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Football Analytics with Python and R : Learning Data Science Through the Lens of Sports by Eric A. Eager and Richard A. Erickson (2023, Trade Paperback)
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Football Analytics with Python & R: Learning Data Science Through the Lens of Sports (Paperback or Softback). ISBN: 9781492099628. Condition Guide. Item Availability.
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About this product
Product Identifiers
PublisherO'reilly Media, Incorporated
ISBN-101492099627
ISBN-139781492099628
eBay Product ID (ePID)23060633791
Product Key Features
Number of Pages349 Pages
Publication NameFootball Analytics with Python and R : Learning Data Science Through the Lens of Sports
LanguageEnglish
Publication Year2023
SubjectMathematical & Statistical Software, Probability & Statistics / General, Data Visualization, Gambling / Sports, Football, Programming Languages / Python, Recreations & Games
TypeTextbook
AuthorEric A. Eager, Richard A. Erickson
Subject AreaMathematics, Computers, Sports & Recreation, Games & Activities
FormatTrade Paperback
Dimensions
Item Height0.8 in
Item Weight21.9 Oz
Item Length9.2 in
Item Width7 in
Additional Product Features
LCCN2023-279858
IllustratedYes
SynopsisBaseball 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
LC Classification NumberGV959.E34 2023
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