The NFL has given Carnegie Mellon University researchers access to official film and on-field data to develop new technologies that can enhance the way coaches, players and fans annotate, analyze and understand games.
The project teams Chenyan Xiong, a self-described football nerd and an associate professor in the Kenneth C. Griffin School of Computer Science’s Language Technologies Institute, with Ron Yurko, the director of the Carnegie Mellon Sports Analytics Center (CMSAC), to build an artificial intelligence model that can learn football.
“Gaining access to the NFL’s official film footage is an incredible opportunity,” said Yurko, assistant teaching professor in the Dietrich College of Humanities and Social Science’s Department of Statistics & Data Science. “The fact that we were able to put together this research proposal and show how creating new AI-enabled technologies could be extremely beneficial to the league and its teams is exciting. We are the only institution that’s conducting research with this data.”
Yurko has worked with the NFL before, integrating research into the NFL IQ AI Chatbot during the 2026 NFL draft that allowed users to ask questions and get answers from the model. Xiong’s CMU research focuses on creating AI technologies that use huge amounts of data from different sources to understand and solve problems in areas like healthcare. He wanted to make an AI tool for the NFL because of his love for the game.
From Xiong’s office, where he proudly displays footballs signed by Ben Roethlisberger, he and Yurko started planning how they could combine their expertise into research and technology that could benefit the NFL and its fans. They approached the NFL and were accepted into the NFL Forward Initiative, a program that allows entrepreneurs and researchers to pitch technological solutions for use in competition, training and player development, and in growing the sport’s reach.
“We want to see whether we can train foundation models on the data to learn the intricacies of football intelligence,” Xiong said. “In this case, football intelligence is comparable to the knowledge of the average fan. The model can understand plays, can potentially make play predictions or, once it sees a play, can also identify if the play has been run before, perhaps by another team.”
