Simulating association between training load and injury using the acute: chronic workload ratio and Bayesian methods in youth football.

Maughan, Patrick; Burgess, Katherine; Swinton, Paul

Abstract

Previous research has examined the relationship between relative workload and injury, where acute training load is expressed in relation to chronic training load using simple ratio scaling or non-linear models including the exponentially weighted moving average (EWMA). Research has demonstrated that higher relative workloads are associated with greater injury risk; however, statistical models generally report non-intuitive statistics such as odds ratios and as a result the practical consequences of increased player loading remain unclear. Here we combine training and injury data collected in youth football with a predictive simulation approach to model the number of injuries sustained across a range of seasonal workloads.

Citation

MAUGHAN, P., BURGESS, K.E. and SWINTON, P. 2017. Simulating association between training load and injury using the acute: chronic workload ratio and Bayesian methods in youth football. Presented at the 2017 UK Strength and Conditioning Association annual conference (UKSCA 2017), 4-6 August 2017, Leicester, UK.

• Presentation Conference Type: Poster
• Conference Name: 2017 UK Strength and Conditioning Association annual conference (UKSCA 2017)
• Start Date: Aug 4, 2017
• End Date: Aug 6, 2017
• Deposit Date: Feb 20, 2024
• Publicly Available Date: Feb 20, 2024
• Peer Reviewed: Peer Reviewed
• Keywords: Workload; Injury; Training load; Injury risks; Youth; Football; Players
• Public URL: https://rgu-repository.worktribe.com/output/2249562