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Found 3 papers, 3 papers with code
Explainable expected goal models for performance analysis in football analytics
To measure the probability of a shot being a goal by the expected goal, several features are used to train an expected goal model which is based on the event and tracking football data.
The Effect of Balancing Methods on Model Behavior in Imbalanced Classification Problems
To capture these changes, Explainable Artificial Intelligence tools are used to compare models trained on datasets before and after balancing.
Explainable artificial intelligence
imbalanced classification
Glocal Explanations of Expected Goal Models in Soccer
This paper introduces the glocal explanations (between local and global levels) of the expected goal models to enable performance analysis at the team and player levels by proposing the use of aggregated versions of the SHAP values and partial dependence profiles.
