Sports Injury is Self-exciting: Modelling AFL Injuries Using Hawkes Processes

Abstract Sports injuries can be considered as self-exciting, in that they can be linked to a previous injury or can be a new independently acquired injury. Disentangling which injuries are connected, either directly or indirectly, remains a persistent challenge, but is important for sport and athlete management. In this paper, we consider injuries as a type of Hawkes Process and view estimation as a branching process. We also propose a computationally efficient latent variable formulation in the context of clustering subsequent sporting injuries among professional Australian Football League (AFL) players in a small sample context. The results underscore the broader advantages of utilising such a point process for accurately modelling and estimating the occurrence of rare events. Our approaches are then assessed to demonstrate better estimation performance and compared to determine their suitability for injury forecasting.

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Publication Details

Journal
SN Computer Science
Published
2025-04-17
DOI
https://doi.org/10.1007/s42979-025-03939-w
Primary Topic
Meta-analysis and systematic reviews
Type
article
Field-Weighted Citation Impact
0.00

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article

Sports Injury is Self-exciting: Modelling AFL Injuries Using Hawkes Processes

Kerrie Lee Mengersen, Paul Pao‐Yen Wu, Liam A. Toohey, John D. Worrall
SN Computer Science
Meta-analysis and systematic reviews
article

Sports Injury is Self-exciting: Modelling AFL Injuries Using Hawkes Processes

Kerrie Lee Mengersen, Paul Pao‐Yen Wu, Liam A. Toohey, John D. Worrall
article en

Abstract

Abstract Sports injuries can be considered as self-exciting, in that they can be linked to a previous injury or can be a new independently acquired injury. Disentangling which injuries are connected, either directly or indirectly, remains a persistent challenge, but is important for sport and athlete management. In this paper, we consider injuries as a type of Hawkes Process and view estimation as a branching process. We also propose a computationally efficient latent variable formulation in the context of clustering subsequent sporting injuries among professional Australian Football League (AFL) players in a small sample context. The results underscore the broader advantages of utilising such a point process for accurately modelling and estimating the occurrence of rare events. Our approaches are then assessed to demonstrate better estimation performance and compared to determine their suitability for injury forecasting.

SN Computer ScienceVol. 6(5)
Australian Institute of Health and Welfare (AU), Queensland University of Technology (AU), University of Canberra (AU)
Queensland University of Technology
Openalex Percentile: Top 92%
Meta-analysis and systematic reviews
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