It's
now Connecticut Sports Analytics Symposium (CSAS)!
- Data/Time: April 11-12, 2025
- Location: Yale University, New Haven,
CT
Data Challenge Winners
- High school/undergraduate division
- Yonsei Blues (Juwon Lee, Jiyong Lee, and Yugyung Kim),
Yonsei University (Korea): Optimizing Batting Orders: Monte
Carlo Game Simulation Based on Batter Swing Clustering
- Graduate division
- Reese Mullen, Boston University: The Effect Of Injuries On
Bat Speed
Student Poster Award
Winners
- First Place: Eugene Han, Yale University: Leveraging
Alternative Data for Mixed Martial Arts Betting Markets
- Second Place: Jacqueline Wang, Yale University: Regularized
adjusted
plus-minus: pseudo-Bayesian player evaluation in hockey
and
performance improvements through design matrix
transformation
- Third Place: Abhi Nagireddygari, Bowdoin College: Extracting
& Analyzing Squash Match Patterns Using a Low-Cost Computer
Vision Framework
About CSAS
While there are many well established sports analytics
conferences, they are often not accessible to students due to
technical level, cost, or space limitations. Connecticut Sports
Analytics Symposium (CSAS) is a continuation of the UConn Sports
Analytics Symposium (UCSAS) which started in 2019 with a
broadened scope. It focuses on students at all levels, including
graduate, undergraduate, and high school, who are interested in
sports analytics or more generally, data science. CSAS aims
to:
- showcase sports analytics to students at an accessible
level;
- train students in data analytics with application to sports
data; and
- foster collaboration between academic programs and the
sports industry.