The Statistics in Sports group engages in a combination of discussion and research regarding the development and incorporation of statistical methods in sports. We discuss papers about a wide variety of sports and diverse perspectives, addressing topics such as game outcome models, measurement and evaluation of player performance, tournament structure, analysis of rules and abjudication, within-game strategy, analysis of sports technologies, and player and team ranking methods.
Our members have presented their research in sports at conferences such as NESSIS, are finalists in hackathons, and consult for professional sports teams.
Check out our upcoming Carnegie Mellon Sports Analytics Conference!
R package to scrape soccer commentary and statistics from ESPN. https://github.com/ryurko/fcscrapR
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An R package to compute WAR for offensive players using nflscrapR. https://github.com/ryurko/nflWAR
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Developing R package with Max Horowitz and Sam Ventura that allows R users to utilize and analyze data from the National Football League (NFL) API. The functions in this package allow users to perform analysis at the play and game levels on single games and entire seasons. With open-source data, the development of reproducible advanced NFL metrics can occur at a more rapid pace and lead to growing the football analytics community. https://github.com/maksimhorowitz/nflscrapR
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