Associations between refined athlete monitoring measures and individual match performance in professional Australian football

Ryan, S; Crowcroft, S; Kempton, T; Coutts, AJ

Associations between refined athlete monitoring measures and individual match performance in professional Australian football

Ryan, S Crowcroft, S Kempton, T Coutts, AJ

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Publisher:: Informa UK Limited
Publication Type:: Journal Article
Citation:: Science and Medicine in Football, 2020, pp. 1-9
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Ryan, S
dc.contributor.author	Crowcroft, S
dc.contributor.author	Kempton, T
dc.contributor.author	Coutts, AJ
dc.date.accessioned	2020-12-09T03:38:18Z
dc.date.available	2020-12-09T03:38:18Z
dc.date.issued	2020-01-01
dc.identifier.citation	Science and Medicine in Football, 2020, pp. 1-9
dc.identifier.issn	2473-3938
dc.identifier.issn	2473-4446
dc.identifier.uri	http://hdl.handle.net/10453/144582
dc.description.abstract	© 2020 Informa UK Limited, trading as Taylor & Francis Group. The purpose of this study was to assess relationships between measures of training load, training response and neuromuscular performance and changes in individual match performance in professional Australian football. Data were collected from 45 professional Australian footballers from one club during the 2019 competition season. External load was measured by GPS technology. Internal load was measured via session rate of perceived exertion (sRPE). Perceptual wellness was measured via pre-training questionnaires (1–5 Likert scale rating of soreness, sleep, fatigue, stress and motivation). Percentage of maximum speed was calculated relative to individual maximum recorded during preseason testing. Rolling derivative training load measures (7-day and 28-day) were calculated. Principal Component Analysis (PCA) identified eight uncorrelated components. PCA factor loadings were used to calculate summed variable covariates and single variables were chosen from components based on practicality and statistical contribution. Associations between covariates and performance were determined via linear Generalised Estimating Equations. Performance was assessed via Player Ratings from a commercial statistics company. Seven-day total distance, IMA event count and sRPE load showed significant positive relationships with performance (18–23% increase in performance z-score). No other covariates displayed significant associations with performance. Individual relative increases in training load within the 7-day period prior to a match may be beneficial for enhancing individual performance.
dc.language	en
dc.publisher	Informa UK Limited
dc.relation.ispartof	Science and Medicine in Football
dc.relation.isbasedon	10.1080/24733938.2020.1837924
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.title	Associations between refined athlete monitoring measures and individual match performance in professional Australian football
dc.type	Journal Article
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
pubs.organisational-group	/University of Technology Sydney/Strength - CHSP - Health Services and Practice
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2020-12-09T03:38:12Z
pubs.publication-status	Published

Abstract:

© 2020 Informa UK Limited, trading as Taylor & Francis Group. The purpose of this study was to assess relationships between measures of training load, training response and neuromuscular performance and changes in individual match performance in professional Australian football. Data were collected from 45 professional Australian footballers from one club during the 2019 competition season. External load was measured by GPS technology. Internal load was measured via session rate of perceived exertion (sRPE). Perceptual wellness was measured via pre-training questionnaires (1–5 Likert scale rating of soreness, sleep, fatigue, stress and motivation). Percentage of maximum speed was calculated relative to individual maximum recorded during preseason testing. Rolling derivative training load measures (7-day and 28-day) were calculated. Principal Component Analysis (PCA) identified eight uncorrelated components. PCA factor loadings were used to calculate summed variable covariates and single variables were chosen from components based on practicality and statistical contribution. Associations between covariates and performance were determined via linear Generalised Estimating Equations. Performance was assessed via Player Ratings from a commercial statistics company. Seven-day total distance, IMA event count and sRPE load showed significant positive relationships with performance (18–23% increase in performance z-score). No other covariates displayed significant associations with performance. Individual relative increases in training load within the 7-day period prior to a match may be beneficial for enhancing individual performance.

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http://hdl.handle.net/10453/144582