The Department of Computer Science offers multiple special topics courses each semester, but one course this term is especially unusual. COMP 152, Sports Analytics, is a new course that is being offered this spring. To the department’s knowledge, it is one of few sports analytics courses offered by a computer science department and geared primarily to computer science students. Developed and taught by Assistant Teaching Professor Megan Monroe, the course plots the intersections between sports analytics and computer science.
Monroe became interested in this area while studying as a PhD student at the University of Maryland-College Park. At the time, her work focused on the analysis and visualization of medical data. However, privacy hurdles meant that it could be difficult for researchers to access medical data. “On multiple occasions we would design and test features using more readily available sports data,” she says. Her work led her to Tufts, and Monroe was recently tapped to be the faculty liaison for the men’s basketball team. With this position came the opportunity to address in-house data challenges.
The inaugural course was well received, especially by student athletes. Students work with real data and real problems, such as identifying certain play types from tracking data, and determining the value of a draft prospect. Monroe has also used this opportunity to invite guest speakers such as CS alumnus Sean Harrington, A14, formerly of the New England Patriots, Matt Malone, Tufts men’s basketball coach, and Scott Goldman, creator of the Athletic Intelligence Quotient (AIQ), to discuss how computer science can intersect with the world of sports. This course is scheduled to be offered again next spring.
Monroe is no stranger to sports herself. Whenever possible, she can be found sailing, watching football, attending basketball games, and catching as many Tufts athletic events as she can manage. If you have any questions about this course, Monroe can be reached at firstname.lastname@example.org.