Ball Scoring

Ball scoring analysis is shifting from solely focusing on players with the ball to comprehensively evaluating the contributions of off-ball movement. Current research utilizes advanced machine learning models, including transformer networks and multi-agent deep reinforcement learning, to predict pass outcomes, assess player actions in continuous spatiotemporal spaces, and quantify the impact of off-ball movement on scoring opportunities. These methods leverage player tracking data to create more nuanced performance metrics, offering valuable insights for tactical analysis, player evaluation, and team strategy optimization in sports like soccer and basketball. The resulting improved understanding of off-ball contributions promises to revolutionize player scouting and coaching strategies.