"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".
Book Synopsis
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
Dimensions (Overall): 9.1 Inches (H) x 6.8 Inches (W) x .9 Inches (D)
Weight: 1.23 Pounds
Suggested Age: 22 Years and Up
Sub-Genre: Databases
Genre: Computers + Internet
Number of Pages: 349
Publisher: O'Reilly Media
Theme: Data Mining
Format: Paperback
Author: Eric A Eager & Richard a Erickson
Language: English
Street Date: September 19, 2023
TCIN: 89135288
UPC: 9781492099628
Item Number (DPCI): 247-18-2148
Origin: Made in the USA or Imported
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Shipping details
Estimated ship dimensions: 0.9 inches length x 6.8 inches width x 9.1 inches height
Estimated ship weight: 1.23 pounds
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