Ball Tracking

Ball tracking in sports analytics focuses on automatically detecting and tracking the ball's trajectory in video footage, enabling quantitative analysis of player performance and team strategies. Current research emphasizes robust algorithms, often incorporating deep learning models like transformers and YOLO, to address challenges such as occlusions, varying lighting conditions, and fast-paced movements. These advancements are improving the accuracy and efficiency of data acquisition for sports analysis, providing valuable insights for coaches, scouts, and broadcasters, and facilitating the development of more sophisticated performance metrics. The availability of large, annotated datasets like SoccerNet is crucial for training and benchmarking these increasingly accurate tracking systems.