More than a Metric: How Training Load is Used in Elite Sport for Athlete Management

Abstract Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load data is usually undertaken with a view to improve player performance and/or manage injury risk. To target these outcomes, practitioners attem...

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Veröffentlicht in:	International journal of sports medicine Jg. 42; H. 4; S. 300 - 306
Hauptverfasser:	West, Stephen W., Clubb, Jo, Torres-Ronda, Lorena, Howells, Daniel, Leng, Edward, Vescovi, Jason D., Carmody, Sean, Posthumus, Michael, Dalen-Lorentsen, Torstein, Windt, Johann
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Rüdigerstraße 14, 70469 Stuttgart, Germany Georg Thieme Verlag KG 01.04.2021
Schlagworte:	Athletes Athletic Injuries - prevention & control Athletic Performance Communication Data Collection - methods Data Interpretation, Statistical Decision Making Humans Physical Conditioning, Human - methods Review Risk Management - methods Sports - physiology Stakeholder Participation Workload - statistics & numerical data workload training performance injury
ISSN:	0172-4622, 1439-3964, 1439-3964
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Abstract	Abstract Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load data is usually undertaken with a view to improve player performance and/or manage injury risk. To target these outcomes, practitioners attempt to optimise load at different stages throughout the training process, like adjusting individual sessions, planning day-to-day, periodising the season, and managing athletes with a long-term view. With greater investment in training load monitoring comes greater expectations, as stakeholders count on practitioners to transform data into informed, meaningful decisions. In this editorial we highlight how training load monitoring has many potential applications and cannot be simply reduced to one metric and/or calculation. With experience across a variety of sporting backgrounds, this editorial details the challenges and contextual factors that must be considered when interpreting such data. It further demonstrates the need for those working with athletes to develop strong communication channels with all stakeholders in the decision-making process. Importantly, this editorial highlights the complexity associated with using training load for managing injury risk and explores the potential for framing training load with a performance and training progression mindset.
AbstractList	Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load data is usually undertaken with a view to improve player performance and/or manage injury risk. To target these outcomes, practitioners attempt to optimise load at different stages throughout the training process, like adjusting individual sessions, planning day-to-day, periodising the season, and managing athletes with a long-term view. With greater investment in training load monitoring comes greater expectations, as stakeholders count on practitioners to transform data into informed, meaningful decisions. In this editorial we highlight how training load monitoring has many potential applications and cannot be simply reduced to one metric and/or calculation. With experience across a variety of sporting backgrounds, this editorial details the challenges and contextual factors that must be considered when interpreting such data. It further demonstrates the need for those working with athletes to develop strong communication channels with all stakeholders in the decision-making process. Importantly, this editorial highlights the complexity associated with using training load for managing injury risk and explores the potential for framing training load with a performance and training progression mindset. Abstract Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load data is usually undertaken with a view to improve player performance and/or manage injury risk. To target these outcomes, practitioners attempt to optimise load at different stages throughout the training process, like adjusting individual sessions, planning day-to-day, periodising the season, and managing athletes with a long-term view. With greater investment in training load monitoring comes greater expectations, as stakeholders count on practitioners to transform data into informed, meaningful decisions. In this editorial we highlight how training load monitoring has many potential applications and cannot be simply reduced to one metric and/or calculation. With experience across a variety of sporting backgrounds, this editorial details the challenges and contextual factors that must be considered when interpreting such data. It further demonstrates the need for those working with athletes to develop strong communication channels with all stakeholders in the decision-making process. Importantly, this editorial highlights the complexity associated with using training load for managing injury risk and explores the potential for framing training load with a performance and training progression mindset. Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load data is usually undertaken with a view to improve player performance and/or manage injury risk. To target these outcomes, practitioners attempt to optimise load at different stages throughout the training process, like adjusting individual sessions, planning day-to-day, periodising the season, and managing athletes with a long-term view. With greater investment in training load monitoring comes greater expectations, as stakeholders count on practitioners to transform data into informed, meaningful decisions. In this editorial we highlight how training load monitoring has many potential applications and cannot be simply reduced to one metric and/or calculation. With experience across a variety of sporting backgrounds, this editorial details the challenges and contextual factors that must be considered when interpreting such data. It further demonstrates the need for those working with athletes to develop strong communication channels with all stakeholders in the decision-making process. Importantly, this editorial highlights the complexity associated with using training load for managing injury risk and explores the potential for framing training load with a performance and training progression mindset.Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load data is usually undertaken with a view to improve player performance and/or manage injury risk. To target these outcomes, practitioners attempt to optimise load at different stages throughout the training process, like adjusting individual sessions, planning day-to-day, periodising the season, and managing athletes with a long-term view. With greater investment in training load monitoring comes greater expectations, as stakeholders count on practitioners to transform data into informed, meaningful decisions. In this editorial we highlight how training load monitoring has many potential applications and cannot be simply reduced to one metric and/or calculation. With experience across a variety of sporting backgrounds, this editorial details the challenges and contextual factors that must be considered when interpreting such data. It further demonstrates the need for those working with athletes to develop strong communication channels with all stakeholders in the decision-making process. Importantly, this editorial highlights the complexity associated with using training load for managing injury risk and explores the potential for framing training load with a performance and training progression mindset.
Author	Clubb, Jo Leng, Edward Dalen-Lorentsen, Torstein Howells, Daniel Carmody, Sean Windt, Johann Vescovi, Jason D. Torres-Ronda, Lorena Posthumus, Michael West, Stephen W.
Author_xml	– sequence: 1 givenname: Stephen W. orcidid: 0000-0001-5800-7000 surname: West fullname: West, Stephen W. email: stephen.west@ucalgary.ca organization: Sport Injury Prevention Research Centre, Faculty of Kinesiology, University of Calgary, Calgary – sequence: 2 givenname: Jo surname: Clubb fullname: Clubb, Jo organization: Sports Performance, Buffalo Bills, Buffalo – sequence: 3 givenname: Lorena surname: Torres-Ronda fullname: Torres-Ronda, Lorena organization: Performance, Philadelphia 76ers, Philadelphia – sequence: 4 givenname: Daniel surname: Howells fullname: Howells, Daniel organization: Sports Medicine and Performance, Houston Astros, Houston – sequence: 5 givenname: Edward surname: Leng fullname: Leng, Edward organization: Football Medicine and Science Department, Manchester United FC, Manchester – sequence: 6 givenname: Jason D. orcidid: 0000-0003-2656-5109 surname: Vescovi fullname: Vescovi, Jason D. organization: Kinesiology and Physical Education, University of Toronto, Toronto – sequence: 7 givenname: Sean surname: Carmody fullname: Carmody, Sean organization: Medical Department, Queens Park Rangers FC, London, UK – sequence: 8 givenname: Michael surname: Posthumus fullname: Posthumus, Michael organization: Sports Science Institute of South Africa, Cape Town – sequence: 9 givenname: Torstein orcidid: 0000-0003-4062-7601 surname: Dalen-Lorentsen fullname: Dalen-Lorentsen, Torstein organization: Oslo Sports Trauma Research Center, Department of Sports Medicine, Norwegian School of Sports Sciences, Oslo – sequence: 10 givenname: Johann surname: Windt fullname: Windt, Johann organization: Department of Kinesiology, The University of British Columbia, Vancouver
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Snippet	Abstract Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load... Training load monitoring is a core aspect of modern-day sport science practice. Collecting, cleaning, analysing, interpreting, and disseminating load data is...
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SubjectTerms	Athletes Athletic Injuries - prevention & control Athletic Performance Communication Data Collection - methods Data Interpretation, Statistical Decision Making Humans Physical Conditioning, Human - methods Review Risk Management - methods Sports - physiology Stakeholder Participation Workload - statistics & numerical data
Title	More than a Metric: How Training Load is Used in Elite Sport for Athlete Management
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