Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/51942
Title: Training load prior to injury in professional Rugby League players: Analysing injury risk with machine learning
Contributor(s): Welch, Mitchell  (author)orcid ; Cummins, Cloe  (author)orcid ; Thornton, Heidi (author); King, Douglas  (author); Murphy, Aron  (author)
Publication Date: 2018
Open Access: Yes
Handle Link: https://hdl.handle.net/1959.11/51942
Open Access Link: https://commons.nmu.edu/isbs/vol36/iss1/59/Open Access Link
Abstract: This study explores the application of Global Positioning System tracking data from field training sessions and supervised machine learning algorithms for predicting injury risk of players across a single National Rugby League season. Previous work across a range of sporting codes has demonstrated associations between training loads and increased incidence of injury in professional athletes. Most of the work conducted has applied a reductionist approach, identifying training load characteristics as risk factors using generalised models to show population trends. This study demonstrates promising results by applying processing techniques and machine learning algorithms to analyse the injury risk associated with complex training load patterns. The accuracy of the algorithms are investigated along with the importance of training load predictors and data window sizes.
Publication Type: Conference Publication
Conference Details: ISBS 2018: 36th International Society of Biomechanics in Sport Conference, Auckland, New Zealand, 10th - 14th September, 2018
Source of Publication: International Symposium on Biomechanics in Sports, 36(1), p. 330-333
Publisher: International Society of Biomechanics in Sports (ISBS)
Place of Publication: Auckland, New Zealand
ISSN: 1999-4168
Fields of Research (FoR) 2020: 460102 Applications in health
460308 Pattern recognition
Socio-Economic Objective (SEO) 2020: 130602 Organised sports
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Appears in Collections:Conference Publication
School of Science and Technology

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