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

Gregory Everett,Ryan Beal,Tim Matthews, Timothy J. Norman,Sarvapali D. Ramchurn


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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 demonstrating the potential to reduce costs and improve player welfare in real-world soccer teams.
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