by Elliott Scott, School of Informatics graduate student This report analyzes football game states using college sports data to predict win probabilities for various game situations. The dataset comprises 1.6 million rows of play-by-play data from Division I FBS football games, focusing on play types like punts, field goals, passes, and rushes. Each play type… Read more »
by Mark Ronad, School of Informatics graduate student This summer, I had the unique opportunity to dive deep into the dynamic and ever-evolving world of sports analytics, with a particular focus on Division One hockey and soccer teams. My project, aptly named “Performance Metrics Analysis for Division One Teams,” was an intensive exploration of performance… Read more »
by Anurag Reddeddy, School of Informatics graduate student This project was inspired by my exploration of various ice hockey platforms. While the leaderboards on these platforms were informative, I noticed a lack of detailed player shot maps, on-ice tendencies, and shot conversion rates. IceScout Pro was created to address this gap by presenting these insights… Read more »
by Kael Ecord, School of Informatics graduate student My project was titled “The Crumbs: Examining Offensive Rebound and Forced Turnover Success Rate”. The goal of my project was to use college basketball data from all games played by Big 12 Conference teams from 2018-19 through 2023-24 to create two new metrics. The first being offensive… Read more »
