Sports Injury Prediction Model based on Machine Learning

Yudong Liang

Chapter 86 in Economic Management and Big Data Application:Proceedings of the 3rd International Conference, 2024, pp 969-981 from World Scientific Publishing Co. Pte. Ltd.

Abstract: In competitive sports, players are always at high risk for injuries. Sports injuries in rugby sports are directly related to the team’s game performance, especially when the player has an old sports injury or psychological stress. By considering the athlete as a dynamic system and quantifying the features associated with sports injuries, machine learning can be used to predict and assess the associated risks. In this paper, a simplified GRU is proposed to construct the mapping relationship between sports injury features and rugby game results. The comparison experiments with other machine learning models show that this model has better robustness in the prediction tasks of sports injuries and competition results of teenage rugby players.

Keywords: Big Data; Information Management; Economic; Data Applications; Blockchain; E-commerce (search for similar items in EconPapers)
JEL-codes: C63 C8 O14 (search for similar items in EconPapers)
Date: 2024
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