The Strain of Success: A Predictive Model for Injury Risk Mitigation and Team Success in Soccer
<|reference_start|>The Strain of Success: A Predictive Model for Injury Risk Mitigation and Team Success in Soccer: 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.<|reference_end|>
@article{everett2024the,
    title={The Strain of Success: A Predictive Model for Injury Risk Mitigation and
  Team Success in Soccer},
    author={Gregory Everett, Ryan Beal, Tim Matthews, Timothy J. Norman, Sarvapali
  D. Ramchurn},
    journal={arXiv preprint arXiv:2402.04898},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.04898},
    primaryClass={cs.AI cs.LG}
}