ISBN: 9781492099628 - football analytics with python & r: learning data science through the lens of sports (44 resultados)

Paperback. Condición: Good. 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.…

paperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Paperback. Condición: Good. 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.…

Condición: good. This book is in good condition. The cover has minor creases or bends. The binding is tight and pages are intact. Some pages may have writing or highlighting.

Condición: good. Good condition. A copy that has been read but remains in clean condition. All pages are intact and the cover is intact. The spine and cover may show signs of wear. Pages can include limited notes and highlighting, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation. If you're not satisfied with purchase please just return it.…

paperback. Condición: Very Good. Very good paperback, from a personal collection (NOT ex-library). Spine is uncreased, binding tight and sturdy. Minor corner/edge-wear. Interior is free of markings. Ships same or next day from Dinkytown, Minneapolis, Minnesota.

Condición: New.

Condición: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books.

Paperback. Condición: New. 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 datasetsDescribe football data with quantitative methodsCreate efficient workflows that offer reproducible resultsUse data science skills such as web scraping, manipulating data, and plotting dataImplement statistical models for football dataLink data summaries and model outputs to create reports or presentations using tools such as R Markdown and R ShinyAnd more.…

Paperback or Softback. Condición: New. Football Analytics with Python & R: Learning Data Science Through the Lens of Sports. Book.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: As New. Unread book in perfect condition.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Paperback. Condición: New. 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 datasetsDescribe football data with quantitative methodsCreate efficient workflows that offer reproducible resultsUse data science skills such as web scraping, manipulating data, and plotting dataImplement statistical models for football dataLink data summaries and model outputs to create reports or presentations using tools such as R Markdown and R ShinyAnd more.…

paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: New.

Condición: new.

Condición: New.

Paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 9-10 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: New. In English.

Condición: As New. Unread book in perfect condition.

Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.

Condición: New.

Paperback. Condición: Brand New. 300 pages. 9.19x7.00x0.90 inches. In Stock.

Condición: New. 2023. 1st Edition. paperback. . . . . .

Condición: New.

Paperback. Condición: New. 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 datasetsDescribe football data with quantitative methodsCreate efficient workflows that offer reproducible resultsUse data science skills such as web scraping, manipulating data, and plotting dataImplement statistical models for football dataLink data summaries and model outputs to create reports or presentations using tools such as R Markdown and R ShinyAnd more.…

Taschenbuch. Condición: Neu. Neuware -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 Englisch.…

Taschenbuch. Condición: Neu. Neuware -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 Englisch.…