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Author Eager, Eric A., author.

Title Football analytics with Python & R : learning data science through the lens of sports / Eric A. Eager and Richard A. Erickson. [O'Reilly electronic resource]

Edition First edition.
Publication Info. Sebastopol, CA : O'Reilly Media, Inc., 2023.
©2023
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Description 1 online resource (xx, 327 pages) : illustrations (some color)
Note Includes index.
Summary "Baseball is not the only sport to use ""moneyball."" American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more".
Subject Football -- Data processing.
Python (Computer program language)
R (Computer program language)
Football -- Statistical methods.
Football -- Mathematical models.
Python (Langage de programmation)
R (Langage de programmation)
Added Author Erickson, Richard A., author.
Other Form: Print version: 1492099627 9781492099628 (OCoLC)1378824793
ISBN 9781492099598 electronic book
1492099597 electronic book
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