Team Sport

Team sports analytics leverages data science and machine learning to analyze player and team performance, aiming to improve strategic decision-making and enhance overall game understanding. Current research focuses on developing sophisticated models, including those based on graph neural networks, transformers, and ensemble methods like QMIX, to predict player actions, identify latent roles within teams, and quantify abstract concepts like momentum. These advancements have significant implications for coaching strategies, player recruitment, and fan engagement, offering data-driven insights to optimize performance and enhance the overall sports experience.