This course delves into the relevant statistics from various sports, including football, soccer, basketball, and hockey. Students will explore how to calculate and interpret common statistics, connecting these metrics to the performance of both past and present athletes. The course also covers the theory, development, and application of sports analytics. Students will learn how to manipulate and wrangle data, utilize data analytics toolkits such as R, and apply predictive modeling and clustering techniques to identify patterns in structured and unstructured data respectively. By the end of the course, students will understand how analytics can be applied to in-game strategy, player performance evaluation, team management, sports operations, and other critical areas within the sports industry. Any introductory statistics will be a good prerequisite for the course. Offered annually in the spring semester.
| Distribution Area | Prerequisites | Credits |
|---|---|---|
| Any introductory statistics will be a good prerequisite for the course. | 1 course |