Название: Football Analytics with Python & R: Learning Data Science Through the Lens of Sports (Final)Автор: Eric A. Eager, Richard A. Erickson
Издательство: O’Reilly Media, Inc.
Год: 2023
Страниц: 352
Язык: английский
Формат: pdf (true), epub (true)
Размер: 20.3 MB, 10.2 MB
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
Who This Book Is For:
Our book has two target audiences. First, we wrote the book for people who want to learn about football analytics by doing football analytics. We share examples and exercises that help you work through the problems you’d face. Throughout these examples and exercises, we show you how we think about football data and then how to analyze the data. Second, we wrote this book for people who want an introduction to data science but do not want to learn from classic datasets such as flower measurements from the 1930s or Titanic survivorship tables from 1912. Even if you will be applying data science to widgets at work, at least you can learn using an enjoyable topic like American football. We assume you have a high school background in math but are maybe a bit rusty (that is to say, you’ve completed a precalculus course). You might be a high school student or somebody who has not had a math course in 30 years. We’ll explain concepts as we go. We also focus on helping you see how football can supply fun math story problems. Our book will help you understand some of the basic skills used daily by football analysts. For fans, this will likely be enough data science skills. For the aspiring football analyst, we hope that our book serves as a springboard for your dreams and lifelong learning.
Who This Book Is Not For:
We wrote this book for beginners and have included appendixes for people with minimal-to-no prior programming experience. People who have extensive experience with statistics and programming in R or Python would likely not benefit from this book (other than by seeing the kind of introductory problems that exist in football analytics). Instead, they should move on to more advanced books.
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