We look at a really interesting topic with no easy answer: planning the microcycle in elite football.

Recent advances in techniques to explain machine learning models are opening up models that were previously considered black box models. This, in conjunction with the injection of sports domain knowledge and club context through robust data explorations, feature engineering and feature selection, combine to allow practitioners to see the reasoning behind the model outputs and enable them to incorporate into their decision-making.

In this post, we provide further insights into the ‘expected’ injury counts per week/month of hamstring strain, which is the most common injury encountered in elite football (soccer) (Ekstrand, 2021).

Injuries happen. We may put a lot of effort into different strategies trying to mitigate them, but unfortunately they still happen.