Enhancing Team Sports Strategy and Performance Using Machine Learning: A Case Study on Soccer

This study aims to improve performance in team sports, with a specific focus on football, using machine learning techniques. The research explores different machine learning methods, such as Random Forest, Decision Tree, and Support Vector Machine (SVM), by analyzing a dataset that includes player statistics, match results, and in-game events. The Random Forest model performed the best, with 88% accuracy in predicting match outcomes and identifying key performance indicators. The study highlights how machine learning can help coaches and analysts gain useful insights to enhance team performance and strategy.