– 2020 UConn Sports Analytics Symposium (October 10)

The UConn Sports Analytics Symposium (UCSAS) focuses specifically on students (graduate, undergraduate, and high school) who are interested in sports analytics. Organized by the UConn Statistical Data Science Lab of the Department of Statistics UCSAS aims to: 1) showcase sports analytics to students at an accessible level; 2) train students in data analytics with application to sports data; and 3) foster collaboration between academic programs and the sports industry.

Four Keynote Presentations

• Thompson Bliss, Data Scientist, National Football League

Estimating the Impact of Travel, Rest, and Playing at Home in the National Football League

• Ron Yurko, PhD Candidate, Carnegie Mellon University

Going Deep: Models for Continuous-Time Within-Play Valuation of Game Outcomes in American Football with Tracking Data

• Stephanie Kovalchik, PhD, Senior Data Scientist at Zelus Analytic

Making the Intangible Tangible: Using Mixture Models for Estimating Latent Quantities in Sports

• ESPN Sports Analytics Team, ESPN

Redesigning NBA Basketball Power Index

Poster Session

A poster session is scheduled for 10:50–12:50. We invite submissions from all, especially students (high school, undergraduate, or graduate), with interesting works on any topics of sports analytics. The submission deadline is Friday, October 2, 2020.

A student poster award (possibly named after a sponsor), decided by the Student Poster Award Committee will be presented at the closing ceremony. The poster session also serves as a networking mixer. Grab a drink in front of your computer while enjoying the poster session and networking.

Training Workshops 

One-hour workshops are offered in two concurrent sessions of two hours (13:00- 15:00). Led by experienced graduate students from the Department of Statistics at UConn, they provide trainings from jumpstart to advanced sports analytic skills.

• Concurrent Session A (Introductory)

– 13:00–13:50: Introduction to R: Tuhin Sheikh

– 14:00–14:50: Introduction to Python: Jun (Bruce) Jin

• Concurrent Session B (Advanced)

– 13:00–13:50: Baseball Analytics with R: Dr. Zhe Wang

– 14:00–14:50: Data Visualization with R: Yiming Zhang


The symposium is open to anyone with an interest in sports analytics. The registration fee is minimal ($5) to get an accurate count for workshop planning and logistics.


We welcome and appreciate corporate and individual sponsorships of the 2020 UCSAS with any amount. Depending on the contribution level, sponsors will be recognized through customary channels. Please contact Dr. Jun Yan (jun.yan@uconn.edu) for details.

For further information, please visit our website. https://statds.org/events/ucsas2020/