Understanding home field advantage is a fascinating aspect of American football analytics, and using data to explore this phenomenon can reveal patterns and insights that enhance our understanding of the game. By combining exploratory data analysis techniques with real-world data, data scientists and football enthusiasts alike can uncover the factors that influence game outcomes.
In this hands-on code-along session, Paul Sabin, Lecturer in Statistics & Data Science, and Senior Sports Analytics Fellow at The Wharton School, will guide you through analyzing home field advantage in Super Bowl games. You’ll learn how data is used to study American football, apply data manipulation and visualization techniques, and assess the impact of home field advantage on game performance. Whether you’re a seasoned data scientist or a football fan with a passion for analytics, this session will provide a unique perspective on the intersection of sports and data.
Presenter Bio
Paul SabinLecturer in Statistics & Data Science, and Senior Sports Analytics Fellow at The Wharton School
Paul leads sports analytics research at The Wharton Sports Analytics & Business Initiative, and teaches data science at The Wharton School. He has built and led NFL Football analytics teams, and he has a sports analytics consultancy, Sabin Analytics. Previously, Paul was an Adjunct Professor in sports analytics at Virginia Tech, VP of Football analytics at SumerSports and a sports Data Scientist at ESPN.