The Strain of Success: A Predictive Model for Injury Risk Mitigation and Team Success in Soccer

• URL: http://arxiv.org/abs/2402.04898v1
• Date: Wed, 7 Feb 2024 14:28:04 GMT
• Title: The Strain of Success: A Predictive Model for Injury Risk Mitigation and Team Success in Soccer
• Authors: Gregory Everett, Ryan Beal, Tim Matthews, Timothy J. Norman, Sarvapali D. Ramchurn
• Abstract summary: We present a novel sequential team selection model in soccer. We model the process of player injury and unavailability using player-specific information learned from real-world soccer data. Our model achieves similar season expected points to the benchmark whilst reducing first-team injuries by 13% and the money inefficiently spent on injured players by 11%.
• Score: 13.061659160183071
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we present a novel sequential team selection model in soccer. Specifically, we model the stochastic process of player injury and unavailability using player-specific information learned from real-world soccer data. Monte-Carlo Tree Search is used to select teams for games that optimise long-term team performance across a soccer season by reasoning over player injury probability. We validate our approach compared to benchmark solutions for the 2018/19 English Premier League season. Our model achieves similar season expected points to the benchmark whilst reducing first-team injuries by ~13% and the money inefficiently spent on injured players by ~11% - demonstrating the potential to reduce costs and improve player welfare in real-world soccer teams.

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