal of Strength & Conditioning Research, 27, 2171–2179. Vissing, K., Brink, M., Lønbro, S., Sørensen, H., Overgaard, K., Danborg, K., Mortensen, J., Elstrøm, O., Rosenhøj, N. & Ringgaard, S. 2008. Muscle adaptations to plyometric vs. resistance training in untrained young men. The Journal of Strength & Conditioning Research, 22, 1799–1810. Walsh, M., Arampatizs, A., Schade, F. & Bruggemann, G.-P. 2004. The effect of drop jump starting height and contact time on power, work performed, and moment of force. The Journal of Strength & Conditioning Research, 18, 561–566. Wilk, K. E., Voight, M. L., Keirns, M. A., Gambetta, V., Andrews, J. R. & Dillman, C. J. 1993. Stretch-shortening drills for the upper extremities: Theory and clinical application. Journal of Orthopedic & Sports Physical Therapy, 17, 225–239. Wilt, F. 1978. Plyometrics: what it is and how it works. Modern Athlete & Coach, 12–19. Wulf, G. 2007. Attention and Motor Skill Learning, Human Kinetics. Young, W. B., Pryor, J. F. & Wilson, G. J. 1995. Effect of instructions on characteristics of countermovement and drop jump performance. The Journal of Strength & Conditioning Research, 9, 232–236. Zamparo, P., Minetti, A. E. & Di Prampero, P. E. 2002. Interplay among the changes of muscle strength, cross-sectional area and maximal explosive power: Theory and facts. European Journal of Applied Physiology, 88, 193–202.
CHAPTER 17
Training change of direction and agility Sophia Nimphius INTRODUCTION The athletic ability demonstrated when rapidly changing direction is considered a highly advantageous quality in an athlete, particularly but not limited to evasion sports both on the field or court. However, despite the increasing research into change of direction ability from a performance and injury perspective, there is still little consensus on the development of this ‘elusive’ physical quality. However, there has been a substantial advancement in the understanding of the biomechanical underpinnings of changing direction and the influence of perceptual-cognitive factors that combine for the perceptual-motor response known as agility. This chapter aims to provide an overview of the current research and scientific understanding of factors associated with change of direction and agility with respect to biomechanical, physical and perceptual-cognitive determinants (Section 1). In Section 2, an applied understanding of how to quantitatively and qualitatively evaluate change of direction ability and agility will be examined, followed by an example of a needs-based program in conjunction with a developmental framework designed to combine improvements in physical capacity with skill development.
SECTION 1 DEFINITIONS Over the last two decades, more clarity on definitions associated with change of direction research has culminated. However, there is still ambiguity of term use both in the research and applied fields. Therefore, the current chapter will use the following definitions and terms in addition to their abbreviations. Change of direction (COD) – the skills and abilities needed to change movement direction, velocity or modes (DeWeese and Nimphius, 2016). Describes the physical event of changing direction and may be used independent of the situation (e.g., ‘pre-planned’ or ‘reactive’) as ultimately a COD still occurs. The COD may be further defined as the events that occur just prior (entry), at the ‘plant’ (occurring between entry and exit) and just following (exit) when describing the typical ‘cutting’ COD movement. This will form the focus of the biomechanical analysis of COD section of this chapter. Change of direction speed (CODS) – overarching description of any test that proposes to examine one’s ‘pre-planned’ COD ability (e.g., T-test, 505, Illinois agility test, pro-agility test) that often has a large component of straight line running. Maneuverability – a further delineation of COD where the purpose of the change in direction is to maintain velocity, therefore eliminating a clearly defined ‘plant’ step associated with a ‘cutting’ COD and subsequently eliciting a more curvilinear path of movement. Further, maneuverability may also be used to describe a COD when one changes mode of travel and the purpose may be tactical movement preference (e.g., COD into a backpedal or shuffle) (Nimphius et al., 2017, Nimphius, 2014). Agility – ‘a rapid whole-body movement with change of velocity or direction in response to a stimulus’ (Sheppard and Young, 2006). As such, an agility maneuver is predicated on a stimulus-response, but the subsequent movement may take the form of any of the aforementioned methods by which one changes direction.
BIOMECHANICS OF CHANGING DIRECTION Although the biomechanics of changing direction could be considered complex, the principles that govern human motion allow for a narrowing of the critical factors required for rapid and efficient COD. Therefore, the commonly measured variables of velocity, force, impulse, ground contact time and momentum can provide a comprehensive understanding of the critical factors relevant to changing direction. With a sound biomechanical understanding, one has the fundamental knowledge required to better understand the interaction of physical capacity and technical or skill requirements that must be present in combination to maximize any COD performance. To begin this discussion of the biomechanics during a COD, a ground-up approach will be adopted, commencing with a description of impulse and ground contact times, followed by a discussion on joint kinematics and kinetics
associated with a COD.
Understanding impulse and ground contact times during a change of direction The ‘plant’ phase, which as previously described, is the step that is most unique in comparison to the mechanics associated with sprinting. Although the plant step is still a stance phase, the term ‘plant’ is chosen to differentiate it from other steps. Specifically, the plant phase is distinctive as it is the instance of transition often including both a braking and propulsive component with typically longer (and intentional) deceleration (braking) followed by acceleration (propulsive) within the force-time (or impulse) curve as shown in Figure 17.1 in comparison to the stance phase during sprinting. However, the plant phase during a COD will vary depending on the velocity of entry (Nedergaard et al., 2014) and the angle of required change of direction (Havens and Sigward, 2015b), which may result in an increase or decrease in the ground contact time for which the plant phase occurs. Therefore, as one considers the different shapes of the curves shown in Figure 17.1, one can also appreciate the different magnitudes and durations of impulse which determine the subsequent change in momentum and therefore velocity as defined by the impulse-momentum theorem. The height of the impulse curve represents the amount of force produced during the plant phase, whereas the width of the impulse curve determines the time one has to apply this force (associated with the rate of force development within the context of a COD). As such, the magnitude of force required or produced and the time available for producing this force can subsequently be used to understand the physical requirements to perform the COD. Further, the change in momentum and subsequent velocity and actual angle of COD that results will be a function of the direction of force application, and the effectiveness of the produced impulse will be expected to be similar to that of sprinting (Rabita et al., 2015). Examples of the time available or time required to execute various changes of direction are described in Table 17.1. As the angle of COD increases, the ground contact time often increases, providing differences in time available to create force that could be considered analogous to comparing time available for a countermovement jump versus a drop jump (Nimphius et al., 2017).
FIGURE 17.1
Example of force-time curve of the plant phase of a 45° COD and a stance phase of a maximal velocity sprint. The vertical dashed lines represent the distinction between the braking and propulsion phases as defined by the anteriorposterior force. Further, notice the difference in the length of these phases and the total ground contact time. The total area under each curve is the impulse.
However, it should be understood that a proportion of the deceleration often occurs prior to the plant step (e.g., penultimate step or prior) (Nedergaard et al., 2014, Havens and Sigward, 2015b), explaining why the plant step doesn’t always fully quantify the demand of greater angle directional changes or why some directional changes can have equal or lesser ground contact times than more shallow changes of direction. For example, substantial braking in the steps prior to the plant step have been shown prior to 135° COD (Nedergaard et al., 2014) and 180° COD (Graham-Smith et al., 2009). The prior deceleration is likely a strategy to decrease the difficulty and ground contact time spent changing direction, otherwise ground contact times may extend as shown to occur when prior deceleration is not possible as with a sudden response to a stimulus (Spiteri et al., 2015a) and shown in Table 17.1. Further, additional acceleration occurs following the plant step, which is critical to subsequent success following the COD. TABLE 17.1 Ground contact times during various angles of change of direction
Reference
Description of change of direction
(Havens and Sigward, 2015b)
~ 45° COD during planned task
(Vanrenterghem et al., 2012)
~ 45° planned task (measured actual angles 39.5° to 25.5°) at various velocities m.s–1);
(between 2 m.s–1
Mean ground contact times (s) 0.16 0.20–0.45
to 5
as velocity increased angle of actual performance decreased and ground contact time decreased
(Spiteri et al., 2014a)
~ 45° COD during agility task from both offensive and defensive conditions with human stimulus
0.23–0.26
(Spiteri et al., 2015a)
~ 45° COD during agility task with video stimulus
0.42–0.51
(Marshall et al., 2014)
~ 75° COD during planned task
0.37
(Havens and Sigward, 2015b)
~ 90° COD during planned task
0.25
(Spiteri et al., 2015a)
~ 90° COD during planned task with transition into a shuffle
0.32–0.35
(Spiteri et al., 2015a)
~ 180° COD during planned task
0.42–0.47
One may, therefore, have to consider the steps entering, the characteristics of the plant step and the steps exiting a COD when assessing the biomechanics of performance, while still ensuring the assessment appropriately isolates the biomechanics surrounding the actual COD instead of a reevaluation of sprint acceleration ability. As discussed by Havens and Sigward (2015b), the approach step (penultimate step) and execution step (plant step) have significantly slower velocities during a 90° COD than during a 45° COD. Therefore, biomechanical factors such as velocity of entry and angle of COD have clear implications for differences in physical requirements for the different ranges of COD performance required in sport. This will be discussed later in this chapter. Although largely not discussed in research (Nimphius et al., 2017), the mass of the athlete should be considered in addition to the aforementioned critical factors of velocity and angle of change of direction. More recent research has highlighted the consideration for calculating what is termed ‘sprint momentum’ for rugby athletes whereby the maximal velocity of an athlete is multiplied by their body mass to determine their momentum, which is considered influential for aspects of sport performance such as breaking tackles (Hendricks et al., 2014, Baker and Newton, 2008). Therefore, within the context of a COD, the velocity of the athlete exiting a COD or the momentum an athlete carries into a COD (entry velocity multiplied by body mass) are factors that practitioners should consider within the biomechanical requirements of an individual athlete’s performance, when applicable.
Joint kinematics and kinetics during a change of direction The discussion of joint kinematics and kinetics during a COD with respect to injury risk has been researched extensively in the literature (Kristianslund et al., 2014, McLean et al., 2004, Jones et al., 2015, Imwalle et al., 2009). However, there is acknowledgement that some joint positions that may create unfavorable loads with respect to injury risk may also be advantageous for performance (Jones et al., 2015) or necessary for task completion (Havens and Sigward, 2015a), but this has yet to be fully understood. Further complications arise when understanding that although expected changes in
whole body centre of mass (COM) occurs when comparing a more shallow COD (45°) versus a more aggressive COD (90°), simultaneous increased physical demand is not evenly evident across all joints (Havens and Sigward, 2015a). Of critical understanding from the research of Havens and Sigward (2015b) is the unique finding that the deceleration demand of the 90° COD in comparison to the 45° COD resulted in different hip functions where the hip seemed to primarily stabilize the trunk during the 90° COD. Further, the aforementioned research highlighted differences in these two COD demands where far greater pelvis rotation occurred during the 90° COD and a trend to larger moments and power absorption at the knee (Havens and Sigward, 2015a) also occurred, likely in response to the increased deceleration demand and hip control requirements in handling the increased trunk lean during the 90° COD. Therefore, it is clear that a specific recommendation for a representative kinematic description of ‘good change of direction’ is likely not possible due to the vast combinations of requirements during changes of directions at different angles that occur at multiple velocities in sport. Additionally, the movement of the athlete during the COD must also be described in context of the requirements of the situation and taken relative to the position the athlete is in at the time of the COD, while also recognizing that more recent research is moving away from the notion of an ‘ideal’ movement for success (Lee et al., 2014). The kinematics or ‘technique’ for success in COD can therefore be considered vast and continually changing with respect to the constraints of the physical, perceptual-cognitive and tactical context of COD. These are analogous to the dynamical systems theory application of constraints within physical, mental and social contexts (Latash, 2008). As such, this chapter will focus on COD development through discussions of the task and goal, instead of an overemphasis on technique (Lee et al., 2014), in an effort to reach multiple movement solutions (kinematics) that result in successful COD. More broad recommendations, however, can be summarized across research that may describe COD movements independent of velocity or angle, with the expectation that the chosen movement will occur with respect to muscle strength, mobility and anthropometry and therefore recommended changes must be considered within that context as well. Technical guidelines have previously been summarized across the areas of visual focus, body positions through deceleration and acceleration, leg action and arm action (DeWeese and Nimphius, 2016). These include use of the trunk during lateral movement (Sasaki et al., 2011) or when there is greater deceleration demands and subsequent increased change in body momentum (Havens and Sigward, 2015a, Havens and Sigward, 2015b), the orientation of the hips toward the direction of travel (Havens and Sigward, 2015a), and good joint alignment of the hip, knee and ankle (DeWeese and Nimphius, 2016) with consideration that some actions, such as increased trunk lean, hip abduction and hip internal rotation, may be necessary for successful completion of more aggressive COD (Havens and Sigward, 2015a). Some of these requirements are often seemingly contrary to suggestions of reducing frontal and transverse movements in an effort to minimize knee adductor moments (Dempsey et al., 2007). However, one must consider successful movement requires loading, and increased capacity and minimization of extremes within these movements are likely more applicable than recommended avoidance to ensure the COD can be successful in the reality of a sporting context. In conclusion, the joint positions and joint moments that are advantageous for performance are only beneficial if the capacity of the athlete is high enough to tolerate those joint moments without subsequent failure or injury occurring in conjunction with successful performance. Further, the description of the ground contact times required at various angles and velocities vary in magnitude but still contain defined ranges which individuals can use to determine subsequent training
requirements. The ground reaction forces (magnitude and direction) required for effective change of momentum during a COD may be produced using multiple joint configurations that are constantly changing due to the physical, perceptual-cognitive and tactical considerations that must be considered.
UNDERPINNING FACTORS RELATED TO CHANGE OF DIRECTION Inherent to the performance of an effective and efficient COD is having the underpinning physical capacities to perform the technical requirements of the COD. As has been highlighted in the introduction of this chapter, each COD has unique characteristics, and therefore will require varying levels of the different physical capacities. Several models of agility have been proposed (Young et al., 2002, Nimphius, 2014), but each result in different requirements and therefore demand a different approach to physical development. Therefore, the current chapter uses a different approach whereby considerations for the types of COD as the overarching commonality are split into different purposes (see definitions). With such an approach, it is also acknowledged that when these performances occur in response to situation or opponent, there are several perceptual-cognitive factors that can interact with the perceptual-motor response and subsequent successful or unsuccessful execution of the COD. It is the ability of the athlete to absorb force (braking) and produce force (acceleration) while controlling the body position between and during these phases of movement that are critical in a COD typically performed for evasion. Factors already considered critical for speed are most applicable when a COD is intended to maintain velocity and unique movement, and ability demands influence change of direction into a new mode of travel such as a shuffle, both termed maneuverability in this chapter. If the strength capacity of the athlete is effectively utilized and coordinated within the constraints of the activity, then success is more likely. Such delineation could be described as the difference between ability and skill. Therefore, the next section will focus on the abilities, termed physical capacities, that are important to further enhance skill development of the COD. The subsequent section will then discuss the current understanding of perceptual-cognitive underpinnings of agility.
Physical capacities underpinning change of direction While maximal strength has been commonly associated with many aspects of sport performance including sprinting and CODS (Suchomel et al., 2016), it should be recognized that the force applied during a COD occurs over a range of ground contact times (see Table 17.1) and over different phases: braking and propulsion. Therefore, the length of time available and characteristics of the COD (see Table 17.1) lend itself to be more associated with eccentric, isometric or concentric strength and relative to the time available (Nimphius, 2014) than just one measure of strength (e.g., a typical onerepetition dynamic performance). Although it is clear that dynamic strength is largely correlated to the specific sub-component measures of strength – isometric, concentric and eccentric (Spiteri et al., 2014b) – the relationship is not perfect, and therefore indicates these sub-qualities of strength can develop at different rates or magnitudes. As highlighted, the required contribution of each sub-quality of strength varies depending on the type of COD required and current physical capacities of the athlete (Spiteri et al., 2015a). Rate of force development, reactive strength or fast and slow stretch-shortening cycle (SSC)
activities (including drop jumps, countermovement jumps and loaded jumps) are also important physical capacities for enhancement of the multi-factorial physical attributes that underpin COD. The reason for an emphasis early in the chapter on ground contact time is to highlight that a COD, where the ground contact time is very short, is likely to be more related to capacities related to fast SSC activities, whereas those with longer ground contacts will benefit from improved longer SSC activities. For example, in shallow cuts or those in response to stimulus where a sudden foot-ground interaction may occur, drop jump performance or reactive strength would be considered relevant to performance, particularly as the increased eccentric phase muscle activity during a drop jump (McBride et al., 2008) could be paralleled to the pre-activity of shallow angle cut agility tasks (Spiteri et al., 2015b). On the other hand, when there is a greater angle of COD, either for evasion or required due to angle, the braking involved results in a longer ground contact, and is therefore likely to be more related to maximal strength (Suchomel et al., 2016), specifically eccentric strength (Jones et al., 2009), and can be improved using higher load, longer SSC activities (McBride et al., 2002). It is acknowledged, however, that having these physical attributes do not guarantee enhanced COD performance, hence why the association between strength and COD performance often only explains a portion of variance, or can change as an athlete develops (Nimphius et al., 2010). Further, one must also learn to utilize increases in strength within the context of the activity (Suchomel et al., 2016), therefore, consideration should be made for the expected delay or lag time between increased physical capacity and ability to actualize the improvement in performance (Stone et al., 2003, Nimphius, 2010). In conclusion, there are several interacting physical capacities and inherent anthropometric characteristics that combine during a successful COD, and the underpinning capacities required are dependent on the type of COD being performed.
Perceptual-cognitive factors underpinning agility Although a motor response must occur during all COD, most agility manoeuvres are typified by the description of a rapid stimulus-response scenario, and such a scenario is typical of a majority of tests designed to assess agility (Paul et al., 2016). The decisions that occur in response to a defensive shift, open space or one-on-one scenario in sport require individuals to combine perceptual-cognitive factors (visual scanning, anticipation, pattern recognition, knowledge of situation, reaction time) with a motor response, which in combination can be termed perceptual-motor ability. As such, perceptualcognitive skill is a function of perception and understanding, while ultimately what one is able to perceive and do with action is what allows for successful execution (Starkes et al., 2004). This circling requirement back to motor response is why the process for understanding and developing COD and agility has started with the motor or physical capacities to ensure a base is present to build from. Such a concept is supported by research demonstrating that although one may make a correct decision (perpetual-motor decision), if they are less skilled they may fail to execute this decision despite making the correct one in the context of the situation (Bruce et al., 2012). Although all of the described perceptual-cognitive factors can be justified as critical to agility performance, current agility tests only allow limited use of the knowledge of situation, visual scanning and pattern recognition, and therefore are likely more confined to understanding one-on-one scenarios. Skills sessions using open-ended games, varying playing space and active defenders (Farrow and Robertson, 2016) will likely provide a better environment to improve visual scanning, anticipation, pattern recognition and situational knowledge, including evaluating the execution of the perceptual-motor response. This is because the likelihood of their transfer to the game would be
considered environmentally and tactically specific. Direct one-on-one scenario training may benefit from targeted training surrounding identifying movement cues to predict movement (Serpell et al., 2011). However, future developments attempting to improve the underpinning processing speed (visual information processing speed and multifocal attention skills) separate to the perceptual-motor response or execution may have promise, but have only been recently evaluated in a few sports (Mangine et al., 2014, Romeas et al., 2016).
SCIENTIFIC RESEARCH AND CURRENT APPLIED PRACTICE The previous sections that have provided a basis of understanding about the biomechanics of changing direction and the physical and perceptual-cognitive factors that underpin one’s ability to produce the kinetics and display the kinematics associated with superior COD are limited to the findings of research to date. There are strengths and weaknesses of the methodological approaches taken thus far that leave much more to be discovered and understood. As a scientist and practitioner, understanding these limitations and placing them into context will allow you to make informed practice decisions. For example, the validity of many of our CODS and agility measurements have been called into question due to many of these tests being focused upon a metric of ‘total time to complete’ as they measure one’s COD ability (Nimphius et al., 2017, Nimphius et al., 2016b, Sayers, 2015). Although a single measure of COD performance does not exist due to the overarching fact that COD performance is angle dependent (Buchheit et al., 2012, Hader et al., 2015) and velocity dependent (Vanrenterghem et al., 2012), a measure more relevant to the purpose of the COD being performed could be evaluated. For example, the evaluation of COD performance must consider the entry velocity of the athletes into the COD and exit velocity out of the COD (Spiteri et al., 2013), in addition to the time taken to actually change direction (ground contact time of plant phase), the direction of the velocity change for evasion and potentially even the momentum during the COD (Nimphius et al., 2017). All these provide more information than the typical ‘total time’ measure. A valid measure of COD and agility based on their definitions should accurately assess the change in direction, velocity or mode, and, as suggested by Sheppard and Young (2006), should represent a distinct physical quality. Despite this understanding, as previously noted, research has primarly used ‘total time’ without consideration of the large to very large correlations with straight-line running speed observed in the research (Gabbett et al., 2008, Nimphius et al., 2013, Nimphius et al., 2010). Although there are many other limitations that could be discussed about current research into COD ability, the potential to improve on the meaure that best represents this quality may well be the most outstanding limitation to consider. There is some research that has taken a potentially more valid approach to evaluating COD ability by assessing an individual’s center of mass during a COD (Wheeler and Sayers, 2010, Sayers, 2015, Hader et al., 2015, Spiteri and Nimphius, 2013). It is therefore possible that future research using this more direct measure of how well a person changes direction may change or at least advance our current knowledge on the topic. The primary reason for such a conclusion is that it has been demonstrated that the chosen measure of COD performance can influence the conclusion made. Specifically, previous research conclusions have shown to be altered depending on the metric used as the ‘measure of COD ability’. For example, Nimphius et al. (2016b) compared the use of a traditional ‘total time’ measure of performance and the COD deficit during the 505 COD test, demonstrating that the metric chosen to evaluate COD changed
the perceived COD ability of the athlete in more than 88% of the athletes assessed. More relevant to the comparison of total time to entry or exit velocity were the alternate conclusions that total time was not sensitive enough to detect significant differences in stronger and weaker athletes, while there was a significant difference in exit velocity of strong and weaker athletes (Spiteri and Nimphius, 2013). These issues hold true with agility testing as well. Further, agility tests still require improvements in ecological validity, as one should acknowledge the current tests mostly focus on one-on-one scenarios, and should consider multiple players, alternative visual perspective and deceptive actions (Paul et al., 2016) to allow for better evaluation of a larger number of the perceptual-cognitive factors (see Figure 17.2) of agility. Gathering all of this information within a practical setting would be complex and time consuming, therefore recommendations will be made with respect to the method of timing or variable to represent performance, choosing a COD test and considerations for agility tests within the context of a typical practitioner in Section 2.
SECTION 2 QUANTITATIVE EVALUATION OF CHANGE OF DIRECTION AND AGILITY PERFORMANCE There is still more to be understood as more isolated measures become common in both applied and scientific settings when assessing COD ability. The complexity of COD assessment is that a COD is performed for multiple purposes. Therefore the ‘metrics’ may change based on the purpose, hence why there will likely never be a single, ideal measure of COD performance. Practitioners drawing conclusions from research must first determine the purpose of the knowledge they require. Therefore, one should determine if they require knowledge on best evasion ability, ability to maintain velocity, ability to tolerate the most demanding braking requirements or to assess general physical capacity to perform a COD at various angle range(s) before generalizing the results and conclusions. A recent review of the most common CODS and agility tests with information on the length of test, angle of COD and number of COD can be sought in existing literature (Nimphius et al., 2017) and may be useful in addition to abbreviated information in Table 17.2. To understand how to choose an appropriate COD assessment, one should first compare the common CODS tests or agility tests and classify them into the more specific delineations under the larger umbrella of ‘COD’ that have been defined in this chapter. Therefore, Table 17.2 has been expanded upon from previous examples of classifying different CODS and agility tests (Nimphius, 2014, DeWeese and Nimphius, 2016). One can draw information from this table on whether a test is evaluating multiple attributes, is long in length and therefore may be confounded by anaerobic capacity if being assessed before and after a training block and the angle changes that occur. Such a classification can be performed on any existing or created CODS or agility test. With an understanding of the current CODS tests and their ‘classification’, or different factors that influence the result, one can begin to improve or select better metrics to identify COD performance. As discussed, one should try to isolate the COD performance intended to measure. A simplified approach to assessing COD performance has recently been proposed (Nimphius et al., 2016a) where a single COD of various angles are performed over the same distance and then a change of direction deficit can be calculated (Nimphius et al., 2016b, Nimphius et al., 2013). Suggestions to measure the COD performance over shorter distances that surround the actual COD (Sayers, 2015), or the aforementioned COD deficit (Nimphius et al., 2016b), are attempts to practically solve an issue whereby the measure (total time) is not isolating or reflecting the actual performance (COD) intended to be measured. When more equipment is available, it is likely the most accurate method to assess COD performance will be to evaluate the COM of an athlete during the COD as performed using three-dimensional motion analysis (Havens and Sigward, 2015b, Wheeler and Sayers, 2010, Sayers, 2015) or using laser distance meters (Hader et al., 2015). However, these techniques are less readily available than timing gates, hence suggestions of more practical methods of assessing COD performance. An example of an athlete’s assessment is provided in Figure 17.2 with a summary of standardized performance (using a z-score) across several physical capacity assessments and different measures of COD that were considered relevant for this athlete. This information will be used in the section ‘Programming to improve change of direction and agility’ as an exemplar of developing a program using performance results.
TABLE 17.2 Example classification of existing change of direction speed and agility tests
Note: Data and information is modified from (Nimphius et al., 2017)
QUALITATIVE EVALUATION OF CHANGE OF DIRECTION AND AGILITY PERFORMANCE A majority of evaluation of COD is focused on quantitative measures. However, coaches should consider evaluating the quality of the COD or the strategy of athletes performing a COD in conjunction with the quantitative measures. Of particular importance is a qualitative assessment of athletes returning to play following an injury. Athletes will often find a method to ‘beat or pass a test’ lending them to focus more on the goal than the process, and with athletes returning from injury this process may involve strategies that are avoidant of the previously injured limb. If observed, it can be called into question whether that athlete has successfully proven their ability to withstand the loading during the chosen COD test, or whether they are psychologically confident in the capacity of the previously injured limb, both reasons indicating an athlete may not be ready for a full return to play.
FIGURE 17.2
Example assessment of COD and physical capacity. To demonstrate the difference between total time and COD deficit measures, both assessments have been provided.
FIGURE 17.3
Qualitative assessment of COD performance during a 180° COD. This figure is modified from the following article, so if required, you may reference (Nimphius et al., 2017).
An example of different observations after return to play can be seen in Figure 17.3 with a comparison of a 180° COD during a traditional 505 on the right and left sides. The right leg of this athlete underwent an ACL reconstruction surgery approximately two years prior to this testing. Performance measures include: total 505 time and COD deficit (505 time – maximal 10m sprint time). Further, the percentage difference between right and left sides is shown in the table. This athlete is well above team mean performance, which may have led a coach to not be overly concerned with assessing technical differences in the COD. However, with this athlete, technical differences provide vast information beyond the discrete time measures. Notice the differences in the strategy as they preferentially load the left leg while changing direction, the ‘right’ side has less effective body position as a result of ineffective load absorption (compare position at 0.64s), and the result is a less effective COD as they would still be ‘present to be tackled’ at 1.10s when turning on the ‘right’ side. Such a qualitative analysis would lend one to ensure the athlete has adequate capacity building and potentially some task constraints in their drills to ensure she loads and develops strategies for a COD on either side. Athletes can avoid movement strategies in planned scenarios; however, if they present these movement strategies in planned tests they may be at risk in scenarios where they can’t use their preferred strategy, which is why some closed drills with tasks and constraints are critical for athlete development and return to play. This will be discussed in the next section when discussing ‘inside and outside leg loading’ as an example of a closed drill with constraints that still allow for movement solutions to be created, but with more targeted loading strategies from a capacity building and accountability stand point.
CAPACITY BUILDING AND SKILL ENHANCEMENT: A MODEL OF COD DEVELOPMENT The development of physical capacity should be considered in association with skill development, and different stages of the development process will have a greater emphasis on physical capacity development versus skill development. However, as discussed in Figure 17.4, the emphasis constantly shifts, and development is never considered all physical or all skill as they are intimately linked. It is suggested that coaches should utilize a constraints-led approach (Davids et al., 2008) in an effort to increase the number of movement solutions an athlete is required to have for the same
‘drill’. For example, an athlete performing a ‘back door cut’ can load their inside or outside leg (i.e., plant leg) to a greater degree, however, both scenarios are common in sport (e.g., leading a defender versus reacting as a defender) even though one will likely be the ‘faster’ performance. Exposing the athlete to a range of solutions by setting constraints, e.g., touching a hurdle while concurrently restricting how close they can get to it (forcing them to reach and load the outside leg) allows for several solutions using the same drills (e.g., ‘back door cut’ or 180° turn). As a result, the focus can be on the development of a movement solution instead of ‘learning the drill’. This ‘repetition without repetition’ is indeed the context of the dynamical systems approach discussed by Bernstein (1967) and highlighted in the proposed model of COD development in Figure 17.4. In addition, the organization of skills practice should be considered within the context of the skill level of the performer and purpose of the phase. It is also important to ensure a shift from block to serial to random practice (Farrow and Robertson, 2016), while also considering the aspects of building capacity versus enhancing skill. Furthermore, it is important to consider the appropriate amount of time to utilize tasks and constraints to increase contextual interference in an effort to enhance skill learning in COD. This holds true during ‘pre-planned or controlled’ and ‘reactive’ environments (as summarized in Figure 17.4). Further, actualization of training from improving physical qualities into skilled movement can be affected by the instruction provided by the coach. Within CODS research, it has been shown that externally focused attention, where one provides instruction that focuses attention on the environment, improves timed performance (Porter et al., 2010). However, a greater understanding of the influence of training experience has indicated that in sprinting (as sprint speed is a large part of the CODS tests currently utilized) either a normal focus or external focus was beneficial in comparison to internal focus for moderate level sprinters. However, as experience level increased, the benefit of external versus internal focus declined likely due to their highly developed implicit motor plans (Winkelman et al., 2017). Therefore, when considering the daily training environment for COD development, coaches should consider the purpose of the session followed by choosing the best practice environment (e.g., blocked versus random), level of contextual interference and the type of feedback or instruction that is most appropriate to achieve the purpose relative to the expertise of the group being trained.
FIGURE 17.4
Proposed change of direction development model.
PROGRAMMING TO IMPROVE CHANGE OF DIRECTION AND AGILITY As was originally presented in Figure 17.2, the assessment of an athlete can determine the focus of the subsequent training blocks that will follow the conceptual model of Figure 17.4. By assessing the athlete appropriately, one can ensure the training is targeting an area that requires improvement. A needs analysis should be performed for the sport of the athlete followed by the strength and weakness assessment. Next, one will usually identify a primary and secondary need of the athlete and then create a plan by distributing the time available based on need. For this example, we will proceed with the information provided as per Figure 17.5. This plan outlines the strengths and weakness of the athlete based upon the data in Figure 17.2, and then identifies the primary and secondary emphasis with a proposed time distribution focus for the current block and how this may change over the subsequent blocks as the athlete develops. Further, an example single session is provided to demonstrate how to use the COD development model to determine not only the long-term but also the daily training process.
SUMMARY To effectively develop and enhance COD ability, it is critical to accurately identify the strengths and weaknesses underpinning COD performance in combination with understanding how well the athlete utilizes their physical attributes within the context of the skilled performance of changing direction. A mixed method qualitative and quantitative approach to evaluation followed by a progressive development that aims to enhance the transfer of underpinning physical attributes to their use in the
technically demanding aspects of changing direction is recommended. Through effective planning and use of both capacity building and skill development processes, an athlete can improve this often underdeveloped and misunderstood athletic quality.
FIGURE 17.5
Example program from needs analysis through to long-term planning for subsequent blocks of training.
REFERENCES Baker, D. G. & Newton, R. U. 2008. Comparison Of Lower Body Strength, Power, Acceleration, Speed, Agility, And Sprint Momentum To Describe And Compare Playing Rank Among Professional Rugby League Players. The Journal Of Strength & Conditioning Research, 22, 153. Bernstein, N. A. 1967. The Co-Ordination And Regulation Of Movements. Bruce, L., Farrow, D., Raynor, A. & Mann, D. 2012. But I Can’t Pass That Far! The Influence Of Motor Skill On Decision Making. Psychology Of Sport And Exercise, 13, 152–161. Buchheit, M., Haydar, B. & Ahmaidi, S. 2012. Repeated Sprints With Directional Changes: Do Angles Matter? Journal Of Sports Sciences, 30, 555–562. Davids, K. W., Button, C. & Bennett, S. J. 2008. Dynamics Of Skill Acquisition: A Constraints-Led Approach. Champaign, IL: Human Kinetics. Dempsey, A. R., Lloyd, D. G., Elliott, B. C., Steele, J. R., Munro, B. J. & Russo, K. A. 2007. The Effect Of Technique Change On Knee Loads During Sidestep Cutting. Medicine & Science In Sports & Exercise, 39, 1765–1773. Deweese, B. & Nimphius, S. 2016. Speed And Agility Program Design And Technique. In: Triplett, N. T. & Haff, G. G. (Eds.) Essentials Of Strength And Conditioning. 5th Ed. Champaign, IL: Human Kinetics.
Farrow, D. & Robertson, S. 2016. Development Of A Skill Acquisition Periodisation Framework For High-Performance Sport. Sports Medicine, 1–12. Gabbett, T. J., Kelly, J. N. & Sheppard, J. M. 2008. Speed, Change Of Direction Speed, And Reactive Agility Of Rugby League Players. The Journal Of Strength & Conditioning Research, 22, 174–181. Graham-Smith, P., Atkinson, L., Barlow, R. & Jones, P. Braking Characteristics And Load Distribution In 180° Turns. Proceedings Of The 5th Annual UK Strength And Conditioning Association Conference, 2009. Hader, K., Palazzi, D. & Buchheit, M. 2015. Change Of Direction Speed In Soccer: How Much Braking Is Enough? Kinesiology, 47, 67–74. Havens, K. L. & Sigward, S. M. 2015a. Joint And Segmental Mechanics Differ Between Cutting Maneuvers In Skilled Athletes. Gait & Posture, 41, 33–38. Havens, K. L. & Sigward, S. M. 2015b. Whole Body Mechanics Differ Among Running And Cutting Maneuvers In Skilled Athletes. Gait & Posture, 42, 240–245. Hendricks, S., Karpul, D. & Lambert, M. 2014. Momentum And Kinetic Energy Before The Tackle In Rugby Union. Journal Of Sports Science And Medicine, 13, 557. Imwalle, L. E., Myer, G. D., Ford, K. R. & Hewett, T. E. 2009. Relationship Between Hip And Knee Kinematics In Athletic Women During Cutting Maneuvers: A Possible Link To Noncontact Anterior Cruciate Ligament Injury And Prevention. The Journal Of Strength & Conditioning Research, 23, 2223–2230. Jones, P., Bampouras, T. M. & Marrin, K. 2009. An Investigation Into The Physical Determinants Of Change Of Direction Speed. Journal Of Sports Medicine And Physical Fitness, 49, 97–104. Jones, P. A., Herrington, L. C. & Graham-Smith, P. 2015. Technique Determinants Of Knee Joint Loads During Cutting In Female Soccer Players. Human Movement Science, 42, 203–211. Kristianslund, E., Faul, O., Bahr, R., Myklebust, G. & Krosshaug, T. 2014. Sidestep Cutting Technique And Knee Abduction Loading: Implications For Acl Prevention Exercises. British Journal Of Sports Medicine, 48, 779–783. Latash, M. L. 2008. Synergy. New York: Oxford University Press. Lee, M. C. Y., Chow, J. Y., Komar, J., Tan, C. W. K. & Button, C. 2014. Nonlinear Pedagogy: An Effective Approach To Cater For Individual Differences In Learning A Sports Skill. Plos One, 9, E104744. Mangine, G. T., Hoffman, J. R., Wells, A. J., Gonzalez, A. M., Rogowski, J. P., Townsend, J. R., Jajtner, A. R., Beyer, K. S., Bohner, J. D., Pruna, G. J., Fragala, M. S. & Stout, J. R. 2014. Visual Tracking Speed Is Related To Basketball-Specific Measures Of Performance In Nba Players. The Journal Of Strength & Conditioning Research, 28, 2406–2414. Marshall, B. M., Franklyn-Miller, A. D., King, E. A., Moran, K. A., Strike, S. C. & Falvey, E. C. 2014. Biomechanical Factors Associated With Time To Complete A Change Of Direction Cutting Maneuver. The Journal Of Strength & Conditioning Research, 28, 2845–2851. McBride, J. M., Mccaulley, G. O. & Cormie, P. 2008. Influence Of Preactivity And Eccentric Muscle Activity On Concentric Performance During Vertical Jumping. The Journal Of Strength & Conditioning Research, 22, 750–757. McBride, J. M., Triplett-Mcbride, T., Davie, A. & Newton, R. U. 2002. The Effect Of Heavy- Vs. Light-Load Jump Squats On The Development Of Strength, Power, And Speed. The Journal Of Strength & Conditioning Research, 16, 75–82. McLean, S. G., Huang, X., Su, A. & Van Den Bogert, A. J. 2004. Sagittal Plane Biomechanics Cannot Injure The ACL During Sidestep Cutting. Clinical Biomechanics, 19, 828–838. Nedergaard, N. J., Kersting, U. & Lake, M. 2014. Using Accelerometry To Quantify Deceleration During A High-Intensity Soccer Turning Manoeuvre. Journal Of Sports Sciences, 32, 1897–1905. Nimphius, S. 2010. Lag Time: The Effect Of A Two Week Cessation From Resistance Training On Force, Velocity And Power In Elite Softball Players. The Journal Of Strength & Conditioning Research, 24, Supplement 1. Nimphius, S. 2014. Agility Development. In: Joyce, D. & Lewindon, D. (Eds.) High-Performance Training For Sports. Champaign, IL: Human Kinetics. Nimphius, S., Callaghan, S. J., Bezodis, N. E. & Lockie, R. G. 2017. Change Of Direction And Agility Tests: Challenging Our Current Measures Of Performance. Strength & Conditioning Journal, Ahead Of Press. Nimphius, S., Callaghan, S. J. & Hawser, A. 2016a. Comparison Of Simplified Change Of Direction Tests. The Journal Of Strength & Conditioning Research, 24, Supplement 1. Nimphius, S., Callaghan, S. J., Sptieri, T. & Lockie, R. G. 2016b. Change Of Direction Deficit: A More Isolated Measure Of Change Of Direction Performance Than Total 505 Time. The Journal Of Strength & Conditioning Research, 30, 3024–3032. Nimphius, S., Geib, G., Spiteri, T. & Carlisle, D. 2013. “Change Of Direction Deficit” Measurement In Division I American Football Players. Journal Of Australian Strength And Conditioning, 21, 115–117. Nimphius, S., Mcguigan, M. R. & Newton, R. U. 2010. Relationship Between Strength, Power, Speed, And Change Of Direction Performance Of Female Softball Players. The Journal Of Strength & Conditioning Research, 24, 885–895. Paul, D. J., Gabbett, T. J. & Nassis, G. P. 2016. Agility In Team Sports: Testing, Training And Factors Affecting Performance. Sports Medicine, 46, 421–442. Porter, J. M., Nolan, R. P., Ostrowski, E. J. & Wulf, G. 2010. Directing Attention Externally Enhances Agility Performance: A Qualitative And Quantitative Analysis Of The Efficacy Of Using Verbal Instructions To Focus Attention. Frontiers In Psychology,
1. Rabita, G., Dorel, S., Slawinski, J., Sàez-De-Villarreal, E., Couturier, A., Samozino, P. & Morin, J. B. 2015. Sprint Mechanics In WorldClass Athletes: A New Insight Into The Limits Of Human Locomotion. Scandinavian Journal Of Medicine & Science In Sports, 25, 583–594. Romeas, T., Guldner, A. & Faubert, J. 2016. 3D-Multiple Object Tracking Training Task Improves Passing Decision-Making Accuracy In Soccer Players. Psychology Of Sport And Exercise, 22, 1–9. Sasaki, S., Nagano, Y., Kaneko, S., Sakurai, T. & f*ckubayashi, T. 2011. The Relationship Between Performance And Trunk Movement During Change Of Direction. Journal Of Sports Science And Medicine, 10, 112–118. Sayers, M. G. 2015. The Influence Of Test Distance On Change Of Direction Speed Test Results. The Journal Of Strength & Conditioning Research, 29, 2412–2416. Serpell, B. G., Young, W. B. & Ford, M. 2011. Are The Perceptual And Decision-Making Components Of Agility Trainable? A Preliminary Investigation. The Journal Of Strength & Conditioning Research, 25, 1240–1248. Sheppard, J. M. & Young, W. 2006. Agility Literature Review: Classifications, Training And Testing. Journal Of Sports Sciences, 24, 919–932. Spiteri, T., Cochrane, J. L., Hart, N. H., Haff, G. G. & Nimphius, S. 2013. Effect Of Strength On Plant Foot Kinetics And Kinematics During A Change Of Direction Task. European Journal Of Sport Science, 13, 646–652. Spiteri, T., Hart, N. & Nimphius, S. 2014a. Offensive And Defensive Agility: A Sex Comparison Of Lower Body Kinematics And Ground Reaction Forces. Journal Of Applied Biomechanics, 30, 514–520. Spiteri, T., Newton, R. U., Binetti, M., Hart, N. H., Sheppard, J. M. & Nimphius, S. 2015a. Mechanical Determinants Of Faster Change Of Direction And Agility Performance In Female Basketball Athletes. The Journal Of Strength & Conditioning Research, 29, 2205–2214. Spiteri, T., Newton, R. U. & Nimphius, S. 2015b. Neuromuscular Strategies Contributing To Faster Multidirectional Agility Performance. Journal Of Electromyography And Kinesiology, 25, 629–636. Spiteri, T. & Nimphius, S. 2013. Relationship Between Timing Variables And Plant Foot Kinetics During Change Of Direction Movements. Journal Of Australian Strength And Conditioning, 21, 73–77. Spiteri, T., Nimphius, S., Hart, N. H., Specos, C., Sheppard, J. M. & Newton, R. U. 2014b. Contribution Of Strength Characteristics To Change Of Direction And Agility Performance In Female Basketball Athletes. The Journal Of Strength & Conditioning Research, 28, 2415–2423. Starkes, J. L., Cullen, J. D. & Macmahon, C. 2004. 12 A Life-Span Model Of The Acquisition And Retention Of Expert PerceptualMotor Performance. Skill Acquisition In Sport: Research, Theory And Practice. 259–281. Stone, M. H., O’bryant, H. S., Mccoy, L., Coglianese, R., Lehmkuhl, M. & Schilling, B. 2003. Power And Maximum Strength Relationships During Performance Of Dynamic And Static Weighted Jumps. The Journal Of Strength & Conditioning Research, 17, 140–147. Suchomel, T. J., Nimphius, S. & Stone, M. H. 2016. The Importance Of Muscular Strength In Athletic Performance. Sports Medicine, 46, 1419–1449. Vanrenterghem, J., Venables, E., Pataky, T. & Robinson, M. A. 2012. The Effect Of Running Speed On Knee Mechanical Loading In Females During Side Cutting. Journal Of Biomechanics, 45, 2444–2449. Wheeler, K. W. & Sayers, M. G. 2010. Modification Of Agility Running Technique In Reaction To A Defender In Rugby Union. Journal Of Sports Science And Medicine, 9, 445–451. Winkelman, N. C., Clark, K. P. & Ryan, L. J. 2017. Experience Level Influences The Effect Of Attentional Focus On Sprint Performance. Human Movement Science, 52, 84–95. Young, W. B., James, R. & Montgomery, I. 2002. Is Muscle Power Related To Running Speed With Changes Of Direction? Journal Of Sports Medicine And Physical Fitness, 42, 282–288.
CHAPTER 18
Speed and acceleration training Pedro Jiménez-Reyes, Bret Contreras and Jean-Benoît Morin SPRINT Sprint running is considered the fastest mode of human locomotion (Nagahara, Matsubayashi, Matsuo, & Zushi, 2014a). The analysis of sprinting is relevant to a better understanding of the muscles and forces generating the highest levels of performance. Sprint running, and more specifically sprint acceleration, is a key component and is central to performance in many sports including football, soccer, and rugby (Cronin & Sleivert, 2005). Sprint, power output, and forward acceleration are key physical determinants of successful athletic performance and are essential components of strength and conditioning training programs in many sports and recreational physical activities. Although maximal straight-line single-bout speed is the focus of many track events, and sprint running speed is also considered a relevant parameter for field-based team-sports (Simperingham, Cronin, & Ross, 2016), it is important to emphasize that the ability to accelerate over short distances should be prioritized in many sport activities rather than maximal velocity, since maximal velocity is rarely achieved in these kinds of sports (Morin, Slawinski, et al., 2015; Spencer, Bishop, Dawson, & Goodman, 2005). Sprinting in field-based team-sports can vary from short (e.g., Futsal, Rugby union forwards) (Deutsch, Kearney, & Rehrer, 2007) to long (e.g., Australian rules football) (Veale, Pearce, & Carlson, 2007) distances. Acceleration is a key factor in field-based team sports since players who accelerate more rapidly have an advantage due to the frequent occurrence of such accelerations (e.g., 5–20m, 2–3 seconds) during games (Schimpchen, Skorski, Nopp, & Meyer, 2016; Spencer et al., 2005). Recent studies suggest that 68% of sprints in rugby (Gabbett, 2012) and 90% of sprints in soccer (Vigne, Gaudino, Rogowski, Alloatti, & Hautier, 2010) are shorter than 20m, and this is not enough distance for players to reach maximum velocity. In addition, such short linear sprints are used in decisive actions (Faude, Koch, & Meyer, 2012). Several factors influence acceleration performance, including the magnitude of the applied force and the ability to apply the force effectively in the forward direction (Morin, Edouard, & Samozino, 2011; Morin et al., 2012). From the simple laws of dynamics, the acceleration of a body in the forward direction is proportional to the amount of ground reaction force produced in that direction. This has been experimentally confirmed in many types of athletes, ranging from non-specialists to world-class sprinters (Morin et al., 2011; Morin, Gimenez, et al., 2015; Morin, Slawinski, et al., 2015; Morin et al., 2012; Rabita et al., 2015). Furthermore, in recent years, a new insight into sprint acceleration mechanics has been proposed which considers the mechanical ability to produce horizontal external force during sprinting through the athlete’s Force-velocity (F-v) profile (Morin & Samozino, 2016; Samozino et al., 2016). Recent studies (Morin et al., 2011; Morin, Slawinski, et al.,
2015; Rabita et al., 2015) have shown that the main mechanical determinants of sprint performance are the absolute physical ability (maximal force and power attributes) of the athlete, and the technical ability to optimally handle this physical ability and apply the ground reaction force effectively (i.e., with a more horizontally-oriented angle). To date, research in this area is lacking, and most studies have focused primarily on different training methodologies (Rumpf, Lockie, Cronin, & Jalilvand, 2016), kinetics, kinematics, ground reaction forces, stiffness, electromyographic (EMG) activity patterns, and transfer of heavy-weight strength training to sprint performance (e.g., Rumpf et al., 2016; Seitz, Reyes, Tran, de Villarreal, & Haff, 2014). However, research is ongoing to determine which training modalities and exercises may be used in the field to improve horizontal force and associated sprint acceleration performance, including resisted and assisted sprinting as well as specific exercises for improving technical ability during sprinting. To enhance performance in athletes requiring high levels of acceleration, it is crucial to understand the mechanical underpinnings of sprint acceleration, and athletes’ subsequent training based on F-v profiling. In this chapter, we will discuss some of our current work in this area, and use the descriptive model “generate force and transmit it to the ground” to describe exercise modalities that may improve the various components of this model and answer the question: “Which exercises may contribute to improving force production, and which exercises may improve mechanical effectiveness and force transmission ability?”
Sprint: General description Typical sprint-track running is characterized by a velocity time-curve and can be divided into three phases; acceleration, constant velocity, and deceleration (Mero, Komi, & Gregor, 1992). In recent years, sprint running has also been divided into three phases described as early acceleration, acceleration, and maximal velocity. During these phases, sprint technique is modified. However, two phases are present during the whole sprint cycle: the stance phase (support phase) and the flight phase (swing phase). Maximum speed is relevant in track events and limited field-based team sport contexts, such as Australian rules football (Veale et al., 2007). Whereas acceleration of specific parameters is of relatively greater importance when covering only short distances at maximal effort, as is common in many field-based team sports (Simperingham et al., 2016). For instance, in team sports, first step quickness has been considered an important parameter for acceleration; this is defined as the first 0–5 meters and is included in the acceleration phase and characterized by a high propulsion force (Sleivert & Taingahue, 2004). Traditionally, several factors/parameters have been investigated concerning acceleration and sprint performance, providing the basis for understanding the ability to run fast. Some of these parameters are: stride length and frequency; ground contact time and flight time; joint torques and joint angle movements; ground reaction forces; stiffness; and EMG activity patterns. Classically, it was considered that if an athlete simply moved their lower limbs faster, thereby increasing the step frequency, they would reach higher levels of acceleration and maximum speed. Weyand et al. (2000) were among the first to debate this notion, concluding that it is the force production capability of the body, resulting in greater ground reaction forces (GRFs), that is the strongest determinant of maximal running speed in humans. There is a large body of literature supporting this statement (e.g., Clark & Weyand, 2014; Weyand, Sternlight, Bellizzi, & Wright, 2000; Weyand, Sandell, Prime, & Bundle, 2010). Although in recent years, research by Morin and colleagues (Morin et al., 2011; Morin, Samozino, Bonnefoy, Edouard, & Belli, 2010; Morin,
Slawinski, et al., 2015; Morin et al., 2012) highlighted the forward orientation of GRFs as a further determining factor of performance, specifically in the acceleration phase of the sprint, and observed that the vertical component of the GRF was not related to performance in that phase. Thus, some contrasting results can be found, and it seems that examining sprint running mechanics and force production in more depth is important to understanding and improving sprinting performance both in track events and field-based team sports. The acceleration of an athlete’s center of mass during sprint running is determined by body mass and three external forces acting on the body: (a) ground reaction force (GRF); (b) gravitational force; and (c) air or wind resistance (Samozino et al., 2016). GRF can be divided into three components (antero-posterior, vertical, and medio-lateral) although typically the antero-posterior (horizontal) and vertical components are the most studied and most relevant for sprint performance (Hunter, Marshall, & McNair, 2005; Morin et al., 2011; Rabita et al., 2015). The horizontal orientation of applied force should be considered when studying GRF during the support phase since the ability to produce and transfer greater forces may allow for shorter ground contact times and a shorter braking phase during contact, which could support the importance of the hip extensors and the ankle stabilizer muscles in training. Classically, running speed has been described as the product of stride rate or frequency and stride length, assuming that to increase velocity it is necessary to increase at least one, if not both (Hunter, Marshall, & McNair, 2004; Weyand et al., 2000). Typically, maximum stride frequency is reached between 10m and 20m, and at this point, stride length is about 75% of the maximum value reached during the maximum velocity phase. During the acceleration phase of a sprint, greater increases in horizontal propulsion are required to achieve high acceleration (Hunter, Marshall, & McNair, 2005; Morin et al., 2011). Ground-leg interaction is the major determinant in sprint running since it is during the contact or support phase of the step cycle that segmental forces can act on and in turn influence horizontal speed. Running is characterized by support (the foot is in contact with the ground) and swing phases (the time between when the lead foot leaves the ground and when it next makes contact with the ground). During the stance (support) phase, the athlete absorbs braking and vertical forces and then produces propulsive force to displace the body forward, while during the swing phase the athlete repositions the limbs in order to prepare for the next stance phase. Forward acceleration is key in sprint running. A typical support phase can be divided into a braking phase (backward orientation of the horizontal force vector; negative horizontal GRF) followed by a propulsive phase (positive horizontal GRF) (e.g., Hunter et al., 2005; Morin et al., 2011; Morin, Slawinski, et al., 2015; Rabita et al., 2015).
Mechanical determinants of sprint and acceleration performance: produce force and transmit it to the ground The aim of this section is to present evidence from existing scientific data to provide a better understanding of the underpinnings of the muscular determinants of sprint acceleration performance supporting our model of “produce the force and transmit it to the ground” and the technical ability to apply force, which will provide the basis of practical training methods to optimize sprint acceleration performance.
Muscular determinants of sprint and acceleration in performance
Sprint performance implies large forward acceleration, which is directly dependent on the ability to develop and apply high levels of horizontal external force into the ground at various speeds over the sprint acceleration period (Morin et al., 2011). This is why the ability to produce GRF with a magnitude and timing unique to each individual phase of the sprint becomes paramount, changing from a high force at low speed in the early acceleration phase to low force at high speed in the maximum speed phase (Morin et al., 2012). Muscle roles shift within the distinct acceleration phases, suggesting that a better understanding of “what force is happening at what speed” is very important in order to design specific training methods and therefore enhance muscle function during forward propulsion. The most widely studied muscles in sprinting are the hip extensors (hamstrings and gluteus maximus), knee extensors (quadriceps), and plantar flexors (soleus and gastrocnemius). It is widely accepted that most muscles activate at the highest levels just before or at the beginning of ground contact (Morin, Gimenez, et al., 2015). It is mainly during this support phase—the single instant when force can be applied to the ground—that the muscles responsible for hip, knee, and ankle movements play a specific role in acceleration performance, efficiently propelling the body forward. When analysing sprint acceleration from a purely biomechanical perspective, great differences/contrasts can be observed among the three phases previously described. These differences provide critical information for a better understanding of the underlying parameters responsible for this differentiation when talking about muscles’ roles or patterns of action. These variations become more evident during the very early steps, when body-positioning force is applied. This phase is characterized by a greater forward lean of the trunk (Debaere, Delecluse, Aerenhouts, Hagman, & Jonkers, 2013; Nagahara et al., 2014a and 2014b) and a longer time for the application of force of approximately 190ms versus ±101–108ms when the maximum velocity phase is reached (Wild, Bezodis, Blagrove, & Bezodis, 2011; Yu et al., 2016). In this first stage, the hip and knee extensors work alongside the soleus and gastrocnemius to achieve a triple joint extension of the lower limb and provide forward propulsion to the body mass. Although during this first ground contact time (GCT) the relative net horizontal impulse is greater than the vertical one (Kawamori, Nosaka, & Newton, 2013), both the calves and the quadriceps significantly contribute to forward displacement of the center of mass, together with the main muscle groups responsible for this function throughout the entire race: the hip extensors (Morin, Gimenez, et al., 2015; Schache, Brown, & Pandy, 2015). This is possible since the more inclined and gathered position prevailing in this phase enables the involvement of muscles that normally produce vertical force during concentric contraction—the quadriceps, soleus, and gastrocnemius—acting here to provide horizontal propulsion because the resulting vector of the applied force in this case is mainly diagonal, not vertical (Kugler & Janshen, 2010). The other major difference lies in ground contact patterns. Firstly, the time available to produce this force varies since the impulse required to overcome the body’s inertia mainly depends on the displacement velocity when body mass is fixed. The second factor is the distribution of propulsive and braking roles during each different phase (Morin, Slawinski, et al., 2015). During acceleration, most of the time in the ground contact phase is spent applying propulsive GRF (approximately 87–95% of total GCT) (Hunter et al., 2005; Sleivert & Taingahue, 2004), which is paramount to sprinting success. Therefore, this phase may be mechanically characterized by an involvement of the knee and hip extensors, in addition to the calves, to provide propulsion during the stance phase, which is distinguished by large contact times enabling the development and application of high levels of force into the ground, also made possible by the low displacement velocities.
The second phase is still included within the acceleration phase; however, from a kinematic point of view this second phase is mostly characterized by a gradual decrease in the body’s forward lean (Nagahara et al., 2014a and 2014b), the achievement of maximal stride frequency, and a marked increase in stride length with a continuous rise in running velocity (Nagahara, Naito, Morin, & Zushi, 2014b). This higher speed is also associated with shorter ground contact time and important consequences on the kinetic patterns. When considering muscle involvement levels during accelerated running, forward propulsion predominantly depends on the hip extensors—i.e., concentric action of the gluteus and eccentric action of the hamstrings (Morin, Gimenez, et al., 2015)—while the knee extensors and calves progressively adopt a more focused role in the stabilization and transmission of forces as the speed of movement is increased (Mann, Moran, & Dougherty, 1986; Schache et al., 2015). It is for this reason that during this second phase the force is applied in a different way, requiring smaller forces than during the first steps, but applied at a considerably greater speed. In turn, this reduction in available time for developing and applying force into the ground is probably associated with the importance of explosiveness (rate of force development) and the effectiveness of ground force application. During the maximum speed phase, the plantar flexors (gastrocnemius, soleus) in conjunction with the dorsiflexor (tibialis anterior) muscles have a major influence on how effectively the forces of different body segments are transferred to the ground. In fact, the gastrocnemius-soleus-achilles complex (GSAC) has been shown to play a relevant role in horizontal propulsion during the contact phase by storing and releasing elastic energy to aid the body’s forward projection. A review of the current literature indicates that a change of pattern is observed, since this still-significant contribution is mostly explained not by a concentric action of the GSAC but by an eccentric action. In turn, as for the GSAC, knee extensor activity is modified throughout this last phase, changing from power generation to a function more focused on the absorption and transmission of power (Schache et al., 2015). These changes can be interpreted mainly in terms of the differences observed in the kinetics of the body segments, where a remarkable modification of the knee and ankle angles—which are notably greater when compared to the first phase—can be observed at the moment of touchdown (Nagahara et al., 2014a and 2014b). This action, together with a significant reduction in ground contact time caused by considerably higher speeds, implies a limitation of mechanical ability during force application/development given the short period of time. All these observations point to the hip extensors as the major muscles responsible for forward propulsion during every phase of acceleration (Morin, Gimenez, et al., 2015). Thus, as suggested by Morin et al. (2015), it is important from a practical standpoint to reinforce hip extensor strength and knee flexion strength (including the eccentric action mode) to improve sprint acceleration performance. The evidence thus points first to the possibility that the muscular strategy chosen for the generation and transmission of forces during the acceleration phase is shifted as running speed increases. These modifications seem to be due to the mechanical differences present in every phase, which display characteristic kinetic and kinematic features. It seems likely that regardless of the observed phase, sprinting ability follows a sequential kinetic linking pattern, displaying an energy flow in a proximalto-distal sequence. From this perspective, the muscles play two distinct roles: producing force and transmitting it into the ground.
Effectiveness of force application onto the ground Accelerated runs are typically characterized by a support phase, which is mainly defined by a
negative horizontal ground reaction force (GRF)—a braking phase—followed by a positive horizontal GRF in the propulsive phase (e.g., Hunter et al., 2004). Considering the possible decomposition of the forces exerted into the ground, only the horizontal component of the GRF will influence the forward displacement of the center of mass of an athlete (Brughelli, Cronin, & Chaouachi, 2011; Morin et al., 2011), while the vertical and medio-lateral components will play a less significant role during acceleration. Given the gravitational constraints present during an acceleration run, most of the total (resultant) GRF is produced in a direction that is not characteristic of the athlete’s displacement. This vertical force (VF) is not directly linked/related to modification of the displacement speed. Even when an increase in velocity occurs, a stabilization in VF production appears when 60% of the maximum speed is reached (Brughelli et al., 2011), however, horizontal forces increase linearly with increasing speed. The evidence points to the fact that during acceleration, only the horizontal component of the total force induces body mass forward displacement, meaning the other component (vertical) is ineffective in producing forward acceleration, although necessary to keep moving forward (Morin et al., 2011). Once top speed is reached, the importance of the vertical component is greater (Clark & Weyand, 2014; Weyand et al., 2000; Weyand et al., 2010). In order to express the relative distribution of horizontal force (HF) compared to the resultant GRF, the ratio of forces (RF) is defined as the percentage of HF to the corresponding total GRF averaged over the support phase (FTot). This is used as an appropriate index to objectively calculate the effective force applied into the ground in order to analyse the technical efficiency during the support phase. This novel and simple index explains much of the mechanics underpinning acceleration performance, adding kinetics to the conventional spatio-temporal analysis. This perspective provides evidence that despite the development of similar GRF levels in hom*ogeneous groups of athletes, factors related to technical ability are able to alter the RF and give rise to different sprint acceleration performances. Indeed, researchers (Kawamori et al., 2013; Kugler & Janshen, 2010; Morin et al., 2011; Morin et al., 2012; Rabita et al., 2015; Slawinski et al., 2017) have observed that when subjects were compared within the same level group, those who performed better in the acceleration run (and on the overall 100m distance) did so on account of a better orientation of the GRF and not because of a greater total amount of GRF. The emergence of this new analysis of the kinetics of the sprint was accompanied by confirmation of the hypothesis that had argued that the ratio of forces present in each of the phases (and practically at each step) varies, showing a greater horizontal component (and therefore a higher RF) during the first support phase. These data confirmed what seemed obvious; the stage where a greater index of horizontality in the application of forces (RFmax) occurs is located during the very first steps. Conditions such as the arrangement of the body segments and the very low or null velocities of displacement existing during these early stages of acceleration enable the generation of large horizontal forces necessary for starting forward propulsion. As these velocities increase, RF decreases as a consequence of the inability to maintain acceleration levels and change both at the kinetic level (i.e., shorter contact time) and the kinematic level (i.e., a more erect body position that favours the transmission of forces rather than the generation of them). To describe this systematic decrease in RF with increasing speed, the same authors developed an index of force application technique (DRF). Basically, those athletes able to maintain their ability to produce horizontal force (and thus further produce net horizontal force while accelerating) despite the
increasing velocity will produce a higher DRF value (i.e., a flat RF–speed relationship), while those whose RF decreases to a greater extent as a result of this increase in speed will have lower DRF values (i.e., a steeper RF–speed relationship) (see Figure 18.1). Typically, non-sprinters have a DRF of about –10% whereas the best sprinters have DRF values of –4 to –6% (Morin et al., 2012; Rabita et al., 2015). In addition, athletes who exhibit better DRF values (which should be considered as a “technical” parameter since it is not correlated to the amount of force applied, i.e., “physical capability”) are better performers in sports where maximum speed is a priority, such as the 100m sprint, since they are able to still produce net horizontal force, and thus orient and transmit horizontal forces while their speed of movement is increasing.
FORCE-VELOCITY PROFILE DEFINITION AND FIELD COMPUTATION METHOD Sprint running implies large forward acceleration and is related to the capacity to produce and apply high power outputs in the horizontal direction into the ground (i.e., high horizontal external forces at various velocities during sprint acceleration). The overall ability to produce horizontal external force during sprint running is well described by the inverse linear F-v and parabolic power-velocity (P-v) relationships (Jaskólska, Goossens, Veenstra, Jaskólski, & Skinner, 1999; Morin et al., 2011; Morin et al., 2010; Rabita et al., 2015) through which maximal power output may be improved by increasing the ability to generate force output at low levels of velocity (a force-dominant profile), maximizing velocity production at low levels of force (a velocity-dominant profile), or both (Morin et al., 2016). The assessment of horizontal power and mechanical relationships during sprint running is essential to understand the specific determinants of sprinting performance. Since horizontal power and its associated determinants are highly related to acceleration ability during sprint running (Morin, Gimenez, et al., 2015; Rabita et al., 2015), researchers have attempted to develop methods to assess these sport-specific determinants accurately to gain a better understanding of running performance. In recent years, the inclusion of F-v relationships and their contribution to ballistic performance has provided a more accurate and integrative mechanical representation of the athlete’s maximal capabilities (Samozino, Rejc, Di Prampero, Belli, & Morin, 2012), encompassing the entire forcevelocity spectrum, from the theoretical maximal force (F0) to the theoretical velocity (v0) capabilities (Morin & Samozino, 2016).
FIGURE 18.1
Ratio of forces (RF) and index of force orientation (DRF). Typical example of the RF-speed linear relationship obtained during a six second sprint on an instrumented sprint treadmill. Each point corresponds to values of RF and running speed averaged for one contact phase. The DRF index value for this subject is –0.0803. The dashed lines would correspond to a better index for the black line (flatter relationship, i.e., more horizontal force produced as speed increases) and a worse index for the grey line (steeper relationship, i.e., the horizontal force drops faster as speed increases).
Since these mechanical features could previously only be measured during sprints on an instrumented treadmill (Morin et al., 2010; Morin et al., 2012) or on track-embedded force plate systems (Rabita et al., 2015), a simpler method has been proposed and validated. This method requires simple distance- or velocity-time data to model external horizontal force measures and associated F-v and P-v relationships during the entire acceleration phase of an over-ground sprint (Samozino et al., 2016). This method uses a computation based on a macroscopic inverse dynamic analysis of the center-of-mass of motion. Velocity-time data are fitted using an exponential function, after which instantaneous velocity is derived to compute the net horizontal antero-posterior ground reaction force (F), and the power output in the horizontal direction (P). Individual linear forcevelocity relationships are then extrapolated to calculate theoretical maximal force (F0) and velocity (v0) capabilities, and underlying maximum horizontal external power output (Pmax). In this method, F and v are averaged and plotted throughout the course of a sprint for each stance phase. The steps from maximal F through to those producing maximal v are subsequently used to plot the linear F-v relationship (Samozino et al., 2016). The entire F-v relationship is described by the maximal theoretical horizontal force that the lower limbs could produce over one contact at a null velocity (F0 expressed in N•kg–1) and the theoretical maximum velocity that could be produced during a contact phase in the absence of mechanical constraints (v0 expressed in m•s–1). A higher v0 value represents a greater ability to develop horizontal force at high velocities. (see Figure 18.2).
FIGURE 18.2
Force-velocity-power profile of Usain Bolt’s world record.
Together with F0, v0, and Pmax, the entire mechanical F-v profile also includes the mechanical effectiveness of ground force application, which is described with two main variables explained above: RF (i.e., the ratio of the effective horizontal component of the GRF to the resultant GRF) and how quickly this ratio drops as the running velocity increases (decrease in the ratio of force, DRF). Therefore, determining the F-v profile is very useful in practice since an athlete can be identified in a force and velocity context, which determines his/her weaknesses, and training can then be aligned accordingly on an individualized basis (Morin & Samozino, 2016). With this in mind, it is worth highlighting the usefulness and strength of this approach for estimating over-ground running sprint kinetics via a simple yet reliable field method with almost identical values to direct measurement via a sophisticated force-plate setup (Rabita et al., 2015; Samozino et al., 2016). This method has been shown to be sensitive enough to differentiate mechanical parameters between athletes with similar capabilities or playing roles and provide practical information to aid return to play from injury in rugby and soccer players (Cross et al., 2015; Mendiguchia et al., 2014, 2016). Furthermore, given the simplicity of obtaining the data required for this method, such as velocity-time measurements with an adequate sampling rate, for training and assessment purposes this profiling method would be easily used by strength and conditioning coaches and practitioners with timing gates, a radar gun, or even a recently validated iPhone app (MySprint) (Romero-Franco et al., 2016).
INDIVIDUALIZED TRAINING BASED ON F-V PROFILING Strength and conditioning coaches and practitioners are very interested in the best training methods
for improving sprinting performance. Several training methods have been widely used, including sprinting (Rumpf et al., 2016), technical skills (Bushnell & Hunter, 2007; Lockie, Murphy, Schultz, Knight, & Janse de Jonge, 2012), maximal power (Delecluse et al., 1995; McBride, TriplettMcBride, Davie, & Newton, 2002), reactive strength (plyometric training) (Sáez de Villarreal, Requena, & Cronin, 2012), ballistic training (Cormie, McGuigan, & Newton, 2010; Sheppard et al., 2011), and combinations of these methods (Harris, Stone, O’Bryant, Proulx, & Johnson, 2000; Ronnestad, Kvamme, Sunde, & Raastad, 2008), although inconsistent results have been achieved with many of them. Strength and conditioning research has influenced the importance of traditional strength training in improving sprint performance via the transfer phenomenon. Thus, the question arises: “is classical ‘vertical’ strength work really effective in transferring and increasing the level of horizontal force output in trained athletes?” Horizontal force generation is a key factor in many sports, and therefore specific training to improve it is essential. The issue for training is that traditional strength-based resistance training may not be the most specific way to develop the ability to apply force with a horizontal orientation since the majority of resistance training methods focus on working the lower limb muscles in a vertical direction. Although during sprinting both the horizontal and vertical components of GRF are necessary to the overall motion of the runner, the horizontal component has the most influence during acceleration (Brughelli et al., 2011; Morin et al., 2011; Morin, Slawinski, et al., 2015; Morin et al., 2012; Rabita et al., 2015). Recently, the existence of a possible transfer of lower-body strength training to sprint performance has been discussed, with a review of literature supporting the idea that sprint performance can be improved through strength gains (Seitz et al., 2014). However, this improvement is not systematic since many parameters affect the magnitude of improvement. Little is known about the effectiveness of a specific training program using exercises to improve the force-velocity-power associated with the horizontal component of GRF on sprint performance. It is likely that a greater transfer of resistance training can be achieved if the conditioning program emphasizes a similar motor pattern and contraction type (i.e., comparable mechanical properties) to the performance movement (Young, 2006). The importance of strength exercises for improving muscles having a determinant action during horizontal force application in acceleration must be noted (Contreras et al., 2016). In addition, since adaptations are specific to the velocity used in training, it is worth considering this specificity over the entire F-v spectrum, which must be covered for training purposes. In consequence, the concept of “what force at what speed” emerges as a relevant factor for improving both acceleration and maximum speed. For F0 improvement it is important to produce high forces at low speeds, while for v0 improvement the application of force at high speed is most significant. Thus, the fundamentals of how to specifically and effectively train according to the F-v profile features are based on this velocity specificity principle, taking into account the different components of the F-v profile (F0, RF, Pmax, DRF, and v0). The features explained above concerning F-v profiling could provide both useful information for sport practitioners and a simple, accessible, yet accurate method for more individualized monitoring and training of physical and technical capabilities. This method can be easily implemented on a regular basis and can therefore be used for long-term monitoring and training processes (Morin & Samozino, 2016).
PRACTICAL APPLICATIONS: INDIVIDUAL PROFILING AND TRAINING
PROGRAM F-v profiling and associated components could provide very useful and practical information, allowing the selection of the most appropriate exercises for improving sprint performance and enabling the design of better training programs for different modalities by considering which component (F0, RF, Pmax, DRF, and v0) should be emphasized. Since the F-v profile can be easily measured during sprint running, coaches could obtain valuable comparative information and guidance for individualized training or rehabilitation prescriptions. In practical terms, if a training program is designed to improve sprint acceleration performance, the focus should be placed on increasing Pmax by improving its components (F0 and v0). This could be done by first comparing the relative strengths and weaknesses in each player’s profile to the rest of the team (e.g., median or mean value) or published data for similar athletes, and then programming the training content depending on the distance over which sprint acceleration should be optimized. The question for coaches is how to specifically target the different components of the F-v profile, and, although training for Pmax could be relevant depending on the orientation of the F-v profile towards force or velocity, the targeted programs for individuals could differ depending on whether a force-oriented or velocity-oriented profile dominates. For practical purposes, it is interesting to divide exercises based on the targeting of different parts of the entire F-v spectrum as follows: • • •
Force side of the F-v: the focus of these exercises is the application of high forces at low speeds, leading to an improvement in the F0 and RF components of the F-v profile. Power side of the F-v: the focus of these exercises is the application of medium forces at medium speeds, resulting in an improvement in the Pmax component of the F-v profile. Velocity side of the F-v: the focus of these exercises is the application of low forces at high speeds, resulting in an improvement in the DRF and v0 components of the F-v profile.
The features of each of the three components discussed above, and appropriate exercises for each, follow: •
F0 and RF category:
At the beginning of an accelerated run, a high horizontal force application is developed at a low velocity of motion. This early acceleration phase is characterized by a very pronounced inclination of the trunk and overall body, which helps in applying force in a horizontal direction. Thus, the main feature of this “high-force, low-velocity” phase is that the athlete applies much higher horizontal forces than when running faster. It is thus logical to assume that an exercise or training modality that could gather these features into a specific running pattern would be appropriate since it would target the development of the force side of the F-v spectrum. A training modality that could best satisfy these considerations is the “Very Heavy Sled” (VHS) since it is an effective way of providing a good incline while applying high horizontal force at low speed, allowing the athlete to create and maintain conditions of high force, high forward lean, and high muscular activity in the main propulsion muscles such as the hip extensors. Interestingly, very recently, a study using amateur soccer players showed the effectiveness of training with VHS (80% of body mass) over an eight week period, which led to marked
improvements in the mechanical effectiveness of force application (F0 and RF) and in Pmax (Morin et al., 2016). Thus, it seems that VHS is both a cost- and time-effective way of overloading the athlete, training both lower limb strength (i.e., general capacity) and the technical ability to apply this force effectively onto the ground (i.e., horizontally-oriented force). •
Pmax category:
After the first steps (about two seconds of initial application of force), maximal power is reached, which is the combination of optimal force and velocity at medium force (F0/2) and medium velocity (V0/2). These “optimal loading” conditions for improving sprint running performance have been discussed (Petrakos, Morin, & Egan, 2016), particularly with regard to resisted sprints, although the criteria for determining optimal load for sprinting were based on non-significant alterations to technical components (i.e., kinematics of the unloaded sprint movement via a 10% decrement with respect to maximal velocity), rather than considering force or velocity components from the F-v profile as a reference. It is important to note that when Petrakos et al.’s criteria are applied, the features and conditions needed to develop horizontal force at a specific velocity at this stage of an accelerated run are limited, since with only a 10% velocity decrement the body cannot remain in a forward-inclined position for long and the athlete is forced to adopt a more vertical position quite quickly. In line with this, very recently, researchers (Cross, Brughelli, Samozino, Brown, & Morin, 2017) analysed the “optimal load” on an individualized basis (i.e., the load which, for each individual, induces maximal power output), and the results appear to be highly individualized, with resistances of between 69–96% of body mass, corresponding to a velocity decrement of ~50% from maximal velocity (Cross et al., 2017). Technical and mechanical F-v characteristics were also found to be highly individualized (Cross et al., 2017). Thus, it seems that using individualized sled resistances that lead to individual optimal load and optimal running velocity, i.e., the velocity at which maximal power is produced (close to V0/2 as shown by Cross et al., 2017) can provide an effective stimulus for maximizing horizontal power production, thereby improving the physical and technical capacities underlying sprinting performance (Morin et al., 2011; Morin, Slawinski, et al., 2015). It is also likely that increasing an athlete’s Pmax will be associated with a better sprint acceleration performance, especially over short distances (e.g., soccer) and in collision sports (e.g., rugby) (Cross et al., 2017). •
DRF and v0 category:
As velocity increases over the acceleration phase, the conditions for force application change. For early acceleration, a high force at low velocity is required, but the athlete then needs to keep producing and applying a net horizontal force despite increasing movement velocity. At high running velocities, the body is essentially in a standing position (vertical), and the knee is extended at touchdown and during the stance phase; in this situation, from a functional anatomy standpoint, the only action leading to a backward push of the foot on the ground is violent hip extension. This condition is a limiting factor in the continued application of force in a horizontal direction, and it has been shown that better sprinters tend to produce a higher RF and thus a higher mechanical effectiveness (i.e., a more horizontally-oriented GRF) at high velocity (Morin et al., 2012).
It is therefore reasonable to assume that an exercise modality that emphasizes the application of force at high velocity could be appropriate since it specifically targets the development of the velocity side of the F-v spectrum. Given the importance of improvement in velocity (i.e., the velocity end of the F-v spectrum), several training modalities have been commonly used, including free sprinting, assisted and resisted sprinting, traditional strength-training, and plyometrics (Rumpf et al., 2016). The effectiveness of these training modalities is unclear (Rumpf et al., 2016), and it could be interesting for coaches to use more specific training based on the F-v profile, targeting the velocity side of the F-v spectrum with potential benefit for the v0 and DRF components of the F-v profile. Sprinting may be the most specific type of training available to improve sprinting speed (Rumpf et al., 2016), probably due to an increase in velocity-specific force production with the same pattern of movement. However, improvements achieved via free sprinting are higher in untrained subjects than in trained athletes (Rumpf et al., 2016), and this issue should be considered in order to implement the F-v profile approach for optimized improvement in sprint velocity. In light of the above information, and based on some preliminary results, the exercises most likely to be appropriate should allow the athlete to apply horizontal force in a high-velocity context. Taking into account that when athletes run at high velocities the body is in a standing position (vertical), with high activity in the hip extensors, it would be useful to reproduce specific and similar patterns during the application of force. The first exercise could be sled with light loads (about 10% of body mass) since this trains the ability to produce horizontal force at high running velocities and is thus an effective stimulus. Another possible exercise involves explosive backward propulsion on a scooter (testing in progress). Together with these exercises, other options that make sense mechanically (but are still to be tested under controlled conditions) include over-speed training and the inclusion of a resistance during an assisted condition. Finally, but no less importantly, free sprinting would also be an effective stimulus for improving velocity capability, since most of the distance in a 50–80m sprint is run at velocities close to maximal velocity. These types of exercises could therefore be an effective way to improve the DRF and v0 components of the F-v profile via the improvement of horizontal force production at high velocities.
CONCLUSION Summarizing the practical details, when an athlete accelerates, the main mechanical need is to (1) produce force and (2) to transmit it effectively to the ground. These two actions must be repeated and performed at high speed. Thus, the main focus of training should be on the core and ankle stabilizer muscles as “transmitting” muscles, and the hip extensors as the main force generators. The latter may be trained using the very specific exercises “hip thrusts” and back extensions to strengthen these key muscles for forward acceleration. This chapter has focused on the mechanical factors underpinning sprinting performance based on the F-v approach; understanding these fundamentals of sprinting performance may allow coaches and practitioners to develop specific training programs to reinforce the main muscles affecting performance in acceleration running. The main value of this approach is that the diagnostic and subsequent targeted training interventions are individualized, and frequent monitoring of program-induced changes in Pmax and its mechanical determinants can make this program more efficient and dynamic in terms of adaptation to individual changes over time.
REFERENCES Brughelli, M., Cronin, J., & Chaouachi, A. (2011). Effects of running velocity on running kinetics and kinematics. Journal of Strength and Conditioning Research, 25(4), 933–939. Bushnell, T., & Hunter, I. (2007). Differences in technique between sprinters and distance runners at equal and maximal speeds. Sports Biomechanics, 6(3), 261–268. Clark, K. P., & Weyand, P. G. (2014). Are running speeds maximized with simple-spring stance mechanics? Journal of Applied Physiology, 117(6), 604–615. Contreras, B., Vigotsky, A. D., Schoenfeld, B. J., Beardsley, C., McMaster, D. T., Reyneke, J., & Cronin, J. (2016). Effects of a sixweek hip thrust versus front squat resistance training program on performance in adolescent males: A randomized-controlled trial. Journal of Strength and Conditioning Research. Cormie, P., McGuigan, M. R., & Newton, R. U. (2010). Adaptations in athletic performance after ballistic power versus strength training. Medicine and Science in Sports and Exercise, 42(8), 1582–1598. Cronin, J. & Sleivert, G. (2005). Challenges in understanding the influence of maximal power training on improving athletic performance. Sports Medicine, 35(3), 213–234. Cross, M. R., Brughelli, M., Brown, S. R., Samozino, P., Gill, N. D., Cronin, J. B., & Morin, J. B. (2015). Mechanical properties of sprinting in elite rugby union and rugby league. International Journal of Sports Physiology and Performance, 10(6), 695–702. Cross, M. R., Brughelli, M., Samozino, P., Brown, S. R., & Morin, J.-B. (2017). Optimal loading for maximising power during sledresisted sprinting. International Journal of Sports Physiology and Performance, 1–25. Debaere, S., Delecluse, C., Aerenhouts, D., Hagman, F., & Jonkers, I. (2013). From block clearance to sprint running: Characteristics underlying an effective transition. Journal of Sports Sciences, 31(2), 137–149. Delecluse, C., Van Coppenolle, H., Willems, E., Van Leemputte, M., Diels, R., & Goris, M. (1995). Influence of high-resistance and highvelocity training on sprint performance. Medicine and Science in Sports and Exercise, 27(8), 1203–1209. Deutsch, M. U., Kearney, G. A., & Rehrer, N. J. (2007). Time – motion analysis of professional rugby union players during match-play. Journal of Sports Sciences, 25(4), 461–472. Faude, O., Koch, T., & Meyer, T. (2012). Straight sprinting is the most frequent action in goal situations in professional football. Journal of Sports Sciences, 30(7), 625–631. Gabbett, T. J. (2012). Sprinting patterns of National Rugby League competition. Journal of Strength and Conditioning Research, 26(1), 121–130. Harris, G., Stone, M., O’Bryant, H., Proulx, C., & Johnson, R. (2000). Short term performance effects of high speed, high force or combined weight training. The Journal of Strength & Conditioning Research, 14(1), 4–120. Hunter, J. P., Marshall, R. N., & McNair, P. J. (2004). Interaction of step length and step rate during sprint running. Medicine and Science in Sports and Exercise, 36(2), 261–271. Hunter, J. P., Marshall, R. N., & McNair, P. J. (2005). Relationships between ground reaction force impulse and kinematics of sprintrunning acceleration. Journal of Applied Biomechanics, 21(1), 31–43. Jaskólska, A., Goossens, P., Veenstra, B., Jaskólski, A., & Skinner, J. S. (1999). Comparison of treadmill and cycle ergometer measurements of force-velocity relationships and power output. International Journal of Sports Medicine, 20(3), 192–197. Kawamori, N., Nosaka, K., & Newton, R. U. (2013). Relationships between ground reaction impulse and sprint acceleration performance in team sport athletes. Journal of Strength and Conditioning Research, 27(3), 568–573. Kugler, F. & Janshen, L. (2010). Body position determines propulsive forces in accelerated running. Journal of Biomechanics, 43(2), 343–348. Lockie, R. G., Murphy, A. J., Schultz, A. B., Knight, T. J., & Janse de Jonge, X. A. K. (2012). The effects of different speed training protocols on sprint acceleration kinematics and muscle strength and power in field sport athletes. Journal of Strength and Conditioning Research, 26(6), 1539–1550. Mann, R. A., Moran, G. T., & Dougherty, S. E. (1986). Comparative electromyography of the lower extremity in jogging, running, and sprinting. The American Journal of Sports Medicine, 14(6), 501–510. McBride, J. M., Triplett-McBride, T., Davie, A., & Newton, R. U. (2002). The effect of heavy- vs. light-load jump squats on the development of strength, power, and speed. Journal of Strength and Conditioning Research, 16(1), 75–82. Mendiguchia, J., Edouard, P., Samozino, P., Brughelli, M., Cross, M., Ross, A., . . . Morin, J. B. (2016). Field monitoring of sprinting power-force-velocity profile before, during and after hamstring injury: Two case reports. Journal of Sports Sciences, 34(6), 535– 541. Mendiguchia, J., Samozino, P., Martinez-Ruiz, E., Brughelli, M., Schmikli, S., Morin, J.-B., & Mendez-Villanueva, A. (2014). Progression of mechanical properties during on-field sprint running after returning to sports from a hamstring muscle injury in soccer players. International Journal of Sports Medicine, 35(8), 690–695. Mero, A., Komi, P. V., & Gregor, R. J. (1992). Biomechanics of sprint running. Sports Medicine, 13(6), 376–392. Morin, J. B., Edouard, P., & Samozino, P. (2011). Technical ability of force application as a determinant factor of sprint performance. Medicine and Science in Sports and Exercise, 43(9), 1680–1688.
Morin, J. B., Petrakos, G., Jimenez-Reyes, P., Brown, S. R., Samozino, P., & Cross, M. R. (2016). Very-heavy sled training for improving horizontal force output in soccer players. International Journal of Sports Physiology and Performance, 1–13. Morin, J. B., Bourdin, M., Edouard, P., Peyrot, N., Samozino, P., & Lacour, J. R. (2012). Mechanical determinants of 100-m sprint running performance. European Journal of Applied Physiology, 112(11), 3921–3930. Morin, J. B., Gimenez, P., Edouard, P., Arnal, P., Jiménez-Reyes, P., Samozino, P., . . . Mendiguchia, J. (2015). Sprint acceleration mechanics: The major role of hamstrings in horizontal force production. Frontiers in Physiology, 6(DEC). Morin, J. B., & Samozino, P. (2016). Interpreting power-force-velocity profiles for individualized and specific training. International Journal of Sports Physiology and Performance. Morin, J. B., Samozino, P., Bonnefoy, R., Edouard, P., & Belli, A. (2010). Direct measurement of power during one single sprint on treadmill. Journal of Biomechanics, 43(10), 1970–1975. Morin, J. B., Slawinski, J., Dorel, S., de villareal, E. S., Couturier, A., Samozino, P., . . . Rabita, G. (2015). Acceleration capability in elite sprinters and ground impulse: Push more, brake less? Journal of Biomechanics, 48(12), 3149–3154. Nagahara, R., Matsubayashi, T., Matsuo, A., & Zushi, K. (2014a). 100. Kinematics of transition during human accelerated sprinting. Biology Open, 3, 689–699. Nagahara, R., Naito, H., Morin, J. B., & Zushi, K. (2014b). Association of acceleration with spatiotemporal variables in maximal sprinting. International Journal of Sports Medicine, 35(9), 755–761. Petrakos, G., Morin, J. B., & Egan, B. (2016). Resisted sled sprint training to improve sprint performance: A systematic review. Sports Medicine (Auckland, N.Z.), 46(3), 381–400. Rabita, G., Dorel, S., Slawinski, J., Sàez-de-Villarreal, E., Couturier, A., Samozino, P., & Morin, J. B. (2015). Sprint mechanics in worldclass athletes: A new insight into the limits of human locomotion. Scandinavian Journal of Medicine and Science in Sports, 25(5), 583–594. Romero-Franco, N., Jiménez-Reyes, P., Castaño-Zambudio, A., Capelo-Ramírez, F., Rodríguez-Juan, J. J., González-Hernández, J., . . . Balsalobre-Fernández, C. (2016). Sprint performance and mechanical outputs computed with an iPhone app: Comparison with existing reference methods. European Journal of Sport Science, 1–7. Ronnestad, B. R., Kvamme, N. H., Sunde, A., & Raastad, T. (2008). Short-term effects of strength and plyometric training on sprint and jump performance in professional soccer players. Journal of Strength and Conditioning Research, 22(3), 773–780. Rumpf, M. C., Lockie, R. G., Cronin, J. B., & Jalilvand, F. (2016). Effect of different sprint training methods on sprint performance over various distances: A brief review. Journal of Strength and Conditioning Research, 30(6), 1767–1785. Sáez de Villarreal, E., Requena, B., & Cronin, J. B. (2012). The effects of plyometric training on sprint performance: A meta-analysis. Journal of Strength and Conditioning Research, 26(2), 575–584. Samozino, P., Rabita, G., Dorel, S., Slawinski, J., Peyrot, N., Saez de Villarreal, E., & Morin, J. B. (2016). A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running. Scandinavian Journal of Medicine & Science in Sports, 26(6), 648–658. Samozino, P., Rejc, E., Di Prampero, P. E., Belli, A., & Morin, J.-B. (2012). Optimal force-velocity profile in ballistic movements--altius: Citius or fortius?. Medicine and Science in Sports and Exercise, 44(2), 313–322. Schache, A. G., Brown, N. A. T., & Pandy, M. G. (2015). Modulation of work and power by the human lower-limb joints with increasing steady-state locomotion speed. The Journal of Experimental Biology, 218(Pt 15), 2472–2481. Schimpchen, J., Skorski, S., Nopp, S., & Meyer, T. (2016). Are “classical” tests of repeated-sprint ability in football externally valid? A new approach to determine in-game sprinting behaviour in elite football players. Journal of Sports Sciences, 34(6), 519–526. Seitz, L. B., Reyes, A., Tran, T. T., de Villarreal, E. S., & Haff, G. G. (2014). Increases in lower-body strength transfer positively to sprint performance: A systematic review with meta-analysis. Sports Medicine, 44(12), 1693–1702. Sheppard, J. M., Dingley, A. A., Janssen, I., Spratford, W., Chapman, D. W., & Newton, R. U. (2011). The effect of assisted jumping on vertical jump height in high-performance volleyball players. Journal of Science and Medicine in Sport, 14(1), 85–89. Simperingham, K. D., Cronin, J. B., & Ross, A. (2016). Advances in sprint acceleration profiling for field-based team-sport athletes: Utility, reliability, validity and limitations. Sports Medicine, 46(11), 1619–1645. Slawinski, J., Termoz, N., Rabita, G., Guilhem, G., Dorel, S., Morin, J.-B., & Samozino, P. (2017). How 100-m event analyses improve our understanding of world-class men’s and women’s sprint performance. Scandinavian Journal of Medicine & Science in Sports, 27(1), 45–54. Sleivert, G. & Taingahue, M. (2004). The relationship between maximal jump-squat power and sprint acceleration in athletes. European Journal of Applied Physiology, 91(1), 46–52. Spencer, M., Bishop, D., Dawson, B., & Goodman, C. (2005). Physiological and metabolic responses of repeated-sprint activities: Specific to field-based team sports. Sports Medicine, 35(12), 1025–1044. Veale, J. P., Pearce, A. J., & Carlson, J. S. (2007). Player movement patterns in an elite junior Australian rules football team: An exploratory study. Journal of Sports Science & Medicine, 6(2), 254–260. Vigne, G., Gaudino, C., Rogowski, I., Alloatti, G., & Hautier, C. (2010). Activity profile in elite Italian soccer team. International Journal of Sports Medicine, 31(5), 304–310. Weyand, P. G., Sandell, R. F., Prime, D. N. L., & Bundle, M. W. (2010). The biological limits to running speed are imposed from the ground up. Journal of Applied Physiology, 108(4), 950–961.
Weyand, P. G., Sternlight, D. B., Bellizzi, M. J., & Wright, S. (2000). Faster top running speeds are achieved with greater ground forces not more rapid leg movements. Journal of Applied Physiology, 89(5), 1991–1999. Wild, J., Bezodis, N., Blagrove, R., & Bezodis, I. (2011). A biomechanical comparison of accelerative and maximum velocity sprinting: Specific strength training considerations. UK Strength and Conditioning Association, 21(21), 36. Young, W. B. (2006). Transfer of strength and power training to sports performance. International Journal of Sports Physiology and Performance, 1(2), 74–83. Yu, J., Sun, Y., Yang, C., Wang, D., Yin, K., Herzog, W., & Liu, Y. (2016). Biomechanical insights into differences between the midacceleration and maximum velocity phases of sprinting. Journal of Strength and Conditioning Research, 30(7), 1906–1916.
CHAPTER 19
Applied coaching science Nick Winkelman
INTRODUCTION In 1993, Jana Novotna was serving against Steffi Graf in the Wimbledon final, just one point away from winning the championship. Despite leading four sets to one, Novotna went on to conceded four straight sets, inevitably losing 6–4 to Graf in what can only be described as one of the most public displays of “choking” ever seen in modern sport. However, Novotna is not alone, as there are many other examples of clear winners losing their nerve in the final moments of a competition. Take, for example, Greg Norman, who was six strokes ahead of Nick Faldo going into the final round of the 1996 Masters and went on to lose by four strokes by the end of Sunday. From a team sport standpoint, fans will not forget the 2004 World Series where the New York Yankees, up three games to one against the Boston Red Sox, lost four straight games and the Commissioner’s Trophy. While it is debatable whether the outcomes described above are examples of “choking” or comebacks, one fact remains, there was a pivotal moment where the winning side started underperforming and/or the losing side started outperforming the competition. Whichever the case, there was a shift in motor skill behavior and decision making that enhanced the fortune of one competitor at the expense of the other. While some might chalk this up to a bad day, poor luck, or a lack of resolve, others may question these surface level explanations in search of underpinning reasons. What’s more, while the opening examples of “choking” provide extreme instances of failure in competition, there is the more common experience of athletes not delivering the same level of performance in competition as they commonly do during practice. It is this latter observation that sets the stage for this chapter, and in doing so requires a fundamental question to be asked. How can coaches increase the probability that the performance their athletes achieve in practice is the one they deliver during competition? To begin answering this question, it is important to define the difference between practice performance and competitive performance. Specifically, Soderstrom and Bjork (2015) define practice performance as “the temporary fluctuations in [motor skill] behavior or knowledge that can be observed and measured during or immediately after the [practice] process,” while competitive performance or what will now be referred to as learning, “refers to the relatively permanent changes in [motor skill] behavior or knowledge that support long-term retention and transfer to [competition].” Thus, as illustrated by the examples of “choking” in sport, coaches are advised against viewing practice performance as a proxy for learning. Rather, learning can only be assessed
in the absence of the stimulus that caused it (i.e., practice), which positions competition as the single most important measure of motor skill retention and transfer. In her seminal book Choke, Sian Beilock provides further support for this line of reasoning, defining “choking as suboptimal performance, not just poor performance,” and noting that “it is performance that is inferior to what you can do and have done in the past” (Beilock, 2010). Thus, while “choking” is often associated with performance anxiety and labeled as failed mental fortitude, an equally viable explanation would be the recontextualization of “choking” as a failure of the learning process. To illustrate the impact of practice performance on learning, it is valuable to review the two pathways by which learning can take place. Take, for example, a child learning to ride a bike. At first their parents would have given them training wheels, allowing them to get a sense of balancing on the bike and learning how to pedal with enough speed where the training wheels become unneeded. Once the parents feel the child is ready, they take the training wheels off, and after a few falls, the child has figured out how to ride the bike safely. From a motor learning standpoint, this scenario is an example of emergent or implicit learning. That is, the parents were not explicitly telling the child how to steer, pedal, maintain posture, and visually navigate the sidewalk; rather, they likely gave them basic instructions (e.g., “pedal faster”) that were of no consequence to the actual movement process required to ride the bike. Thus, this movement pattern emerged out of the child’s determination not to fall and their desire to ride their bike like the rest of the neighbor kids. As noted, this is an example of an implicit learning pathway, which can be defined as learning that occurs through practice that emphasizes experience and limits explicit information, leading to a physical understanding of rhythm, sequence, and execution that can be measured through performance, but not through factual recall (Kleynen et al., 2014). In other words, while easily able to ride their bike, the child would not have much in the way of words to describe how they achieved this childhood feat. In contrast to the example above, consider the same child’s experience during Karate class. It is likely that the child would have an instructor, suggesting that instruction would be used to facilitate the learning process. For example, the choku-zuki or “straight punch” would be a fundamental movement that the child would learn as they transition from their white belt to their yellow belt. In learning this movement, the instructor would teach the child proper body position, describe how their clenched fist should remain palm up and just above their belt, and further describe how the punch should be thrown in concert with the recoiling of the opposing arm. In this instance, the motor learning strategy would be considered deliberate or explicit. Specifically, the instructor would assume that the child would focus on the movement instructions while performing the straight punch, allowing them to learn the skill faster than had they been left to their own devices. What’s more, the instructor would also assume that, in time, the child’s ability to throw the straight punch would become more automatic, requiring less explicit attention from the child. This would be particularly important if the child was to demonstrate movement sequences or use the straight punch in a competitive setting. Thus, distinct from the implicit learning, the explicit learning pathway can be defined as learning that generates verbal knowledge of movement performance (e.g., facts and rules), involves cognitive stages (i.e., awareness) within the learning process, and is dependent on working memory involvement (Kleynen et al., 2014). Considering the examples provided above, it is necessary to highlight that, while distinct, both implicit and explicit learning pathways are essential to the motor learning process (Vidoni & Boyd, 2007). However, from a coaching standpoint, it is important to recognize the pedagogical or coaching strategies associated with each learning pathway, along with the mediating factors that guide the differential use of each strategy. With this in mind, it is valuable to first examine the underpinning
neuroscience associated with the learning process. Specifically, a coach’s awareness of the neural correlates (i.e., brain regions) connected to implicit and explicit learning, and the general influence of attention and memory on this process, will assist them in selecting coaching strategies that are both task type and experience level appropriate.
NEUROSCIENCE OF IMPLICIT AND EXPLICIT LEARNING Before discussing how best to apply implicit and explicit learning strategies, it is important to review the mediating role of attention and memory within the learning process and the associated neuroscience. In his seminal work, The Principles of Psychology, William (1890) captures the essence of attention when he states that “My experience is what I agree to attend to. Only those items which I notice shape my mind—without selective interest, experience is utter chaos.” These words highlight the importance of attention within the human experience, as people are only aware, and thus a product of that on which they focus. The alternative would find people, upon waking, having gained skills (e.g., playing the piano) for which they have no recollection of ever practicing. While this osmosis-esque version of super-learning may become a reality in future, for now one can be confident in knowing that learning is a product of what one pays attention to (Gallagher, 2009). Extending this line of thinking, Kahneman (2011) notes that people “dispose of a limited budget of attention that you can allocate to activities, and if you try to go beyond your budget, you will fail” (Miller, 1994). Thus, while the capacity to focus one’s attention exists, this capacity is limited and requires people to selectively attend to the information that is deemed most relevant for a given context. From this perspective, the role of the coach is to deploy strategies that help the athlete direct their attentional spotlight in a way that best serves the learning process. To understand how attention influences learning, it is important to first appreciate how what an athlete attends to impacts where the information is stored in the brain. Thus, just as there are explicit and implicit learning strategies, there are also explicit and implicit memory systems. Specifically, explicit memory, also known as declarative memory, are conscious memories of facts and rules pertaining to a motor skill, while implicit memory, also known as procedural memory, are the subconscious memories associated with the control and performance of a motor skill (Vidoni & Boyd, 2007). Put simply, explicit memory is required to describe a movement, while implicit memory is required to perform it. To highlight the impact coaching can have on the way memories are formed during the learning process, consider the following example of two baseball players being asked the same question by a reporter: “What are the key strategies to effective batting performance?” Athlete one might respond by providing rules and facts about batting, noting the best mental cues to use during practice, while athlete two, to the reporter’s disappointment, may respond by stating that they have no idea and pointing out that they just get up and swing. While fictional, these responses are not too dissimilar to notable quotes from famed golfer, Jack Nicklaus and Irish Rugby International, Ronan O’Gara, where Nicklaus stated that “concentration is a fine antidote to anxiety” and O’Gara proclaimed that “[he] knows how to kick a ball, but [has] no idea how to teach someone to kick a ball.” These examples highlight how information (i.e., explicit and implicit) about the same motor skill can be stored in distinct memory systems, and that the ability to perform a movement is not dependent on one’s ability to verbally describe it (e.g., Lam, Maxwell, & Masters, 2009). Thus, as will be shown later on, the way information is learned and stored has a lot to do with the robustness of the motor skill, especially when exposed to the stress of competition.
To illustrate how memory formation influences the learning process, it is important to now examine the distinct brain regions associated with the explicit and implicit memory systems. Specifically, there are three key areas that are involved in generating and integrating explicit memories as they relate to motor skill learning. These areas include, but are not limited to, the medial temporal lobe (hippocampus and associated cortices), the prefrontal cortex (the “seat of conscious processing”), and the dorsolateral prefrontal cortex (DLPFC) (Vidoni & Boyd, 2007). To appreciate how these brain regions are used in explicit memory formation and integration, consider the preceding baseball example once again. Specifically, re-visiting the answer of athlete one to the question of how to hit a baseball, it is evident that their coach would have used, at least in part, explicit learning strategies to teach them how to hit. That is, from a neuroscience standpoint, athlete one’s hippocampus and associated cortices would have been responsible for processing any instructions or feedback provided by their coach, ensuring that this information was readily available during batting practice or to answer a reporter’s question about hitting performance. What’s more, in applying the coach’s instructions while practicing, athlete one would have depended on their DLPFC to integrate any explicit thoughts held in working (short-term) memory with the visuospatial information (i.e., motion of pitcher and ball speed) required to hit the ball (Jueptner et al., 1997; Vidoni & Boyd, 2007). Thus, the DLPFC plays an important role in integrating the information contained within the explicit memory system and the motor actions that information is meant to influence within the implicit memory system. The implicit memory system involves a greater number of brain regions, which is not surprising considering its role in motor control. These brain regions include, but are not limited to, the cerebellum, the basal ganglia, and the cortical motor areas: the premotor cortex (PMC), the supplementary motor area (SMA), and the primary motor cortex (M1). Again, it is helpful to examine the function of these brain regions in the context of the baseball example. Specifically, while it is evident that athlete one has more explicit memories (i.e., facts and rules) of how to hit than athlete two, likely due to how they were coached, both athletes require the formation of implicit memories associated with the requisite motor control needed to hit a baseball. Thus, in learning how to hit, both athletes would have depended on their cerebellum to tune and optimize the hitting pattern. That is, the cerebellum is responsible for integrating sensory input and motor output in a way that allows the motor system to make real-time adjustments to the movement (Ivry, 1996; Vidoni & Boyd, 2007). This fine tuning of the movement is a hallmark of implicit learning. In addition to the cerebellum, the athletes would have depended on their basal ganglia to integrate explicit information with the implicit motor action and switch between motor tasks (i.e., hit the baseball, drop the bat, and run to first base). It is not surprising then that the basal ganglia operates like a “switchboard”, connecting disparate brain regions that are critical for motor control, notably the “motor circuit” regions (i.e., putamen, thalamus, SMA, and PMC) and the DLPFC described in the explicit memory section (Vidoni & Boyd, 2007). Damage to this region of the brain has been shown to slow the learning process and disrupt the influence of explicit information on performance and learning (Boyd & Winstein, 2006). Finally, the athletes would have depended on their primary motor cortex (M1) to initiate the swing in addition to fine tuning the coordination of the hitting motion. This fine tuning can be attributed to the role M1 plays in determining direction of motion and force output during movement (Vidoni & Boyd, 2007). Thus, like the cerebellum, the M1 is central to real-time motor control and the development of the implicit motor plan (Lohse, Wadden, Boyd, & Hodges, 2014). Working alongside the M1 are the PMC and the SMA. The PMC, via the basal ganglia, is responsible for integrating explicit
information relating to the sequence of a motor action (Vidoni & Boyd, 2007). Thus, if the coach was to give instructions around how to move the bat in space (i.e., swing path), the PMC would play a central role in integrating this information with the implicit motor plan for swinging a baseball bat. In contrast, the athletes would have depended more on their SMA when they were practicing without explicit information (i.e., coach input) (Vidoni & Boyd, 2007). That is, the SMA would leverage taskintrinsic feedback that could be used to modify the swing path, for example, on subsequent repetitions. However, this process would function in the absence of explicitly derived instruction or feedback. Interestingly, the PMC is highly active during early stages of learning where explicitly derived information is needed (Grafton, Hazeltine, & Ivry, 1995); however, as learning progresses there is a reduction in activity in the PMC in favor of increased activation of the SMA, highlighting its role in coordinating implicit motor actions (Toni, Krams, Turner, & Passingham, 1998). In summary, it is important to place the functional role of the disparate memory systems (i.e., explicit and implicit) and their associated brain regions within a practical context. That is, while the two systems interact, highlighting the importance of explicit and implicit learning strategies, it is important to understand that becoming overly reliant on explicit information can be detrimental to learning, especially during the rigors of competition (Baumeister, 1984; Masters, 1992). Specifically, research has shown that a form of neural competition can exist between explicit memory systems and implicit memory systems (Poldrack et al., 2001). Thus, while the explicit memory system is important during early stages of learning, independent of whether the information is explicitly derived from the coach or autogenously from the athlete, it can become detrimental to the execution of the implicit motor plan once learning consolidation has occurred (Song, 2009). That is to say, if the athlete starts thinking about a pattern for which there is already an implicit basis for automaticity, the thinking will disrupt the athlete’s ability to naturally self-organize the pattern in relation to task and environmental demands (i.e., “choking”). In support of this line of reasoning, Song (2009) notes the following when discussing the interaction between the explicit and implicit memory systems: Motor learning may initially rely on more explicit and prefrontal areas, but after extended practice and expertise, shift to more dorsal areas, but thinking about the movement can shift activity back to the less skilled explicit areas. Although many explanations may be derived, one could argue that these athletes show that even when years of practice has given the implicit system an exquisitely fine-tuned memory for a movement, the explicit system can interfere at the time of performance and erase all evidence of implicit memory. Therefore, it is important that coaches understand how to place explicit and implicit coaching strategies within the context of where the athlete is within their learning process. What’s more, it is important to understand how to deploy explicit coaching strategies in a way that supports the longterm learning and retention of desired motor skills, but doing so in a manner that will not thwart the expression of those skills in a competitive arena (i.e., choking and/or over-reliance on coaching feedback). To start seeding this information into a practical framework, the next section will discuss the integrative role of explicit and implicit coaching strategies within stage models of motor skill learning (e.g., Anderson, 1982; Fitts, 1964).
STAGE MODELS OF MOTOR SKILL LEARNING Stage models of motor skill learning (e.g., Anderson, 1982; Fitts, 1964) suggest that individuals will
transition from a cognitive or declarative stage (i.e., explicit memory)—whereby explicit rules are acquired concerning goal-relevant aspects of the motor skill, to an autonomous or procedural stage (i.e., implicit memory)—whereby goal-relevant aspects of the motor skill have been consolidated (Song, 2009) and are no longer consciously attended to during motor skill execution (Masters, 1992). Thus, independent of the coaching strategies used, the athlete learning a novel skill will naturally leverage their explicit memory system during the initial stages of the learning process and depend more on their implicit memory system during later stages of the learning process. That is to say, the athlete would naturally “pay attention” or be aware of performing the movement at first, however, once they lay down an implicit understanding of the movement process (e.g., coordinating upper and lower body in an effort to dribble a basketball) they would naturally be able to divert their attention to more relevant features of the environment (e.g., the approaching opponent or the teammate best suited to receive the ball and shoot a jump shot). To illustrate this point, it is instructive to examine the work of Beilock, Carr, MacMahon, and Starkes (2002) and Castaneda and Gray (2007), who showed that experts perform better when they focus on features of the environment (i.e., implicit learning), while novices benefit from focusing on the motor skill itself (i.e., explicit learning). In-line with these findings, Beilock et al. (2002) recommends that during early stages of learning it would be “beneficial to direct performers’ attention to step-by-step components of the skill, [while] at later stages of performance, this type of attentional control may be detrimental.” While the conclusion of Beilock et al. (2002) suggests that explicit learning strategies should be used with novices and implicit learning strategies with experts, coaches would be ill-advised to apply such a literal translation to their practice. For example, Masters (1992) identified an interaction between the way a motor skill is learned (i.e., practice) and one’s susceptibility to “choking” during a high-stress testing condition (i.e., competition). Specifically, one group of novices were asked to practice a golf putt while focusing on a specific set of instructions (i.e., explicit learning group), while a different group of novices practiced the same putt with no instructions and a secondary-task designed to deter explicit focus on the movement (i.e., implicit learning group). As one might expect, the novices in the explicit learning group “sunk” more putts during the practice sessions than the implicit learning group, although both groups significantly improved over the four practice sessions. However, this trend inversed when the participants were asked to putt under a high-stress test condition where they were led to believe that they would receive a monetary reward based on the evaluation of their performance by a golf professional. This illustrates two key points. First, as noted in the introduction, successful performance in practice is not necessarily indicative of an equally successful performance under stressful conditions. Second, implicit learning provides a certain level of protection over performance loss or “choking” during competition. Thus, this latter point suggests that there could be some benefit to using implicit learning strategies with a novice, especially as it relates to success in competition. Similarly, just as Masters (1992) has provided evidence for the benefit of implicit learning strategies for novices, Wulf and Su (2007) and Bell and Hardy (2009) have provided evidence that explicit learning strategies are beneficial for experts. Specifically, both studies showed that focusing on the outcome of a golf shot (e.g., club motion, club face position, or flight path of ball) resulted in significantly better performance and learning than focusing on the movement process (e.g., arm action or wrist position) in both novices and experts. Thus, this line of inquiry suggests that it is not information, in a general sense, that disrupts implicit motor learning, rather, it is the direction of focus (i.e., external or environment vs. internal or body) encouraged by the instruction that determines whether there is a positive or negative impact on learning. What’s more, similar research on the use
of analogies has shown that instructions that highlight the movement outcome or the effect the movement should have on the environment (e.g., Sprinting: Sprint as fast as you can past the 10-meter cone or push away from the start line as fast as you can) through an analogous cue (e.g., Sprinting: Drive out and away from the start line like a jet taking off), serve to support implicit learning as opposed to thwart it (Lam et al., 2009). Put simply, coaches can think of the explicit memory system as a conductor in an orchestra, guiding the general direction or outcome of the composition, while the implicit memory system is the many musicians that must coordinate their playing, just as joints and muscles must coordinate motion, generating a piece of music far more complex and beautiful than anything that would be created in isolation. Therefore, just as a conductor cannot and should not attempt to play every instrument, coaches should avoid explicit instructions that require the athlete to focus on one aspect of the movement at the expense of the whole, independent of whether they are a novice or an expert. In summary, it is important for coaches to recognize the necessary interplay between explicit and implicit learning strategies, as it is impossible to stop an athlete from thinking just as it is impossible to stop a coach from coaching. Thus, it is not a matter of picking sides, rather, coaches need to know when and how to apply explicit and implicit learning strategies to steward the athlete’s journey from novice to expert. For this reason, the next two sections will provide explicit and implicit coaching frameworks for optimizing performance and learning.
EXPLICIT COACHING FRAMEWORK The explicit coaching framework is chiefly concerned with the impact thinking has on the motor skill learning process. That is, while athletes may autogenously derive explicit thoughts concerning the movement they are learning, especially if the new skill is similar to a movement they know, this section is primarily concerned with the thoughts that are encouraged by the instruction and feedback provided by the coach. Specifically, instruction is used to focus an athlete’s attention on the most important characteristics of the motor skill being learned prior to movement execution, while feedback is used to inform the athlete of the outcomes (i.e., knowledge of results) and performance (i.e., knowledge of performance) associated with an already executed movement. Thus, instruction and feedback can be used to shape the attentional spotlight and focus the athlete on the most relevant features of the motor skill being learned. With this in mind, the following section will provide strategies for optimizing instruction and feedback in the context of the factors that mediate their influence on the learning process (e.g., experience level).
Instruction Instruction can be considered any verbal information that is provided to the athlete prior to them performing a given motor skill. The purpose of instruction is to facilitate the athlete focusing their attention on the most relevant feature of the motor skill being learned. For example, if a coach was teaching an athlete how to perform a vertical jump and they noticed that the athlete was not fully extending through their hips during the ascent of the jump, then they may select an instruction or cue that, if focused on during the jump, will help the athlete improve this attribute of the motor skill. This example illustrates an important assumption that needs to be confirmed for any coach interested in optimizing the effectiveness of their instructional strategies. Specifically, instructional strategies are
only as effective as they are relevant to the primary motor skill errors. That is to say, if a coach directs their instruction or cue at an irrelevant feature of the movement (e.g., cueing the upper body during a sprint when the source of the error exists within the lower body), then the end result will not be favorable, even if the substance of the instruction is representative of the strategies to follow (Polsgrove, Parry, & Brown, 2016). Thus, the first step to providing the athlete with explicit information that will support the learning process, is to ensure that the substance of the information is relevant to overcoming the identified movement error. Both Carson and Collins (2011) and Winkelman (2017) have provided models that suggest the importance of identifying the source of the motor skill error as a precursor to the deployment of explicit and implicit learning strategies. While the conceptualization of how to instruct has been broadly researched, the psychological domain of attentional focus has provided the greatest level of breadth and depth concerning the optimization of instruction and cueing (for a review, see Wulf, 2013). Specifically, an athlete can focus internally on the motion of their body (i.e., movement process) or externally on the effect their movements have on the environment (i.e., movement outcome) (Wulf et al., 1998). More specifically, instruction encouraging an internal focus will commonly direct attention towards joint motion (e.g., “extend your hips” or “flex your knees”) or muscle function (e.g., “squeeze your glute” or “lengthen your hamstring”), while an external focus encourages the athlete to focus their attention on the movement outcome (e.g., “jump as high as you can” or “sprint towards the finish line as fast as you can”) or the effect on the environment (e.g., “explode off the ground during the jump” or “push the ground back during the sprint”). To illustrate the application of these instructional strategies, consider the following example of a coach teaching an athlete how to perform the Olympic lifts. In one instance, the coach could provide an internal cue by telling their athlete to “focus on explosively extending through your hips,” alternatively, the coach could provide an external cue by telling their athlete to “focus on explosively pushing the ground away.” While the instructions carry the same message (i.e., get off the ground “explosively”), the internal cue calls attention to the body (i.e., hips) and the external cue calls attention to the environment (i.e., ground). These examples lead to an intuitive question, under what conditions is it best to use instructions or cues that encourage an internal focus versus an external focus? To answer this question, it is helpful to briefly review the research that has contrasted the differential influence of internal and external focus on practice performance and learning. While attentional focus has been widely studied, the following paragraphs will primarily focus on the literature pertinent to athletic performance (e.g., jumping and sprinting). For instance, Wulf, Zachry, Granados, and Dufek (2007) examined the effects of attentional focus on vertical jump performance. The results showed that novices jump significantly higher when they adopt an external focus (i.e., “focus on the highest rung of the Vertec”) compared to an internal focus (i.e., “focus on getting the tips of your fingers as high as possible”). Wulf and colleagues (Wulf & Dufek, 2009; Wulf, Dufek, Lozano, & Pettigrew, 2010) confirmed these findings and found that underpinning improved vertical jump performance were higher lower body impulses and joint moments and lower EMG in the lower body within the external focus condition, which suggests that a more efficient movement pattern is achieved (Lohse, Sherwood, & Healy, 2010; Vance, Wulf, Tollner, McNevin, & Mercer, 2004). What’s more, these findings have been extended to horizontal jumping, with all known research on the differential effects of internal and external focus showing that adopting an external focus of attention leads to significantly further jump distances during practice (e.g., Porter, Anton, & Wu, 2012; Porter, Ostrowski, Nolan, & Wu, 2010; Wu, Porter, & Brown, 2012). Similar to the jumping literature, the current evidence suggests that athletes learning to sprint
would be well advised to adopt an external focus of attention. Specifically, Ille, Selin, Do, and Thon (2013) and Porter, Wu, Crossley, and Knopp (2015) have provided evidence that novices exhibit superior sprint performance over 10m and 20m when they adopt an external focus opposed to an internal focus. However, both Porter and Sims (2013) and Winkelman, Clark, and Ryan (2017) have shown that as experience increases, so does the benefit of the athletes’ normal focus, which is commonly referred to as the control condition within attentional focus research. This finding makes sense, as one would expect that with experience comes the development of the implicit motor plan. This motor plan does not require as much explicit attention control, as the pattern has been consolidated and now exists within automatic motor control structures (Lohse et al., 2014). Thus, from a practical standpoint, it is beneficial to allow the experienced athlete to perform an increased number of repetitions without instructional reminders, as this will only strengthen their ability to autonomously deploy the motor skill when instruction and feedback is not available from a coach (e.g., competition). Finally, it is worth noting that the vast majority of research supports the findings presented above, showing that novices unquestionably benefit from an external focus of attention (Wulf, 2013), and that the advantage of a normal focus becomes evident as experience level with the motor skill increases (e.g., Stoate & Wulf, 2011; Wulf, 2008). However, it is worth noting that research has consistently shown that highly experienced individuals still benefit from an external focus of attention (e.g., Bell & Hardy, 2009; Ille et al., 2013; Wulf & Su, 2007). What’s more, in support of these findings, research has shown that an external focus of attention promotes greater movement velocity (e.g., Vance et al., 2004), force (e.g., Halperin, Williams, Martin, & Chapman, 2016), endurance (e.g., Marchant, Greig, Bullough, & Hitchen, 2011), and efficiency (e.g., Lohse & Sherwood, 2012). Considering these findings, it is not surprising that an external focus of attention has also been associated with greater cerebellar and primary motor cortex activation than an internal focus of attention (Zentgraf et al., 2009). Thus, one can argue that instruction encouraging an external focus, while explicit in nature, supports implicit learning to a greater degree than an internal focus. Moreover, this argument aligns with the constrained action hypothesis, which suggest that an internal focus “constrains the motor system by interfering with automatic motor control processes that would ‘normally’ regulate the movement”; while an external focus allows the “motor system to more naturally self-organize, unconstrained by the interference caused by conscious control attempts” (Wulf, McNevin, & Shea, 2001). For this reason, coaches should prioritize the use of externally focused instructions and cues, especially as it relates to optimizing the coordination required to perform in practice and express that performance in the context of competition (see Winkelman, 2017 for an applied model).
Feedback While instruction provides guidance prior to the execution of a motor skill, feedback provides the necessary information required to help the athlete reflect and apply new information to subsequent practice trials. From a practical perspective, the feedback given after the completion of a practice trial is often interwoven with the resultant instruction or cues meant to influence the ensuing practice. Thus, feedback plays a primary role in guiding motor skill learning by providing the substance required to continuously refresh instructions and cues. Two forms of feedback have been identified and will be the focus of this section. First, knowledge of results (KR) provides the athlete with information about a quantitative outcome. This could be
how high they jumped, how fast they covered a distance, their accuracy and thus proximity to a fixed point, or successful attempts as represented by a percentage. Alternatively, coaches can provide their athletes with a knowledge of performance (KP), which directly relates to the movement process or technique that led to a given outcome. This type of feedback is often subjective and requires the expertise of a coach. Examples of KP can be further broken down into prescriptive feedback, whereby the coach provides the athlete with specific instruction around how to correct an observed movement error (e.g., “on your next repetition, focus on getting off the ground faster”), and descriptive feedback, which simply requires the coach to describe the error without providing any corrective instruction (e.g., “your lower body was excessively flexed when you hit the ground”). Collectively, KR and KP are both important to guide the learning process, however, the application of these feedback strategies need to be considered in terms of the type of skill and the experience level of the athlete. For coaches to understand how best to apply feedback strategies, it is important to recognize the fundamental purpose of feedback. Specifically, the central role of feedback is to provide the athlete with pertinent information that they would not otherwise be aware of if not provided externally. Thus, coaches should seek to provide KR and KP that is not redundant to the task-intrinsic information associated with a given motor skill. To help illustrate this point, it is instructive to review the recommendations for providing feedback discussed by Magill (1994). 1. If the skill being learned does not allow the learner to detect critical sensory feedback information, such as when a limb’s spatial position cannot be seen, then augmented feedback is required. Recommendation one suggests that augmented feedback is required when visual or proprioceptive feedback is not available to the athlete or not associated with an established implicit motor plan. Thus, for an athlete just learning how to Olympic lift or to sprint, for example, it may be important to provide the athlete with KP on bar position in the case of the former and body position in the case of the latter. However, as the athlete develops an implicit motor plan and the associated sensory-motor representation (i.e., feel for the movement), then this information may become redundant to the taskintrinsic feedback now available to them. 2. If the skill being learned involves acquiring a new concept that is essential for successful performance, such as understanding a unit of measurement, then again, augmented feedback is required. Recommendation two encourages coaches to use feedback, specifically KR, when this information can help the athlete benchmark their performance against a quantitative outcome. For example, providing an athlete information about jump height or jump distance can help them to benchmark their current performance against the sensory consequences of achieving that outcome. They can then compare the good reps to the bad ones, which helps the athlete use sensory feedback associated with the execution of the motor skill to further refine their performance during practice. 3. If the skill provides the learner with all the essential feedback information needed to learn the skill, then augmented feedback may not be needed. As noted earlier, feedback is only impactful when it decreases uncertainty and provides the athlete
with new information. Thus, coaches should be critical to provide feedback that is not available to the athlete and prioritized based on the most critical movement errors that, if corrected, would allow learning to continue. 4. Skills for which the outcome is easy to determine but the limb coordination requirements to produce high-level performance are difficult to develop require knowledge of performance about limb movement characteristics. This final recommendation is highly specific to accuracy based tasks. These tasks could include passing a rugby ball, hitting a golf or tennis ball, kicking a field goal, or shooting a basketball. In all cases, there is task-intrinsic feedback about the outcome, however, less information would be readily available around the coordination required to achieve the desired outcome, especially for those that are novices. Thus, building on the last point, the context of the skill is often a key determinate of which type of feedback is most appropriate. While the preceding recommendations will guide the selection of appropriate feedback, there is still a need to understand how often feedback should be provided, commonly referred to as feedback schedules. The basis for this latter line of inquiry dates back to Salmoni, Schmidt, and Walter (1984), who suggested that there is a guidance effect associated with too much feedback. That is, feedback “acts as guidance, with immediate reward providing more guidance and perhaps leading to a reliance on such feedback for performance, and hence poorer performance in a transfer test” or during competition (Salmoni et al., 1984). Put simply, if feedback is provided too often, athletes may become dependent on feedback, possibly ignoring intrinsic sensory feedback that is important for establishing internal error-detection mechanisms, and they may also be encouraged to make too many explicit corrections during practice, which could make it difficult to establish a stable motor pattern (Anderson, Magill, Sekiya, & Ryan, 2005). From a practical standpoint, feedback should only be given as often as is needed to provide the athlete with the information necessary to progress their performance and learning. This will typically mean that more feedback is provided when an athlete is initially learning a skill, with a progressive reduction in feedback as the athlete gains experience. However, each time the difficulty of the skill is increased (e.g., progressing from a hang clean to a power clean), there will be a period of time where feedback is also increased. Thus, there is an interaction between experience level, skill complexity, and the amount of feedback required to support the learning process (Guadagnoli, Dornier, & Tandy, 1996). In an effort to help coaches optimize their feedback frequency, strategies have emerged to help overcome the negative impact of too much feedback. These strategies include bandwidth feedback (e.g., Lee & Carnahan, 1990), where feedback is only provided if the error is outside of a preset parameter or bandwidth (e.g., KR is only provided if bar speed during a bench press drops below a certain velocity or KP is provided only if a certain technical error is observed); faded feedback (e.g., Winstein & Schmidt, 1990), where feedback is systematically reduced over a given number of practice trials (e.g., 100% feedback for first set of 10 trials, 66% feedback for second set of 10 trials, and 33% feedback for third set of 10 trials); summary feedback (e.g., Schmidt, Lange, & Young, 1990), where feedback is provided as a summary following a certain number of trials (e.g., KR about jump height is provided after five jumps have been performed or KP about prominent technical errors is provided after three sprint repetitions have been performed); average feedback (e.g., Young & Schmidt, 1992), where feedback is represented as an average following a certain number of trails (e.g., KR concerning sprint times is averaged and provided to the athlete after three sprint efforts or
KP about the most common error observed across three repetitions of an agility drill); and selfcontrolled feedback (e.g., Chiviacowsky & Wulf, 2005; Janelle, Kim, & Singer, 1995), where the athlete is given the option to request feedback whenever they feel it is necessary (e.g., based on the task type and difficulty, athletes can request KR and KP at the rate that they feel is most appropriate for them). Note that all of these feedback scheduling strategies have evidence to support their efficacy, however, as noted earlier, this is often mediated by the type of skill, the complexity of the skill, and the experience level of the individual (Guadagnoli et al., 1996). Thus, coaches are encouraged to pay close attention to the progress within practice and the level of retention in competition, using these observable factors as guides to support the selection of an optimal feedback strategy. In summary, instruction provides a basis for guiding the motor learning process, while feedback plays a central role in refining the motor learning process. This interaction creates a learning loop, ensuring that explicit coaching strategies steward the learning process, but not at the expense of a robust implicit motor plan. In-line with this conclusion is the evidence showing that an external focus helps protect against choking under pressure (e.g., Lawrence, Gottwald, Khan, & Kramer, 2012; Ong, Bowco*ck, & Hodges, 2010). Thus, in light of the strategies discussed above, coaches are advised to keep their messages brief as to not overload working memory (i.e., one major point per repetition), provide feedback at a frequency that guides the learning process without creating dependence on the coach, and to ensure the substance of the message encourages an external focus of attention when at all possible.
IMPLICIT COACHING FRAMEWORK The implicit coaching framework is primarily concerned with the ecological dynamics associated with the learning process. Specifically, ecological dynamics describes how behavior emerges in accordance with the interaction of an organism, in this case the athlete, and their environment (Gibson, 1979). Within motor learning theory, an ecological or dynamical systems view is often associated with a constraint-led approach to teaching (Newell, 1985; Newell, 1986). That is, motor behavior is said to emerge as a result of the constraints inherent to the body, the environment, and the task. Thus, a change to the body (e.g., strength or mobility), the environment (e.g., the surface), and/or the task parameters (e.g., rules of a game) will result in a different movement solution (Newell, 1986). From this perspective, a constraint-led approach would suggest that in certain instances, a coach could manipulate constraints to encourage one movement solution over another. Intuitively, coaches do this all the time, however, it may be a function of chance rather than choice. Therefore, the following section will focus on how to effectively use a constraint-led approach to support learning through an implicitly emphasized pathway.
Constraint-led approach From a coaching perspective, it is best to consider the constraint-led approach as a conceptual framework that can be used to design learning rich environments. Specifically, coaches can systematically select constraints within the context of practice and specific drills to encourage the formation of adaptable “coordinative structures” (i.e., technique) (Anson, Elliott, & Davids, 2005). Thus, “constraints define the boundaries within which [the] human neuromuscular system must
operate and, therefore, shape the emergence of patterns of coordination and control” (Glazier & Davids, 2009). This idea that movement emerges in accordance with internal and external constraints was referred to by Bernstein (1967) as the “degrees-of-freedom problem” (e.g., Vereijken, Emmerik, Whiting, & Newell, 1992) and is now commonly described as the “Bernstein problem” (Turvey, 1990). The notion that movements are a solution to a problem provides coaches with an accessible metaphor for designing practice. That is, coaches can view themselves as teachers, the athlete as their student, and movement as the subject being taught. Therefore, practice is designed to pose a series of problems (i.e., drills or tactical scenarios) that the athlete must answer by searching for the most effective movement solution.
FIGURE 19.1
Newell (1986) interacting constraints model.
To illustrate this last point, consider the following examples. First, imagine a coach trying teaching their athlete how to squat for the first time. Suppose that they notice the athlete’s knees consistently going inward (i.e., valgus) despite providing explicit instruction to focus on vertical alignment. In this instance, if instruction is ineffective, then the coach can use a constraint to help the athlete selfcorrect. Specifically, a common constraint used in this scenario would be to place an elastic miniband around the knees (i.e., task constraint) and instruct the athlete to “keep tension through the band” as they squat. This constraint provides new sensory information about the knee position, increasing the “signal” and, thus, the salience of the error to be corrected. Second, if the same coach is instructing a different athlete how to perform a kettlebell swing and finds that they are not fully extending their hips during the completion of the motion, then they may decide to use a spatial constraint. Specifically, the coach can have the athlete swing the kettlebell in front of a wall. This limits the athlete’s ability to leave the kettlebell too far forward, encouraging effective hip extension as to avoid hitting the wall. Thus, while a change in proprioceptive sense led to the change in the last example, in the present example, it would be the presence of new visual information that drives the change in movement behavior. Finally, consider a coach who has identified that their athlete tends to look down when attempting to cut or side-step an opponent while on offense. In this case, the coach can deploy spatial and temporal task constraints to encourage the athlete to perceive and act quicker than they currently are. Specifically, the coach can design a 5m × 5m box, marked by cones in each corner, and have the athlete in question stand in one corner and face a defender in the diagonal corner. The coach would then instruct the athlete, ball in hand, to sprint forward and attempt to exit the upper
left or right sides of the box without being tagged by the defender. The box provides the spatial constraint, limiting the amount of movement options, while the defender provides the time constraint, limiting how much time the athlete has to make their decision. This environment creates a safe and repeatable opportunity for the player to work through the error and improve their ability to pick-up the correct visual information, allowing them to anticipate the defender’s movement and side-step in a game-relevant context. The key similarity in the examples noted above, which qualifies why these strategies are referred to as implicit, is that the athlete would not be aware of the specific reason for the improvement, however, they would be quite aware that they are making progress. Thus, unlike explicit learning strategies, constraint-led implicit strategies allow learning to take place outside the athlete’s conscious awareness of the source of improvement. To place these examples in a broader context, it is helpful to understand the various categories of constraints. Newell (1986) presented the first theoretical model proposing how movement emerges from the interaction of constraints that exist within the organism, environment, and task (see Fig. 19.1). From an organism standpoint, there are two major categories of constraints, structural and functional (Glazier & Davids, 2009; Newell, 1986). Structural constraints are relatively stable over time and include genetic (e.g., muscle fiber type) and anthropometric (e.g., height, weight, and limb length) features (Shemmell, Tresilian, Riek, & Carson, 2004). However, structural constraints can change, albeit slowly, with improvements in strength, power, and flexibility being exemplars. Conversely, functional constraints are more susceptible to rapid change and include psychological attributes such attention, memory, intention, perception, emotion, and decision-making (Glazier & Davids, 2009; Kelso, 1997). Thus, as highlighted by the explicit coaching framework, the instruction, cues, and feedback we use operate as informational constraints that directly influence the behavior and movement solutions deployed by athletes. As the name implies, environmental constraints include all constraints external to the organism. This would include light, temperature, surface, implements, and gravity (Glazier & Davids, 2009). As one might assume, these constraints are more difficult to manipulate, as most coaches cannot quickly change temperature, altitude, and/or the type of surface that they are playing on. What’s more, it is for this reason that many movement behaviors become ubiquitous in sport, as they emerge as a direct consequence of a constant environment. While most environmental constraints are constant, those that can be varied are often associated with the task itself and can be defined as such. Task constraints are a form of environmental constraint (Newell & Jordan, 2007) that directly relate to the desired outcomes of the movement (e.g., lifting the weight or making the shot). Specifically, task constraints include the space the movement is being performed in, the time the movement can be performed in, and the goals, rules, and equipment associated with the movement behavior. While the sport dictates space (i.e., field size), time (i.e., game time), and rules at one level, the opponent, in team sports, is equally able to further manipulate the space (e.g., pushing a player into touch in rugby) and time (e.g., charge a player, forcing them to quickly make a decision) an athlete has to achieve a given outcome via a specific movement behavior. Thus, constraint couplings become ubiquitous in sport and typically create the boundaries for teaching an athlete how to play a given sport; however, it is equally viable to manipulate these constraints within the context of practice to encourage one movement solution over another. Therefore, whether trying to improve the accuracy with which an athlete kicks and passes, or how that same athlete coordinates the major upper and lower body lifts in the weight room, all movement is subject to modification through a constraint-led approach. In summary, movement behavior is constantly being nudged by the constraints that exist within and
outside of the human body. From birth, constraints guide and influence our development (Thelen, Fisher, & Ridley-Johnson, 1984), placing the environment front and center as the first coach/teacher one meets in life. What’s more, there is a strong evolutionary basis for implicit learning (Reber, 1992) and, thus, the importance of constraints. This is not surprising considering that movement emerged long before one had the ability to think about movement (Sugarman, 2002). For this reason, coaches are encouraged to define the stable and variable constraints that exist across the organism, the environment, and the task, relative to their sporting context, as these constraints will impose the largest pressure on learning. In identifying these constraints, coaches can prioritize how best to manipulate their influence on the learning process. For example, an athlete who lacks the requisite relative strength and power (i.e., organismic constraints) to effectively accelerate may benefit from additional work within the weight room, as increased sprinting on the field will not improve these qualities to the same degree. Conversely, if a coach has identified a player who needs to improve their acceleration ability, however, their relative strength and power is already established, then it may be best to use environmental and task constraints to encourage improvements in the coordination associated with their acceleration. As illustrated by these examples, the constraint-led approach can serve to inform an athletic profile, providing coaches with a framework to map and prioritize where and how time should be spent to support the development of the athlete.
CONCLUSION The primary objective of every coach is to guide the learning process, encouraging progressive improvements in practice performance that transfer to the competitive environment. As discussed, when a gap emerges between the performance observed in practice and competition, an athlete is often labeled as “choking.” However, from a skill acquisition standpoint, this gap is also a reflection of the quality of the learning process. Thus, coaches are encouraged to actively monitor and assess learning outside of the context with which learning is meant to take place (i.e., practice). From a sport coaching perspective, this is as simple as benchmarking an athlete’s performance in practice versus competition. While a gap may have to do with susceptibility to anxiety and worry, this cannot explain all underperformance. Thus, coaches can use this as feedback to adapt their teaching and their approach to designing learning environments. Equally, a strength and conditioning coach can benchmark their effectiveness by having their experienced athletes perform a given lift without any initial instruction. This serves to see what information has been retained and can be applied without the explicit guidance of the coach, highlighting any implicit learning that has taken place. In a way, the quality of the learning observed within the athlete acts as a constraint on the way the coach deploys explicit and implicit learning strategies. For example, an athlete that has difficulty transferring performance in practice, when a coach is present, to the competitive environment, where the coach is absent, may depend too much on explicit guidance. Similarly, an athlete who is struggling to understand a drill or make progress within a given lift may benefit from explicit information that externally guides their attention towards the desired outcomes. Thus, while all motor learning must find a resting place within the implicit memory system, the pathway taken to get there will be highly individualized and guided by the seamless integration of explicit and implicit coaching strategies.
REFERENCES
Anderson, D.I., Magill, R.A., Sekiya, H., & Ryan, G. (2005). Support for an explanation of the guidance effect in motor skill learning. Journal of Motor Behavior, 37(3), 231–238. Anderson, J.R. (1982). Acquisition of cognitive skill. Psychological Review, 89(4), 369. Anson, G., Elliott, D., & Davids, K. (2005). Information processing and constraints-based views of skill acquisition: Divergent or complementary? Motor Control, 9(3), 217–241. Baumeister, R.F. (1984). Choking under pressure: Self-consciousness and paradoxical effects of incentives on skillful performance. Journal of Personality and Social Psychology, 46(3), 610. Beilock, S. (2010). Choke: What the Secrets of the Brain Reveal About Getting It Right When You Have To. New York, NY: Simon and Schuster. Beilock, S.L., Carr, T.H., MacMahon, C., & Starkes, J.L. (2002). When paying attention becomes counterproductive: Impact of divided versus skill-focused attention on novice and experienced performance of sensorimotor skills. Journal of Experimental Psychology: Applied, 8(1), 6–16. Bell, J.J. & Hardy, J. (2009). Effects of attentional focus on skilled performance in golf. Journal of Applied Sport Psychology, 21(2), 163–177. Bernstein, N.A. (1967). The Co-ordination and Regulation of Movements. London: Pergamon Press. Boyd, L.A. & Winstein, C.J. (2006). Explicit information interferes with implicit motor learning of both continuous and discrete movement tasks after stroke. Journal of Neurologic Physical Therapy, 30(2), 46–57. Carson, H.J. & Collins, D. (2011). Refining and regaining skills in fixation/diversification stage performers: The Five-A Model. International Review of Sport and Exercise Psychology, 4(2), 146–167. Castaneda, B. & Gray, R. (2007). Effects of focus of attention on baseball batting performance in players of differing skill levels. Journal of Sport and Exercise Psychology, 29(1), 60–77. Chiviacowsky, S. & Wulf, G. (2005). Self-controlled feedback is effective if it is based on the learner’s performance. Research Quarterly for Exercise and Sport, 76(1), 42–48. Fitts, P.M. (1964). Categories of human learning. In A. W. Melton (Ed.), Perceptual–Motor Skills Learning. New York, NY: Academic Press. Gallagher, W. (2009). Rapt: Attention and the Focused Life. New York, NY: Penguin. Gibson, J.J. (1979). The Ecological Approach to Visual Perception. Hillsdale, NJ: Lawrence Erlbaum Associates. Glazier, P.S. & Davids, K. (2009). Constraints on the complete optimization of human motion. Sports Medicine, 39(1), 15–28. Grafton, S.T., Hazeltine, E., & Ivry, R. (1995). Functional mapping of sequence learning in normal humans. Journal of Cognitive Neuroscience, 7(4), 497–510. Guadagnoli, M.A., Dornier, L.A., & Tandy, R.D. (1996). Optimal length for summary knowledge of results: The influence of task-related experience and complexity. Research Quarterly for Exercise and Sport, 67(2), 239–248. Halperin, I., Williams, K.J., Martin, D.T., & Chapman, D.W. (2016). The effects of attentional focusing instructions on force production during the isometric mid-thigh pull. The Journal of Strength and Conditioning Research, 30(4), 919–923. Ille, A., Selin, I., Do, M.C., & Thon, B. (2013). Attentional focus effects on sprint start performance as a function of skill level. Journal of Sports Sciences, 31(15), 1705–1712. Ivry, R.B. (1996). The representation of temporal information in perception and motor control. Current Opinion in Neurobiology, 6(6), 851–857. Janelle, C.M., Kim, J., & Singer, R.N. (1995). Subject-controlled performance feedback and learning of a closed motor skill. Perceptual and Motor Skills, 81(2), 627–634. Jueptner, M., Stephan, K.M., Frith, C.D., Brooks, D.J., Frackowiak, R.S., & Passingham, R.E. (1997). Anatomy of motor learning. I. Frontal cortex and attention to action. Journal of Neurophysiology, 77(3), 1313–1324. Kahneman, D. (2011). Thinking Fast and Slow. New York, NY: Farrar, Straus and Giroux. Kelso, J.S. (1997). Dynamic Patterns: The Self-Organization of Brain and Behavior. Cambridge, MA: MIT Press. Kleynen, M., Braun, S.M., Bleijlevens, M.H., Lexis, M.A., Rasquin, S.M., Halfens, J., Wilson, M.R., Beurskens, A.J., Masters, R.S. (2014). Using a Delphi technique to seek consensus regarding definitions, descriptions and classification of terms related to implicit and explicit forms of motor learning. PLoS One, 9(6), e100227. Lam, W., Maxwell, J., & Masters, R. (2009). Analogy versus explicit learning of a modified basketball shooting task: Performance and kinematic outcomes. Journal of Sports Sciences, 27(2), 179–191. Lawrence, G.P., Gottwald, V.M., Khan, M.A., & Kramer, R.S. (2012). The movement kinematics and learning strategies associated with adopting different foci of attention during both acquisition and anxious performance. Frontiers in Psychology, 3(468), 1–11. Lee, T.D. & Carnahan, H. (1990). Bandwidth knowledge of results and motor learning: More than just a relative frequency effect. The Quarterly Journal of Experimental Psychology, 42(4), 777–789. Lohse, K., Wadden, K., Boyd, L., & Hodges, N. (2014). Motor skill acquisition across short and long time scales: A meta-analysis of neuroimaging data. Neuropsychologia, 59, 130–141. Lohse, K.R. & Sherwood, D.E. (2012). Thinking about muscles: The neuromuscular effects of attentional focus on accuracy and fatigue. Acta Psychologica, 140(3), 236–245. Lohse, K.R., Sherwood, D.E., & Healy, A.F. (2010). How changing the focus of attention affects performance, kinematics, and
electromyography in dart throwing. Human Movement Science, 29(4), 542–555. Magill, R.A. (1994). The influence of augmented feedback on skill learning depends on characteristics of the skill and the learner. Quest, 46(3), 314–327. Marchant, D.C., Greig, M., Bullough, J., & Hitchen, D. (2011). Instructions to adopt an external focus enhance muscular endurance. Research Quarterly for Exercise and Sport, 82(3), 466–473. Masters, R.S. (1992). Knowledge, knerves and know-how: The role of explicit versus implicit knowledge in the breakdown of a complex motor skill under pressure. British Journal of Psychology, 83(3), 343–358. Miller, G. (1994). The magical number seven, plus or minus two: Some limits on our capacity for processing information. 1956. Psychological Review, 101(2), 343–352. Newell, K. (1985). Coordination, control and skill. Advances in Psychology, 27, 295–317. Newell, K.M. (1986). Constraints on the development of coordination. Motor Development in Children: Aspects of Coordination and Control, 34, 341–360. Newell, K.M. & Jordan, K. (2007). Task constraints and movement organization: A common language. In W. E. Davis & G. D. Broadhead (Eds.), Ecological Task Analysis and Movement. Champaign, IL: Human Kinetics. 5–23. Ong, N.T., Bowco*ck, A., & Hodges, N.J. (2010). Manipulations to the timing and type of instructions to examine motor skill performance under pressure. Frontiers in Psychology, 1(196), 1–13. Poldrack, R.A., Clark, J., Pare-Blagoev, E.J., Shohamy, D., Creso Moyano, J., Myers, C., & Gluck, M.A. (2001). Interactive memory systems in the human brain. Nature, 414(6863), 546–550. Polsgrove, M.J., Parry, T.E., & Brown, N.T. (2016). Poor quality of instruction leads to poor motor performance regardless of internal or external focus of attention. International Journal of Exercise Science, 9(2), 10. Porter, J.M., Anton, P.M., & Wu, W.F. (2012). Increasing the distance of an external focus of attention enhances standing long jump performance. Journal of Strength and Conditioning Research, 26(9), 2389–2393. Porter, J.M., Ostrowski, E.J., Nolan, R.P., & Wu, W.F. (2010). Standing long-jump performance is enhanced when using an external focus of attention. Journal of Strength and Conditioning Research, 24(7), 1746–1750. Porter, J.M. & Sims, B. (2013). Altering focus of attention influences elite athletes sprinting performance. International Journal of Coaching Science, 7(2), 41–51. Porter, J.M., Wu, W.F.W., Crossley, R.M., & Knopp, S.W. (2015). Adopting an external focus of attention improves sprinting performance in low-skilled sprinters. Journal of Strength and Conditioning Research, 29(4), 947–953. Reber, A.S. (1992). The cognitive unconscious: An evolutionary perspective. Consciousness and Cognition, 1(2), 93–133. Salmoni, A.W., Schmidt, R.A., & Walter, C.B. (1984). Knowledge of results and motor learning: A review and critical reappraisal. Psychological Bulletin, 95(3), 355. Schmidt, R.A., Lange, C., & Young, D.E. (1990). Optimizing summary knowledge of results for skill learning. Human Movement Science, 9(3), 325–348. Shemmell, J., Tresilian, J.R., Riek, S., & Carson, R.G. (2004). Musculoskeletal constraints on the acquisition of motor skills. In A. M. Williams & N. J. Hodges (Eds.), Skill Acquisition in Sport: Research, Theory and Practice. London: Routledge. 390–408. Soderstrom, N.C. & Bjork, R.A. (2015). Learning versus performance: An integrative review. Perspectives on Psychological Science, 10(2), 176–199. Song, S. (2009). Consciousness and the consolidation of motor learning. Behavioural Brain Research, 196(2), 180–186. Stoate, I. & Wulf, G. (2011). Does the attentional focus adopted by swimmers affect their performance? International Journal of Sports Science and Coaching, 6(1), 99–108. Sugarman, R. (2002). Evolution and executive functions: why our toolboxes are empty. Revista Española de Neuropsicología, 4(4), 351–377. Thelen, E., Fisher, D.M., & Ridley-Johnson, R. (1984). The relationship between physical growth and a newborn reflex. Infant Behavior and Development, 7(4), 479–493. Toni, I., Krams, M., Turner, R., & Passingham, R.E. (1998). The time course of changes during motor sequence learning: A whole-brain fMRI study. Neuroimage, 8(1), 50–61. Turvey, M.T. (1990). Coordination. American Psychologist, 45(8), 938–953. Vance, J., Wulf, G., Tollner, T., McNevin, N., & Mercer, J. (2004). EMG activity as a function of the performer’s focus of attention. Journal of Motor Behavior, 36(4), 450–459. Vereijken, B., Emmerik, R.E.A.V., Whiting, H.T.A., & Newell, K.M. (1992). Free(z)ing degrees of freedom in skill acquisition. Journal of Motor Behavior, 24(1), 133–142. Vidoni, E.D., & Boyd, L.A. (2007). Achieving enlightenment: What do we know about the implicit learning system and its interaction with explicit knowledge? Journal of Neurologic Physical Therapy, 31(3), 145–154. William, J. (1890). The Principles of Psychology. New York, NY: Dover Publications. Winkelman, N.C. (2017). Attentional Focus and Cueing for Speed Development. Strength and Conditioning Journal. Winkelman, N.C., Clark, K.P., & Ryan, L.J. (2017). Experience level influences the effect of attentional focus on sprint performance. Human Movement Science, 52, 84–95. Winstein, C.J. & Schmidt, R.A. (1990). Reduced frequency of knowledge of results enhances motor skill learning. Journal of
Experimental Psychology: Learning, Memory, and Cognition, 16(4), 677. Wu, W.F., Porter, J.M., & Brown, L.E. (2012). Effect of attentional focus strategies on peak force and performance in the standing long jump. Journal of Strength and Conditioning Research, 26(5), 1226–1231. Wulf, G. (2008). Attentional focus effects in balance acrobats. Research Quarterly for Exercise and Sport, 79(3), 319–325. Wulf, G. (2013). Attentional focus and motor learning: A review of 15 years. International Review of Sport and Exercise Psychology, 6(1), 77–104. Wulf, G. & Dufek, J.S. (2009). Increased jump height with an external focus due to enhanced lower extremity joint kinetics. Journal of Motor Behavior, 41(5), 401–409. Wulf, G., Dufek, J.S., Lozano, L., & Pettigrew, C. (2010). Increased jump height and reduced EMG activity with an external focus. Human Movement Science, 29(3), 440–448. Wulf, G., Höß, M., & Prinz, W. (1998). Instructions for motor learning: Differential effects of internal versus external focus of attention. Journal of Motor Behavior, 30(2), 169–179. Wulf, G., McNevin, N., & Shea, C.H. (2001). The automaticity of complex motor skill learning as a function of attentional focus. The Quarterly Journal of Experimental Psychology, 54(4), 1143–1154. Wulf, G. & Su, J. (2007). An external focus of attention enhances golf shot accuracy in beginners and experts. Research Quarterly for Exercise and Sport, 78(4), 384–389. Wulf, G., Zachry, T., Granados, C., & Dufek, J. (2007). Increases in jump-and-reach height through an external focus of attention. International Journal of Sports Science and Coaching, 2(3), 275–284. Young, D.E. & Schmidt, R.A. (1992). Augmented kinematic feedback for motor learning. Journal of Motor Behavior, 24(3), 261–273. Zentgraf, K., Lorey, B., Bischoff, M., Zimmermann, K., Stark, R., & Munzert, J. (2009). Neural correlates of attentional focusing during finger movements: A fMRI study. Journal of Motor Behavior, 41(6), 535–541.
Index Page numbers in italics refer to figures. Page numbers in bold refer to tables. absolute strength phase (weightlifting) 264 acceleration see sprint running accentuated eccentric training 25 accuracy based tasks, and feedback 338 active heat maintenance 158 acute: chronic workload ratio 144–145, 145; calculation of 146 acute training load 144 adaptation 118–122; biological 137–138, 137–138; general adaptation syndrome 120, 121, 137, 137; muscular 63, 118, 276–277; neural 277; to plyometric training 276–278; vs. recovery 179–181; stimulus-fatigue-recovery-adaptation theory 120, 121, 122 adenosine monophosphate-activated kinase (AMPK) 103 adenosine triphosphate (ATP) 87–88, 89, 234 aerobic capacity 73, 81 aerobic fitness 72–73; exercise intensity zones 75–76, 76; high-intensity training 77–79; lowintensity/easy training 76; measuring 74–75; psychological determinants of endurance performance 73–74; and repeated-sprint ability 91, 92–93; role in repeated sprint activity sports 80–81; smallsided games training for 81–83; strength training for 79–80; threshold/steady training 77, 77; training 75–83, 93 aerobic metabolism 91–92 aerobic power 73, 81, 82 after-effects of training 122 agility: definition of 292; perceptual-cognitive factors underpinning 298–299; programming to improve 305; qualitative evaluation of 302–303, 303; quantitative evaluation of 300, 301, 302; testing 300; see also change of direction (COD) air/wind resistance, in sprint running 312 alternate-leg bounding 156, 282 amortization phase (stretch-shortening cycle) 274–275 5’ AMP-activated protein kinase (AMPK) 180 anaerobic glycolysis 89–90; hydrogen ion flux and buffer capacity 90–91 anaerobic power 95 androgen receptors, and resistance training 57 ankle jump 279 ankle stiffness, and performance 46, 50 anterior cruciate ligament (ACL) injuries: Functional Movement Screen 214–215; Landing Error Scoring System 216, 217; single leg hop 221, 222
antioxidants (AO), for recovery 171–174 attentional focus 3; and instruction 334–335; and learning 329, 332 augmented feedback 240, 337 average feedback 338 back door cut 304 background of athletes 6 back squat 27, 239, 250; force-velocity characteristics in 231; load placement in 232; using variable resistance with chains 27, 28 ballistic exercises: complex training 25; and firing frequency 19; for muscular power/strength 29; and post-activation potentiation 156–157; and resistance training 233–234 bandwidth feedback 338 barbell hip thrust 232 basal ganglia 330–331 basketball players, aerobic fitness of 80–81 behaviour: and cortisol 65–66; and testosterone 58 benchmarking, and feedback 337 bench press: ballistic 233; using variable resistance with elastic bands 27, 28 “Bernstein problem” 340 bilateral hops 281, 282 bilateral squat 239 bilateral training, for muscular power/strength 26–27 binomial distribution 141 biological adaptation 137–138, 137–138 biomechanics 4, 4; of change of direction 292–296; of overhead squat 207; of sprint acceleration 313–314 block periodisation 20 bodyweight exercise, for muscular power/strength 22–23 box jumps 283 brain regions associated with memory 330–331 braking phase: change of direction 292, 297; sprint running 312, 314, 315; SSC tasks 41, 45; vertical jump 196, 197 breath-by-breath systems 74 British Association of Sport and Exercise Sciences (BASES) 4 buffer capacity 90–91 caffeine 152, 160 calisthenics 158 carbohydrate (CHO) supplementation, for recovery 169–171 cardio-respiratory development, and concurrent training 103–104 cardiovascular fitness see aerobic fitness carnosine 90 catch, snatch/clean 253–255, 254–255 catching derivatives, weightlifting 259–260 cautionary coach feedback (VCCF) 59, 154
cellular stress, cold water immersion for 174 centre of mass (COM) 295, 299, 312, 315 cerebellum 330 change of direction (COD): biomechanics of 292–296; capacity building and skill enhancement 304; deficit 299, 302, 302, 303; definition of 291–292; development model 304, 305; impulse and ground contact times during 292–295, 293, 294; joint kinematics and kinetics during 295–296; perceptual-cognitive factors underpinning agility 298–299; physical capacities underpinning 297–298; plant phase 292–294, 293; and plyometric training 278; programming to improve 305; qualitative evaluation of 302–303, 303; quantitative evaluation of 300, 301, 302, 302; return to play of athletes 302–303, 303; scientific research and current applied practice 299–300; stance phase 292; underpinning factors related to 296–299; see also agility change of direction speed (CODS): definition of 292; tests 300 choking 327, 328, 332, 333, 342 chronic training load 144, 147 circadian rhythm, and testosterone release 60, 152 clean (weightlifting): catch 253–255, 254–255; first pull 250, 252, 252, 265–266; hang power clean 239, 259; recovery 255, 256; second pull 253, 254, 260; snatch/clean transition 252–253, 253; see also power clean clothing, for maintaining heat 157–158 cluster sets 235–236, 236; weightlifting 259–260, 263 coach 1–3; considerations for 6–8, 7 coaching 7–8, 327–329; analysis 6; constraint-led approach 304, 339–342; contexts 3; cues 240; explicit coaching framework 334–339; implicit coaching framework 339–342; neuroscience of implicit and explicit learning 329–332; non-contact 5–6, 7; science of 3–4; stage models of motor skill learning 332–333 cold water immersion (CWI), for recovery 174–175, 176–177; during endurance training 180–181; during strength training 179–180 combination loading 30, 231 communication 3–4 competence 3 competition: demands 6; pre-competition strategies to pre-training 158–159; recovery strategies for 181; resistance training before 152 competitive performance 327 competitive phase of periodisation 117 complex training (CT) 277; for muscular power/strength 25–26 compression garments, for recovery 177–178 concentric phase (stretch-shortening cycle) 275 concurrent training 79, 101, 159; decision making process during periods of 110; frequency, volume, and mode 108–109; intensity 107–108; interference effect 102–104; periodisation 104–105; recovery 106–107; session, sequencing 105–106; strategies to minimise interference 104–109 confidence 3, 8 conjugate sequence system 128–129, 129, 129 connection 3, 8 constrained action hypothesis 336 constraint-led approach 304, 339–342
constraints model (Newell) 340, 341 contexts 3, 75 control condition 335 Cori cycle 90 cortisol 60, 64, 234; and behaviour 65–66; and circadian rhythm 152; concentration levels 65; and concurrent training sequencing 106; moderating effect on testosterone 65–66; see also testosterone countermovement jump (CMJ) 193, 279; force-time curve 197 countermovement shrug 260 coupled successive system see conjugate sequence system creatine 152, 160 creatine kinase (CK) 169 cricket, training loads in 144 criterion method, for data analysis 197 critical non-essentials (CNe) 6 cross-sectional area (CSA), muscle: and concurrent training 102–103; and muscular power/strength 14–16, 16, 17 cryotherapy, for recovery 174–175; whole body cryotherapy 175–177 cueing: plyometric training 279, 281; resistance training 240; see also feedback, coaching; instruction, coaching cyclists: cold water immersion for 180; recovery of 173 data analysis 4; fitness testing 196–198, 197, 198; for RSA training 96 declarative memory see explicit memory decrease in the ratio of force (DRF), in sprint running 316, 317, 318, 322–323 deep squats 215, 230 degrees-of-freedom problem see Bernstein problem demands, sport/competition 6 depth jumps 156, 283 descriptive feedback 336 detraining 120 dip phase, jerk 255–256, 256 distance runners, and motor unit recruitment 19 dorsolateral prefrontal cortex (DLPFC) 330, 331 dose-response relationship 78, 79, 144 Douglas bag method 74 drop jumps (DJs) 45–46, 279, 281, 282, 283; and joint stiffness 46; and leg stiffness 46, 47, 50 dynamical systems theory 296 dynamic strength tests 191–192; protocol standardisation for 195 eccentric phase (stretch-shortening cycle) 274 eccentric training, for muscular power/strength 24–25 eccentric utilisation ratio (EUR) 193 ecological dynamics of learning 338 effectiveness, coaching 2, 3 Ekblom’s soccer specific endurance circuit 82
elbow flexion exercises, and testosterone release 61 electromyograms (EMGs) 102; overhead squat assessment 207; single leg squat assessment 210 electronic timing gates 194, 195, 319 elite athletes 63–64; aerobic fitness of 80; concurrent training for 104, 105; performance, and testosterone levels 58, 66, 152 emergent learning see implicit learning emotional intelligence 2 endocrinology, and resistance training 56; cortisol 64–66; hormone-receptor complex 56–57; muscle remodelling 57; testosterone 57–64 endurance performance: and antioxidants 172; and periodisation 104; and plyometric training 278; psychological determinants of 73–74 endurance training 101; and aerobic fitness 79–80; recovery after 181; using cold water immersion during 179–180; see also concurrent training; resistance training energy system, high-intensity interval training based on 96 environmental constraints 341 equipment selection, fitness testing 193–195 exercise-induced muscle damage (EIMD) 172 exercise-induced oxidative stress 171 exercise intensity zones 75–76, 76 exercise programming 7 experienced/expert athletes 63–64; learning strategies for 332, 333; performance, effects of attentional focus on 335, 336 expertise, coaching 3 explicit coaching framework 334–339; feedback 336–339; instruction 334–336 explicit learning 328; benefits for experts 333; neuroscience of 329–332 explicit memory 329–330; brain regions associated with 330 exploratory factor analysis 215, 220 explosive strength training 79, 80 exponential taper 131 external focus 335 external workload 140 faded feedback 338 fatigue: Fitness-Fatigue paradigm 122, 123, 138; non-chemical sources of 92; and plyometric training 284; and potentiation 237; residual 159; stimulus-fatigue-recovery-adaptation theory 120, 121, 122; 3:1 loading paradigm 118, 119 fatigue index (FI) 96 feedback, coaching 334–336; cautionary coach feedback 59, 154; positive coach feedback 59, 154, 160; pre-match/post-match video with feedback 59; purpose of 337; resistance training 240–241; see also cueing feedback schedules 338 female athletes, carbohydrate/protein supplementation for 171 fibres, muscle: and plyometric training 277; Type II fibres 64, 174; Type II:I fibres, ratio of 16 field computation method 316–319 firing frequency, and muscular power/strength 19
first pull, snatch/clean 250, 252, 265–266; end of first pull 252; starting position 252 first step quickness 311 Fitness-Fatigue paradigm 122, 123, 138 fitness testing 190; data analysis 196–198, 197, 198; equipment selection 193–195; order 196; reasons for doing 190; standardising protocols 195–196; test selection 191–193; timing of 190–191 505 COD test 299, 303 flight/swing phase (sprint running) 311, 312 flight time method 194 footwear, resistance training 238 force plates, for assessing overhead squat 206 force platforms 193 force production 155; capacity 14–15; and circadian rhythm 60; and firing frequency 19; and ground reaction forces 311–312; and heavier loads 30; and muscle tendon stiffness 50; and neuromuscular inhibition 20; vectors, resistance training 232–233; and weightlifting 260–261, 264 force-time data analysis 196 force-velocity characteristics, in resistance training 231 force-velocity (F-v) profile (sprint running) 311, 316–319, 318; individualized training based on 319–320; individual profiling and training program 320–323 force-velocity (F-v) profile (weightlifting) 261–265, 262; absolute strength phase 264; maximal strength phase 264; speed-strength phase 265; strength-endurance phase 263; strength-speed phase 264 forward acceleration, in sprint running 312, 313, 316 four-by-four running method 93 free sprinting 322, 323 free weight training 23 frequency, training 120; concurrent training 108–109; plyometric training 281 frontal plane projection angle (FPPA) of knee joint, during single leg squat 211 front squat 239; force production vectors 232; load placement in 232 full squats 241–242 functional constraints 341 functional foods, for recovery 174–174 Functional Movement Screen (FMS) 205, 212–216; injury prediction 214 functional overreaching 139 gastrocnemius-soleus-achilles complex (GSAC) 314 general adaptation syndrome (GAS) 120, 121, 137, 137 general physical training (GPT) 116–117 gravitational force, in sprint running 312 grip: handgrip strength 66; hook grip 231, 250, 251; resistance training 230–231 ground contact patterns, in sprint running 314 ground contact time (GCT): during change of direction 292–295, 294, 297–298; in sprint running 313–314 ground-leg interaction, in sprint running 312 ground reaction force (GRF): and change of direction 296; and force production 311–312; in running
47; in sprint running 311–312, 313, 315, 319 growth hormone (GH) 65, 234; and hypertrophy 62, 63 guidance effect (feedback) 338 half-squats 241; ballistic 233–234 half-time 157 handgrip strength 66 hang high pull 260, 261, 265 hang power clean 239, 259 hang power snatch 259 heat gains, protection of 155, 160 heat maintenance strategies 157–158 heavy day/light day loading 30 hexagonal bar jump 232 high force training see resistance training high-intensity interval training (HIIT) 77–79; for aerobic fitness 92–93; based on energy system 96; calculation of interval distances 94 high jumps, and leg stiffness 46–47 high velocity training 16 hip extensors, role in sprint running 313–315 ‘hip hinge’ strategy 207 hippocampus 330 Hooke’s Law 40, 40 hook grip 231, 250, 251 hopping: bilateral hops 281, 282; and leg stiffness 46; single leg hop 206, 221–223, 223 hop tests 221–223 horizontal force (HF), in sprint running 312, 313, 315, 317, 319 horizontal jumps: and barbell hip thrust 232; performance, effects of attentional focus on 335 horizontal power, in sprint running 316–317, 322 hormonal priming 154, 163 hormone-receptor complex 56–57 hormones: definition of 56; growth hormone 62, 63, 65, 234; see also endocrinology, and resistance training Hudl Technique 207, 211 hydrogen ion flux 90–91 hyperoxia, and repeated-sprint ability 92 hypertrophy 15–16, 18, 57, 67; effects of low vs. high load resistance training on 63; and rest intervals 63, 234; and testosterone/growth hormone 62, 63 implicit coaching framework 339–342 implicit learning 328, 342; benefits for novices 333; and external focus 336; neuroscience of 329–332 implicit memory 329–330, 331–332; brain regions associated with 330 implicit motor plan 331, 335, 337, 339 impulse, during change of direction 292–295
impulse-momentum theorem 293 inflammation: cold water immersion for 175, 180, 181–182; functional foods for 173; and muscle remodelling 57 injury: prevention programs 217; using Functional Movement Screen for predicting 214–215; using workload information for predicting 140–142, 141, 142, 144–145, 145, 146–147 instruction, coaching 334–336; see also cueing insulin 65 intensity, training 116, 117, 118; concurrent training 107–108; plyometric training 282–283 intensity, warm-up 154–155, 160 interference effect 79, 102–104, 159; cardio-respiratory development 103–104; molecular signalling 103; muscular development 102–103; neural development 102 internal focus 334–335 internal workload 140 interpersonal knowledge 2, 7 inter-repetition rest intervals, resistance training 235–236 inter-set rest intervals: effect on resistance exercise-induced muscle hypertrophy 63; plyometric training 281; resistance training 234–235 interval training (aerobic fitness) 76, 81; and repeated sprint activity sports 80; see also highintensity interval training (HIIT) intrapersonal knowledge 2, 7 intra-set rest intervals, plyometric training 281 introspection 2 involution see detraining iPhone apps, for measuring jump height 194 ischemic preconditioning (IPC) 153–154, 163; combining prior priming exercise with 153, 160 isometric strength tests 192 jerk (weightlifting): dip 255–256, 256; drive 257, 257; receiving positions 257–258, 257, 258; recovery 258, 258; starting position 255, 256 joint kinematics/kinetics, during change of direction 295–296 joint stiffness 42–43; effects of training interventions on 48, 50; influence of joint touchdown angles on 44; joint moment-joint angular displacement relationship 43; and performance 46–47; torsional spring model 42 Judo 154 jump mats 194 jumps: ankle 279; box 283; countermovement 193, 197, 279; depth jump 156, 283; height, measuring 194; hexagonal bar jump 232; high 46–47; horizontal 232, 335; and leg stiffness 46–47; squat jump 16, 193; static jump 279; tuck jump assessment 219–221, 219; see also drop jumps (DJs); plyometric training (PT); vertical jumps jump shrug 260, 261, 265 jump squat 60, 232; force-velocity characteristics in 231 jump testing 193; movement screening in 205; protocol standardisation for 195 kayakers, concurrent training for 105, 106 kettlebell training: for muscular power/strength 27–29; swing 340
kinematics: joint, during change of direction 295–296; sprint running 314, 315 kinetics: joint, during change of direction 295–296; sprint running 314, 315, 316 knee stiffness, and performance 46, 50 knee valgus: and overhead squat 207, 208; and tuck jump assessment 220 knowledge of coach 2 knowledge of performance (KP) 336–337 knowledge of results (KR) 336–337 lactate 62, 234; and anaerobic glycolysis 90 lactate threshold (LT) 73, 74, 76, 77; and small-sided games 81–82 lactate turnpoint (LTP) 73, 74, 77–79 Landing Error Scoring System (LESS) 206, 216–219, 223; operational definitions 217; score sheet 218 large muscle group exercises, and testosterone release 61 learning 327–328; and attention 329, 332; impact of practice performance on 328; implicit/explicit, neuroscience of 329–332; and memory 329–330; see also coaching Le Chatelier’s principle 90 leg stiffness 43–44; effects of training interventions on 48, 50; influence of joint touchdown angles on 44; and performance 46–47; spring-mass model 45 lifestyle see performance lifestyle Limb Symmetry Index (LSI) 221 linear position transducers 192, 195 linear taper 131 loads, training: chronic training load 144, 147; combining heavy and light loads 30; and injury likelihood 141, 141, 144; low vs. high loads 63; monitoring 8; optimal 30; placement, resistance training 232; protective effect of 144, 145; volume-equated resistance training loading strategies 63; weightlifting 259 lock and key theory 56 logistic regression model 141 logit link function 141 long-latency response (LLR) 41 lower limb: joint stiffness 42–43, 42–43; leg stiffness 43–44, 45; muscle-tendon stiffness 41–42; stretch-shortening cycle 39–40 low-intensity training (aerobic fitness) 76 machine-based exercises 23 macrocycles 117 mammalian target of rapamycin (mTOR) 103; and strength training 79 maneuverability 292, 297 marathon running 101; recovery of runners 173 marginal gains 5–6 match-day performance, priming 151; heat maintenance strategies 157–158; hormonal priming 154; ischemic preconditioning 153–154; modification of warm-ups 154–157; organizing pre-match period 162; post-activation potentiation 155–157, 163; practical applications 159–160, 161–162, 163; pre-competition strategies to pre-training 158–159; prior priming exercise 152–153, 160;
sleep deprivation effects, attenuating 151–152; strategies implemented during scheduled withinmatch breaks 157–158; strategies implemented less than three hours before a match commences 153–157; strategies implemented more than three hours before a match commences 151–153; typical activities performed in 12 hours before match 161 maximal aerobic capacity see maximal oxygen uptake (V̇O2 max) maximal aerobic speed (MAS) 93, 94 maximal lactate steady state (MLSS) 74, 77–79 maximal lower body strength, and Functional Movement Screen 213 maximal oxygen uptake (V̇O2 max) 73, 74 maximal sprint performance 193 maximal strength phase (weightlifting) 264 maximal test 74 maximal velocity running, and injury likelihood 145, 146–147 maximal velocity sprint, force-time curve of plant phase and stance phase 293 maximal voluntary contraction (MVC) 172 maximal voluntary isometric contraction (MVIC) 210 maximum horizontal external power output (Pmax), in sprint running 321–322 mechanical model of stretch-shortening cycle potentiation 275, 275 mechanical stress 168 medial gastrocnemius (MG) 16, 45–46 medial knee displacement see knee valgus medial temporal lobe 330 medium-latency response (MLR) 41 memory: brain regions associated with 330–331; and learning 329–330; types of 329 mesocycles 117, 118 metabolic stress 168 method of amplification of error (MAE) 240–241 metrics, workload 143 microcycles 117; non-traditional periodisation 130; summated 126 mid-thigh pull 260–261, 262, 265, 270 milk 169, 170 mode: of concurrent training 108–109; of plyometric training 279 molecular signalling, and concurrent training 103 monotony, training 122, 124 Montmorency cherry juice, effects on recovery 173 motion analysis of overhead squat 205–206 motivation 154; and testosterone 64; and training 59; videos 59 motor skill learning 328; and memory systems 329–332; stage models of 332–333 motor units: definition of 18; recruitment, and muscular power/strength 18–19; synchronisation, and muscular power/strength 20 movement screening 6, 205–206; Functional Movement Screen 212–216; Landing Error Scoring System 216–219, 217, 218; overhead squat 205, 206–209, 208–209; package 222, 223, 224; single leg squat 209–212, 211–212; tuck jump assessment 219–221, 219 movement specificity 249–250
multi-faceted nature of strength and conditioning 9 multijoint isometric strength tests 192 Multi-Stage Fitness Test (MSFT) 74, 193 muscle activation strategies 41, 46 muscle architecture 17–18, 18 muscle excitability 92 muscle protein synthesis 169 muscle recruitment strategies 50, 92 muscle remodelling 57 muscle stabilisers 23 muscle-tendon stiffness (MTS) 41–42; joint 42–43, 42–43; leg 43–44, 45; and performance 45–48, 48; and training 48–51, 49 muscle-tendon unit (MTU) 40, 41, 284 muscular adaptations: effects of volume-equated resistance training loading strategies on 63; and periodisation 118; and plyometric training 276–277 muscular development, and concurrent training 102–103 muscular power/strength: ballistic vs. non-ballistic exercises 29; bodyweight exercise 22–23; combining heavy and light loads 30; complex training 25–26; cross-sectional area 14–16, 16, 17; definition of 13; eccentric training 24–25; firing frequency 19; importance of 13–14; kettlebell training 27–29; loading considerations 29–30; machine vs. free weight training 23; morphological factors affecting 14–18; motor unit recruitment 18–19; motor unit synchronisation 19–20; neuromuscular factors affecting 18–20; neuromuscular inhibition 20; optimal loads 30; periodisation model 20–21, 21; plyometric training 24; power output 14; rate of force development 14, 15; and rest intervals 235; and tendon stiffness 50–51; and testosterone 58, 60, 64; training considerations 20–29; training status 31; training to failure 29–30; unilateral vs. bilateral training 26–27; variable resistance training 27; weightlifting exercises 23–24 muscular strength: and aerobic fitness 80; definition of 232; effects of low vs. high load resistance training on 63; and force-velocity profile 263; and plyometric training 277; see also muscular power/strength musculotendinous unit (MTU) 274, 275 My Jump app 194 MySprint app 319 N-acetylcysteine (NAC) supplementation, effects on recovery 172 needs analysis 305, 306 neural adaptations, and plyometric training 277 neural development, and concurrent training 102 neuromuscular electrical stimulation (NMES), for recovery 178–179 neuromuscular inhibition, and muscular power/strength 20 neurophysiological model of stretch-shortening cycle potentiation 275, 275 Newton’s second law 13 non-ballistic exercises: for muscular power/strength 29; and resistance training 233–234 non-contact coaching 5–6, 7 non-functional overreaching 139 non-traditional periodisation 129–130, 130
novice athletes 63–64; learning strategies for 332–333; performance, effects of attentional focus on 335 nutrition 4, 4; and recovery 169, 182, 182 oestrogen 170 one repetition maximum (1-RM) test 48, 191–192, 259; back squat test 30, 195; power clean test 192 onset blood lactate accumulation (OBLA) 74 optimal loads 30; in sprint running 321–322 optimum training dose 137–140 outcomes, athlete 2–3 overhead press 240 overhead squat 205, 206–209, 208–209, 223; anterior view 208; arms fall forward 209; assessment, instructions for 210; excessive forward lean 208; external rotation of feet 208; knee valgus 208; lateral view 208; lower back arching 209; lower back rounding 209; posterior view 208 overload 58, 250 overreaching 139–140; planned 116, 120, 122, 127 overtraining 139–140 overtraining syndrome 139 oxidative phosphorylation 73; and repeated-sprint ability 92 parallel elastic component (PEC) 275 parallel squats 230 partial squats 230, 241 partial unilateral training see unilateral training passive heat maintenance 155 patella-femoral pain syndrome (PFPS) 210, 211 peak aerobic capacity see peak oxygen uptake (VO2 peak) peak oxygen uptake (VO2 peak) 73, 74 pennation angle of muscle 16, 16, 17, 18 perceptual-cognitive factors underpinning agility 298–299 perceptual-motor ability 298 performance: effects of attentional focus on 335; endurance 73–74, 104, 172, 278; knowledge of performance 336–337; lifestyle 5–6; maintaining peak performance for 35 weeks 129; maximal sprint performance 193; physical performance testing 6; practice vs. competitive 327; resistance training modifications for 237–240; and stiffness 45–48, 48; test, Functional Movement Screen 213–214, 215; see also match-day performance, priming periodisation 7, 116; advanced model of 127–129, 127, 127; application of 124–129; basic model of 124–126, 125, 125; concurrent training 104–105; defining 116–118; exercise deletion and representation 124; Fitness-Fatigue paradigm 122, 123; general adaptation syndrome 120, 121; intermediate model of 126, 126, 127; maintaining peak performance for 35 weeks 129; maintenance programmes 129–130; models 20–21, 21, 67; non-traditional approach to 129–130, 130; phases of 116–117, 117; of plyometric training 284–285, 285; recovery and adaptation 118–122; stimulus-fatigue-recovery-adaptation theory 120, 121, 122; taper 130–131, 131, 132, 133, 133; training monotony 122, 124
peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1a) 180 phase potentiation see periodisation phosphocreatine (PCr) 88–89, 234 phosphofructokinase (PFK) 89 phosphorylase 89 Physical Activity Enjoyment Scale 82 physical capacities underpinning change of direction 297–298, 302; building 304 physical performance testing 6 physiology 4, 4 planned overreaching 116, 120, 122, 127 planning of coach 7 plyometric training (PT) 16, 250, 274; adaptations to 276–278; exercises 280; frequency and recovery 281, 282; general preparation phase 286; impulsive ability/explosiveness phase 284, 285, 285, 287; mode and specificity of 279, 281; for muscular power/strength 24; periodisation of 284–285, 285; progression 283–284; push-ups 233; strength phase 286; stretch-shortening cycle 274–276, 275; and tuck jump assessment 220; unilateral vs. bilateral 26; volume and intensity 282–283 positive coach feedback (VPCF) 59, 154, 160 post-activation potentiation (PAP) 25, 155–157, 163 post-match video with feedback 59 postural screening 6 potentiation: potentiation complex rest intervals, resistance training 236–237; stimulus, ballistic exercises as 233–234; stretch-shortening cycle 274–275, 275 power: aerobic 73; anaerobic 95; horizontal, in sprint running 316–317, 322; maximum horizontal external power output 321–322; muscular see muscular power/strength; relative power outputs of exercises 22; strength-power potentiating complexes 25–26 power clean 259, 270; derivatives, kinetic variables across 267–269; hang power clean 239, 259; 1RM power clean test 192; position 255; see also clean (weightlifting) power jerk, receiving position 257, 258, 258 power output 14 power snatch 240, 255, 259, 270 power-velocity (P-v) relationships, in sprint running 316–317 practice performance 327, 333; impact on learning 328 prefrontal cortex 330 prehabilitation 7 preload stimulus volume 156 pre-match video with feedback 59 premotor cortex (PMC) 330, 331 preparatory phase of periodisation 116–117, 118 pre-programmed aspect of muscle activation 41 prescriptive feedback 336 pre-season training cycle, fitness testing during 190–191 pre-training, application of pre-competition strategies to 158–159 primary motor cortex (M1) 330 principle of diminishing returns 122, 124
prior priming exercise 152–153, 160; combining with IPC 153, 160 procedural memory see implicit memory professional knowledge 2, 7 propulsive phase: change of direction 292; sprint running 312, 314; SSC tasks 45, 275; vertical jump 196, 197 protein supplementation, for recovery 169–171 protocols, fitness testing 195–196 p70S6K 180 psychology 4, 4 pull from the floor 260–261, 263, 265 pull from the knee 260 pulling derivatives, weightlifting 260–261 push-ups, plyometric 233 pyruvate dehydrogenase (PDH) 89 quarter-squats 230, 241 quasi-stiffness 43 range of motion (ROM): resistance training 229–230; specificity 241–242 rate coding see firing frequency rate of force development (RFD) 14, 15, 79–80, 231, 264; and change of direction 297; and firing frequency 19; speed-strength training blocks 260 rating of perceived exertion (RPE) 140–141, 143 ratio of forces (RF), in sprint running 315, 316, 317, 318, 321 re-analysis 6 recovery 137–138, 137–138, 168; acute carbohydrate/protein supplementation 169–171; vs. adaptation 179–181; antioxidants and functional foods 171–174; cold water immersion 174–175, 179–181; compression garments 177–178; concurrent training 106–107; emerging therapies 175–179; guidelines for practical application 181–182; neuromuscular electrical stimulation 178–179; periodisation 118–122; and plyometric training 281, 282; post-warm-up 155; practical recommendations for 182, 183; strategies, in practice 179–182; whole body cryotherapy 175–177 reflective marker 211 reflex aspect of muscle activation 41 rehabilitation 7, 23, 209, 221 repeated-sprint ability (RSA) 87; aerobic metabolism 91–92; anaerobic glycolysis 89–91; biochemistry of 87–88; non-chemical sources of fatigue 92; PCr 88–89; tests, reporting results from 95–97; training to improve 92–95, 93–94 repeated sprint activity sports 76; role of aerobic fitness in 80–81; using small-sided games training for 81–83 repetition maximum (RM): loads, training with 29; and stiffness 48; and testosterone release 61; see also one repetition maximum (1-RM) test resistance training 101, 229; for aerobic fitness 79–80; ballistic and non-ballistic exercises 233–234; combined with plyometric training 277, 284; before competition 152; complex training 25; and cross-sectional area of muscle 16; cueing 240; and endocrinology see endocrinology, and resistance training; exercise technique 229–231; feedback 240–241; footwear 238; force
production vectors 232–233; force-velocity characteristics 231; grip and stance variation 230–231; for improving sprint performance 319; inter-set/inter-repetition rest intervals 235–236; inter-set rest intervals 234–235; load placement 232; mechanical demands of exercises 231–234; modalities, for muscular power/strength 21–29; modifications for appropriate exercise performance 237–240; and muscle architecture 17; potentiation complex rest intervals 236–237; range of motion 229–230, 241–242; and rate of force development 14; recovery after 181; relative power outputs of exercises 22; rest intervals 234–237, 235; and stiffness 48, 50; stretch-shortening cycle 231–232; types of 79; unilateral training alternatives 239–240; unilateral vs. bilateral training 26; using cold water immersion during 179–180; variable 27; weightlifting movements 238, 239; see also concurrent training resisted sprints 321 rest intervals, resistance training 234–237 rewarm-ups 158 rugby 101; periodisation 129; prediction of injury in 141–142, 141, 142; protection of heat gains 155; sleep deprivation effects in 151–152; small-sided games 82; sprint momentum 295 running: four-by-four running 93; ground reaction force during 47; and leg stiffness 46, 47, 50; for maintaining heat 158; marathon 101, 173; maximal velocity running 145, 146–147; and muscletendon stiffness 47–48; velocity running 46; see also sprint running running economy 73, 74; and low-intensity/easy training 76; and plyometric training 278; threshold/steady training 77 sampling frequency capability, of fitness testing equipments 195 science: of coaching 3–4; definition of 4 scientist 4–5, 4 second pull, snatch/clean 253, 254, 260 self-controlled feedback 338 sensory feedback 337, 338 sequencing: of concurrent training sessions 105–106; of exercises, and testosterone levels 60 series elastic component (SEC) 275 shoes, weightlifting 238 short-latency response (SLR) 41 single leg hop (SLH) 206, 221–223, 223 single leg squat (SLS) 205, 209–212, 211, 223; assessment, instructions for 213; hip drop 212; hip hike 212; inward trunk rotation 212; knee valgus 211; outward trunk rotation 212 situational factors of coaching 3 skills-based conditioning games 82 sleep: deprivation, attenuation of effects 151–152, 160; quality/quantity of 182, 182 slow-continuous method, and testosterone release 62 small-sided games: during half-time 158; to improve aerobic fitness 81–83 snatch (weightlifting) 239; catch 253–255, 254, 255; first pull 250, 252, 265–266; hang power snatch 259; power snatch 240, 255, 259, 270; recovery 255, 256; second pull 253, 254, 260; transition 252–253, 253 soccer: and aerobic fitness 80; and concurrent training 104; maintaining peak performance in 129; recovery of players 173; small-sided games 81, 82 social environment, effects on testosterone 59
sodium bicarbonate 90 soft skills 2 soreness, muscle: CHO-protein supplementation for 169, 171; cold water immersion for 174, 175; compression garments for 177; neuromuscular electrical stimulation for 178; whole body cryotherapy for 175–176 spatial constraints 340 spatial task constraints 340–341 specificity: movement 249–250; of plyometric training 279, 281; range of motion 241–242; sportspecificity 117, 205 speed and acceleration training: force-velocity profile definition and field computation method 316–319, 318; individualized training based on F-v profiling 319–320; individual profiling and training program 320–323; sprint running 310–316; see also sprint running speed development (weightlifting) 265, 266; early-mid competition phase 270; general preparation phase 265–266; late competition/taper phase 270; special preparation phase 266 speed-strength phase (weightlifting) 265 split jerk, receiving position 257, 257 split squat 26, 239 sport science 4–5 sport-specificity 117, 205 sport-specific physical training (SSPT) 116–117 spring-mass model 43–44, 45 sprint decrement (Sdec) 96 sprint momentum 295 sprint running 310–312; cueing 240; effectiveness of force application onto the ground 315–316; focus in 304; force-velocity profile definition and field computation method 316–319, 318; individualized training based on F-v profiling 319–320; and leg stiffness 46; muscular determinants of acceleration performance 313–315; performance, effects of attentional focus on 335; periodisation 129; phases of 311; transfer phenomenon 319; see also repeated-sprint ability (RSA) sprint testing: maximal sprint performance 193; measurement of timing 194; protocol standardisation for 195 squat 340; back 27, 28, 231, 232, 239, 250; bilateral 239; deep 215, 230; and footwear 238; front 232, 239; full 241–242; half- 233–234, 241; jump 60, 231, 232; parallel 230; partial 230, 241; quarter- 230, 241; split 26, 239; variations 230; see also overhead squat; single leg squat (SLS) squat jump (SJ) 16, 193 stability: core 213–214; and unilateral/bilateral training 27, 240; and weightlifting shoes 238 stance, resistance training 230–231 stance/support phase (sprint running) 311, 312, 313 static jump 279 steady training (aerobic fitness) 77, 77 step taper 131 stiffness 40–41; joint 42–43, 42–43; leg 43–44, 45; muscle-tendon stiffness see muscle-tendon stiffness (MTS) stimulus-fatigue-recovery-adaptation (SFRA) theory 120, 121, 122 strength-endurance phase (weightlifting) 263
strength-power potentiating complexes (SPPCs) 25–26 strength-speed phase (weightlifting) 264 strength training see resistance training stress 137, 138; cellular 174; exercise-induced oxidative stress 171; mechanical 168; metabolic 168; physiological response to 120, 121, 168, 179; type and timing of 181–182, 182 stretch reflex 275 stretch-shortening cycle (SSC) 39–40, 274–276; and change of direction 297; phases of 274–275; potentiation 274–275, 275; resistance training 231–232; see also muscle-tendon stiffness (MTS) stride frequency, in sprint running 312 stride length, in sprint running 312 structural constraints 341 subjective measures 143–144 submaximal test 74, 75 summary feedback 338 summated microcycles 126 supercompensation 120, 122, 137 supplementary motor area (SMA) 330, 331 tactical metabolic training 130 take-off velocity method 193 taper 130, 131; optimal taper strategy 131, 133, 133; strategies 131, 132 task constraints 340, 341 task-intrinsic feedback 331, 337, 338 team briefings 154, 160, 163 team sports 82, 101; and acceleration 310; competitive phase in 117; first step quickness in 311; see also match-day performance, priming; rugby; soccer temperature: cryotherapy 174–177; heat gains, protection of 155, 160; heat maintenance strategies 157–158 temporal phase analysis 196–197, 198 temporal task constraints 340–341 tempo training (aerobic fitness) 76 tendon see muscle-tendon stiffness (MTS) testosterone 57, 65, 154; and behaviour 58; and circadian rhythm 60, 152; and concurrent training sequencing 106; and hypertrophy 62, 63; levels, and athlete experience 63–64; moderating effect of cortisol on 65–66; and muscular power/strength 58, 60; priming, via non physical interventions 59; release, manipulating acute resistance training variables to enhance 61–62; release, manipulating exercise sessions to enhance 60–61; see also cortisol theoretical maximal force (F0), sprint running 321 three intensity zone model 76, 76 3:1 loading paradigm 118, 119 threshold training (aerobic fitness) 77, 77 torsional-spring model 42, 42 ‘total time to complete’ measure 299 touchdown, and joint stiffness 43, 44 training: aerobic fitness 75–83; application of pre-competition strategies to pre-training 158–159;
frequency see frequency, training; intensity see intensity, training; monitoring 137–140; monotony 122, 124; optimum training dose 137–140; overtraining 139–140; recovery strategies for 181; status, of athletes 31; and stiffness 48–51, 49; -stress balance see acute: chronic workload ratio; videos 154; volume see volume, training; zones, aerobic fitness 78; see also specific entries training load (TL) see loads, training training to failure method 29–30 transition, snatch/clean 252–253, 253; mid-thigh position 253 triple extension 249, 257 tuck jump assessment (TJA) 206, 219–221; grading criteria for 219 two-dimensional video analysis, of single leg squat 211 2-phase taper 131, 132 ultramarathon runners, recovery of 172 unilateral training: for muscular power/strength 26–27; resistance training 239–240 variable resistance training, for muscular power/strength 27 vastus lateralis (VL) 45–46 velocity at the onset of blood lactate accumulation (vOBLA) 95 velocity at V̇O2 max (V̇O2 max) 74, 74; and aerobic metabolism 91; and high-intensity training 78; and repeated-sprint ability (RSA) 93–95; and small-sided games 81 velocity-based training 241 velocity running: and leg stiffness 46; maximal velocity running, and injury likelihood 145, 146–147 velocity time-curve 311 verbal persuasion 154 vertical force (VF) 232, 266, 270, 315 vertical jumps: assessment using force platform 195; force-time data analysis 196, 197; and front squat 232; and kettlebell training 28; and leg stiffness 46; performance, effects of attentional focus on 335; and plyometric training 24, 278 “Very Heavy Sled” (VHS) training 321 Vitamin C supplementation, for recovery 171–173 Vitamin E supplementation, for recovery 171–173 volitional training performance, and testosterone 58 volume, training 116–117, 117; concurrent training 108–109; plyometric training 282–283 volume-equated resistance training loading strategies 63 walking, and muscle-tendon stiffness 47–48 warm-ups: intensity, increasing 154–155, 160; post-activation potentiation 155–157; protection of heat gains 155, 160; rewarm-ups 158 weighted vests 283 weightlifting 101, 249; catching derivatives 259–260; force-velocity profile, developing 261–265, 262; jerk dip 255–256, 256; jerk drive 257, 257; jerk receiving positions 257–258, 257, 258; jerk starting position 255, 256; and motor unit recruitment 19; pulling derivatives 260–261; shoes 238; snatch/clean catch 253–255, 254–255; snatch/clean first pull 250, 252, 252; snatch/clean recovery 255, 256; snatch/clean second pull 253, 254, 260; snatch/clean transition 252–253, 253; speed development 265–270, 266; speed-strength training blocks 260; technique 250–258
weightlifting movements 238; and ballistic exercises 233; effectiveness of 249–250; movement specificity 249–250; for muscular power/strength 23–24; overload 250 well-being: continuum 140; subjective 143 well trained athletes 63–64 whole body cryotherapy (WBC) 175–177 Woodward, Clive 6 workload monitoring: external and internal workloads 140; facts about 144–145; gold standard 143; overreaching and overtraining 139–140; prediction of injury 140–142, 141, 142; subjective measures 143–144; training monitoring and optimum training dose 137–140; well-being continuum 140 work to rest ratios 120 Yo-Yo Intermittent Recovery Test (YIRT) 74, 193 z-score 302
