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This presentation explores leveraging machine learning (ML) to forecast football outcomes. It delves into ML classification and regression models, applying algorithms like KNN and logistic regression to tackle dynamic and unpredictable factors in football. By comparing ML and classical methods and analyzing features such as expected goals (xG), the study introduces a dual-model system for predicting categorical and continuous outcomes. The results highlight algorithm performance, challenges,...