Why would you ever bring your data science homework to a Siena basketball game? Because the basketball game is the homework.
Twenty years ago, Oakland A's executive Billy Beane began making player personnel decisions based on advanced analytics and otherwise neglected statistics. He used math and predictive modeling to overthrow a century's worth of conventional wisdom. And, as detailed in the book Moneyball (and movie of the same name), it worked. In the two decades since, professional teams have begun to incorporate data science into their sport. On Siena's campus, two professors are now incorporating sports into the data science.
Matt Bellis, Ph.D., associate professor of physics, and Eric Breimer, Ph.D., associate professor of computer science, both taught sections of Exploratory Data Analysis and Visualization this semester. It's the first sequence in the data science major and is made up mainly by underclassmen. And so to pique interest in data among underclassmen, the professors provided interesting data.
Sports analytics has grown into a major field within data science. And so Dr. Bellis and Dr. Breimer reached out to Vice President and Director of Athletics John D'Argenio and created a semester-long experience where students learn about real data collection and analysis in a real-world setting. The students attended Siena basketball games and cheered for the first half before getting to work in the second half.
"I chose to record turnovers to see if that correlated to the winner/loser of the game (more turnovers, more likely to lose). At the game, I used a notebook and recorded the data by hand. I feel being present at the game allowed me to retain my focus better and conduct better data collection. I hope, in some way or another, the women’s basketball team could use this data to help elevate their level of play and lead to greater success in seasons to come."
Margaret Frechette '24
The students all uploaded their data into a common spreadsheet, and made use of it for their final project. In fact, some students, as a result of this class, are now considering a career in sports analytics.
"As we blended together data science and sports, I came to realize that data is extremely useful in solving problems, visualizing something in a unique way, and is usually human-focused."
Christian Kolker '24
"To be able to keep track of a common statistic in basketball and then turn it into something meaningful for a class project was very interesting. Typically if someone were to keep stats for a basketball game, it would entail tracking several of the main events that occur in the game, so being able to focus on just one aspect of the game and have everything come together in the end hopefully made the data collection more accurate."
Mason Yattaw '22