04/09/2020
Can machine learning predict injury in elite-level youth football players? To a certain extent .. yes it can. It was a great pleasure to have contributed to this study. Elite-level youth football is known to entail a high injury risk. This is often attributed to early specialization, high training loads, and high training and game intensities. To specifically target injury risk mitigation strategies in young footballers, knowledge of both modifiable and non-modifiable risk factors is crucial. In practice, however, it is often not feasible for clubs and coaches to perform thorough player screening for injury risk management purposes. There is simply limited time and little financial means. Therefore, there is a strong interest to assess injury risk based on field-specific and relatively easy screening tests, such as motor performance tests already taken by many clubs to monitor player development. Therefore, the aim of this study was to use a machine learning approach to evaluate the risk of injury in youth elite-level football players, based on such available data. The first aim was to use preseason test results to assess the accuracy of a machine learning model predicting injury during the season. The second aim was to apply a similar model to correctly classify different types of injuries, namely overuse and acute injuries. %U
Elite-level youth football is known to entail a high injury risk. This is often attributed to early specialization, high training loads, and high training and game intensities. To specifically target injury risk mitigation strategies in young footballers, knowledge of both modifiable and non-modifia
