Sports Predictive Analytics

Watching professional sports provides excitement and has entertainment value. Recent advancements in the field of Predictive Analytics models have allowed more accuracy in computing the probabilities of win/loss prospects of these sporting events. Moreover, algorithms have been developed that can analyze the performance of individual players. The goal of predictive analytics in sports is not only to predict the outcome of a game but also to evaluate team and player performance, which can result in building increasingly competitive teams. This course will survey the literature and explore various Predictive Analytics models designed for sporting events. Starting by computing simple statistics of previously played games, students will use correlation to detect statistical relationships between different metrics of the game. Topics will include Sabermetrics methods, Massey’s Method, Colley’s Method, and Elo System. In the end, this course will cover how to create a presentation for the GM of a team to describe performance, and suggest changes for team optimization strategies.