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 »
