The 7th Connecticut Sports Analytics Symposium (CSAS)
April 10–11, 2026, University of Connecticut
The 7th CSAS continues with its unique focus on students at various educational levels-from graduate and undergraduate to pre-college-who have an interest in sports analytics or data science more broadly. Organized by the Connecticut Statistical Data Science Lab, CSAS aims to: 1) showcase sports analytics at an accessible level; 2) provide hands-on training in data analytics using sports data; 3) foster collaboration between academia and the sports industry.
# Confirmed Keynote Speakers
+ Mark Glickman, Senior Lecturer on Statistics, Department of Statistics, Harvard University
+ Dean Oliver, Sports Analytics Pioneer, Project Specialist, ESPN Sports Statistics
# Data Challenge: Curling
Partnered with the US Olympic and Paralympic Committee, the data challenge engages students in a real-world sports analytics problem focused on mixed-doubles curling. Teams analyze stone-position data from recent international competitions to examine power-play strategy, including when to deploy it, how to execute it, and how to defend against it. More than 70 teams registered. Final submissions are due on January 15, 2026, and entries are judged on statistical rigor, clarity of insight, and effective communication.
# Poster Session
We invite poster submissions from all participants, especially students at the pre-college, undergraduate, and graduate levels, presenting work on any topic in sports analytics. Limited travel support for students is available through NSF funding subject to NSF guidelines. A student poster award will be presented at the closing ceremony. The poster session will also serve as a networking mixer. Abstracts are to be submitted by 11:59 PM on Monday, March 16, 2026.
# Training Workshops
The Workshops feature hands-on training workshops at introductory, intermediate, and advanced levels, with a strong emphasis on student-led instruction and peer learning. Many workshops are designed and delivered by students, providing practical training grounded in real data and reproducible workflows. Introductory offerings include Introduction to R, Introduction to Python, and Interactive Visu- alization. Intermediate workshops cover Project Management with Git, Basketball Analytics, and Football Analytics. Advanced topics include sports data applications, player tracking–based performance metrics, and causal analysis of defensive strategies in Major League Baseball.
# Participation
We welcome participation from across the sports analytics community. Those interested in contributing are encouraged to reach out:
+ Gregory J. Matthews (
gmatthews1@luc.edu) for presenting;
+ James Hyman (
jahyman@connecticutsun.com) for serving as a judge for the Data Challenge before the conference or poster competition on site.
# Sponsorship/Partnership
Sponsorship and partnership opportunities are available at multiple contribu- tion levels. Sponsors will be recognized through customary channels, including naming opportunities for selected sub-events. Please contact Dr. Jun Yan (
jun.yan@uconn.edu) for further details.
Jun Yan on behalf of the Organizing Committee
Sean Ahmed, Principal Quantitative Analyst, Detroit Tigers
James Hyman, Basketball and Business Intelligence Analyst, Connecticut Sun
Brian Macdonald (co-chair), Senior Lecturer and Research Scientist, Department of Statistics and Data Science, Yale University
Gregory J. Matthews, Associate Professor, Statistics, Loyola University Chicago
Lauren Poe, Sports Analytics Engineer, ESPN
Jun Yan (co-chair), Professor, Department of Statistics, University of Connecticut