Football Analytics with Python & R Learning Data Science Through the Lens of Sports
Football Analytics with Python & R Learning Data Science Through the Lens of Sports by Eric A. Eager, published by O’Reilly Media, Incorporated in 2023, offers a comprehensive introduction to the application of statistical models in analyzing football data. This 327-page book is written in English and serves as a resource for those interested in leveraging data analytics in the realm of American football, whether for professional analysis, fantasy leagues, or sports betting.
Readers will find practical insights into obtaining and visualizing NFL data using Python and R, along with methods for applying regression models to play-by-play data. The book includes case studies that guide users through various analytical techniques, such as classification problems and multivariate statistics, aimed at understanding player performance and enhancing decision-making in sports contexts. This edition is designed for anyone looking to deepen their knowledge of data science through the lens of football analytics.
Official synopsis Publisher
Baseball is not the only sport to use “moneyball.” American football teams, fantasy football players, fans, and gamblers are increasingly using data to gain an edge on the competition. Professional and college teams use data to help identify team needs and select players to fill those needs. Fantasy football players and fans use data to try to defeat their friends, while sports bettors use data in an attempt to defeat the sportsbooks.
In this concise book, Eric Eager and Richard Erickson provide a clear introduction to using statistical models to analyze football data using both Python and R. Whether your goal is to qualify for an entry-level football analyst position, dominate your fantasy football league, or simply learn R and Python with fun example cases, this book is your starting place.
Through case studies in both Python and R, you’ll learn to:
- Obtain NFL data from Python and R packages and web scraping
- Visualize and explore data
- Apply regression models to play-by-play data
- Extend regression models to classification problems in football
- Apply data science to sports betting with individual player props
- Understand player athletic attributes using multivariate statistics
Publisher
Topics
FAQ
What is “Football Analytics with Python & R Learning Data Science Through the Lens of Sports” about?
Who is the author of “Football Analytics with Python & R Learning Data Science Through the Lens of Sports”?
When was “Football Analytics with Python & R Learning Data Science Through the Lens of Sports” published?
What is the ISBN for “Football Analytics with Python & R Learning Data Science Through the Lens of Sports”?
What are the book details (language, pages, edition)?
