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

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Gregory Everett, Dr. Ryan Beal, Dr. Tim Matthews, Prof. Sarvapali Ramchurn, Prof. Timothy Norman


Player injuries in soccer significantly impact team performance, club financial stability and player welfare, with the ‘Big Five’ European soccer leagues experiencing a staggering £513 million in injury-related costs during the 2021/22 season. In this paper, we present a novel forward-looking team selection model, framed as a Markov decision process and optimised with Monte Carlo tree search, that balances team performance with the risk of long-term player unavailability due to injury. We demonstrate that real-world teams could reduce the incidence of player injury by ~13% and wages inefficiently spent on injured players by ~11% using our data-driven team selection model.