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Benjamin Riela

Benjamin Riela standing on a University of Michigan soccer field

Michigan Sports Analytics Society (MSAS) featured Member: Benjamin Riela, co-president

Degree: Bachelor of Science in Information, ‘22, focusing on Information Analysis, minoring in Computer Science

Home: Westborough, MA

Goal of organization: The Michigan Sports Analytics Society is a student-led group working to develop interest in the field of sports analytics through discussion, student engagement and various project opportunities. 

Why I’m involved: I chose this organization because as a sophomore I was new to data analysis and wanted to find a way to build my skills outside of a classroom setting. I grew up a massive sports fan, so MSAS was the perfect club for blending my passions of both sports and data analytics. I also loved the culture and the people in the organization, so it was easy for me to come to and participate in meetings and projects. I’m very grateful for my time here with MSAS.

Membership: Anybody can join. All are welcome regardless of class year, undergraduate vs. graduate status, prior programming experience, or major. We have approximately 40 regularly attending members.

Noteworthy: MSAS is a place for anyone interested in sports analytics to interact, learn, and collaborate with people of similar interests in a meaningful setting that also allows for personal and professional growth. We feel it’s important that any student with sports analytics interest can come to the club and have a positive experience. 

A good reason to join: Statistics and data analysis are the future of sports, and also important skills for many future careers. At MSAS, club members can improve their resumes with skills attractive to sports organizations as well and in the general analytics industry. Many prior club members used their MSAS membership and project experience to work in analytics internships and full-time jobs, both inside and outside of the sports industry. 

Important events/activities: Our marquee event of the year is hosting the Michigan Sports Analytics Symposium. This is an event where club members and others within the Michigan sports analytics community can present their sports analytics research to fellow students and faculty, listen to guest speakers, and network. When possible, we also try to host a hackathon, have watch parties for big games, present guest speakers, and have course planning events. 

Meetings and activities: In the fall, our new members who do not have any prior coding experience go through a Python tutorial module sequence developed by the MSAS Leadership Board, which introduces members to Python and teaches basic data analysis with the Pandas package. For those who have prior programming and/or data analysis experience, we partner with outside organizations to work on projects using their data. For example, last year we partnered with a minor league hockey team, and this year we are working with Pro Football Focus (PFF), a popular football analytics website. 

Time commitment: We typically have one hour per week for club meetings. Research projects will require some more time commitment outside of the classroom, and that can vary depending on how much effort you wish to put into the project. 

Interesting project: The most interesting project I worked on was during my sophomore year. At the time, there was a big controversy surrounding Kawhi Leanord, one of the biggest stars in the NBA, over how much rest time he was getting during the regular season. I created a project that investigated this from an analytics perspective and compared his rest tendencies to other top players in the NBA. 

How to get involved: At the beginning of the year, you can find us at Festifall and sign up for the club there. During the middle of the school year, you can reach out to the primary contact on our Maize Pages page. New members can join the club at any time! 

More information: Reach out to the primary contact on our Maize Pages page

Statistics and analysis are the future of sports. More so than ever before, teams in every sport use data to make personnel decisions and devise winning strategies. Learn about how teams do analysis, find peers for collaboration on research projects and build your resume with skills attractive to franchises, agencies and other sports organizations.