On October 24–25, three Rice Sport Analytics students—Elisabeth Millington ’26, Lou Zhou ’27, and Dante Maurice ’26—presented their research at the Carnegie Mellon Sports Analytics Conference in Pittsburgh. The conference brought together students, researchers, and industry professionals to share developments in sports data modeling and performance analysis.
"These conferences give our students opportunities not just to share their work, but also to network with professionals in the field and learn from others in their field," said Clark Haptonstall, Chair of Rice's Department of Sport Management.
Millington, Zhou, and Maurice each showcased projects developed through coursework, summer research, and independent study.
Millington earned second place in the conference’s Reproducible Research Competition (Student Track) for her project, titled “A comps-based approach for interpreting tree-based predictions with an application to the NFL Draft." The project introduces a method for interpreting machine learning models by generating player similarity scores to explain how and why predictions occur. She applied her approach to the 2025 NFL quarterback draft class to produce interpretable projections.
“One of my biggest takeaways from the conference was the importance of connecting quantitative analysis with practical, interpretable insights that coaches, scouts, and executives can use,” Millington said.
Zhou presented two projects. His oral presentation analyzed NFL player tracking data to predict the likely target of a pass based on positioning and game context, developed during a summer research program at CMU. His poster presentation highlighted a Python package designed to support esports analytics by providing clean and transparent access to match and performance data.
“It was really cool,” Zhou said. “I was able to get feedback from leaders in the field and reconnect with old friends from other schools.”
He added that presenting helped him refine his work and think about new directions for future projects.
Maurice presented research on MLB hitters’ swing behavior, using bat-tracking data and Gaussian Mixture Models to examine whether hitters alter their swing mechanics in two-strike situations. The findings suggest that hitters tend to react to pitch context, rather than deliberately changing swing profiles.
“It was an incredible experience presenting my research to a room full of peers and professionals,” Maurice said. “Preparing for CMSAC strengthened both my technical and communication skills, and attending helped me see where I want to grow next in the field.”
Their time at CMSAC offered a chance to share their work and learn from others in the field, providing perspective they’ll carry forward as they continue developing their projects at Rice. They encouraged other students interested in sport analytics to seek out similar opportunities to present, connect, and learn.
Sergio Rojas, a senior from Houston, Texas, is double-majoring in Business with a concentration in Finance and Sport Management with a concentration in Leadership.