AI for Youth Sports: Democratizing Professional Sport Analytics Tools

Sports analytics is about observing, understanding and describing the game in an intelligent manner. In practice, this requires a fully automated, robust end-to-end pipeline: from visual input, to player and group activities, to player and team evaluation, to planning. Despite major advancements in computer vision and machine learning, sports analytics is still in its infancy and relies heavily on simpler descriptive statistics. In addition, current sports analytics solutions are limited to top leagues and are not widely available for downmarket leagues and youth sports. In this talk, we explain how we have developed scalable and robust computer vision solutions to democratize sport analytics and offer pro-league-level insights to leagues with modest resources, including youth leagues. We highlight key challenges such as the requirement for low cost, low latency processing and the need for robustness despite variations in venues, and how we solved some of those problems.