Course Description

Sports analytics has become an essential tool across professional and collegiate athletics, shaping how teams evaluate players, develop strategy, and make organizational decisions. This course introduces students to analytics in a wide range of sports, including the NFL, Major League Baseball, the NBA/WNBA, and soccer. Students will explore how data informs individual and team performance evaluation, in-game strategy, and front office decision-making. The course blends traditional statistical approaches?such as correlation, regression, and other conventional methods?with more advanced techniques, including machine learning and generalized additive models (GAMs). By applying these methods to real-world sports data, students will gain hands-on experience in building, interpreting, and communicating analytical models that drive decisions on and off the field. Each week we will cover a specific sport beginning with a lecture on key topics/research questions for the sport followed by guided R work to conduct analyses and draw conclusions.

Course Reviews

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