Football Analytics with Python & R: Learning Data Science Through the Lens of Sp

Description: Football Analytics with Python & R by Eric Eager, Richard Erickson Estimated delivery 3-12 business days Format Paperback Condition Brand New Description 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. This concise book provides a clear introduction to using statistical models to analyze football data. Publisher Description 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. Youll 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 Author Biography Eric A Eager is the Head of Research, Development and Innovation at Pro Football Focus (PFF), where he uses his training as an applied mathematician to produce solutions to quantitative problems for 32 National Football League clients, over 105 NCAA Football clients and numerous media clients and contacts. He also co-hosts the PFF Forecast Podcast, which can be found on PodcastOne and iTunes and is the most popular football analytics podcast in the world since 2018. Additionally, Eager supplies odds used by Steve Kornacki on Football Night in America, the Today Show, and other programs since 2020. He studied applied mathematics and mathematical biology at the University of Nebraska, where he wrote his PhD thesis on how stochasticity and nonlinear processes affect population dynamics. Eager spent his first six years thereafter as a professor at the University of Wisconsin - La Crosse, before transitioning to PFF full-time in 2018. He has since taught statistics and mathematics to over 10,000 students through college-level courses, the Wharton Sports Analytics and Business Initiatives Moneyball Academy, as well as an online course, "Linear Algebra for Data Science in R" with DataCamp. Eager has been interviewed by nfl.coms Ian Rappoport about Cowboys in-game decision making and The Washington Post for commentary about sports analytics. He joined the legendary Peter Kings podcast about fourth-down decisions and is a frequent guest on Cris Collinsworths podcast. Richard A Erickson helps people use mathematics and statistics to understand our world as well as make decisions with this data. He is a lifelong Green Bay Packer fan, and, like thousands of other cheeseheads, a team owner. He has taught over 25,000 students statistics through graduate-level courses, workshops, and his DataCamp courses on Generalized Linear Models in R and Hierarchical Models in R. He also uses Python on a regular basis to model scientific problems. Erickson received his PhD in Environmental Toxicology with an applied math minor from Texas Tech where he wrote his dissertation on modeling population-level effects of pesticides. He has modeled and analyzed diverse datasets including topics such as soil productivity for the USDA, impacts of climate change on disease dynamics, and improving rural healthcare. Erickson currently works as a research scientist and has over 70 peer-reviewed publications. Besides teaching Eric about R and Python, he also taught Eric to like cheese curds. Details ISBN 1492099627 ISBN-13 9781492099628 Title Football Analytics with Python & R Author Eric Eager, Richard Erickson Format Paperback Year 2023 Pages 349 Publisher OReilly Media GE_Item_ID:145026561; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. 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Price: 54.47 USD

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End Time: 2024-11-10T04:46:54.000Z

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Restocking Fee: No

Return shipping will be paid by: Buyer

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Item must be returned within: 30 Days

Refund will be given as: Money Back

ISBN-13: 9781492099628

Book Title: Football Analytics with Python & R

Number of Pages: 349 Pages

Publication Name: Football Analytics with Python and R : Learning Data Science Through the Lens of Sports

Language: English

Publisher: O'reilly Media, Incorporated

Subject: Mathematical & Statistical Software, Probability & Statistics / General, Data Visualization, Gambling / Sports, Football, Programming Languages / Python, Recreations & Games

Publication Year: 2023

Item Height: 0.8 in

Item Weight: 21.9 Oz

Type: Textbook

Subject Area: Mathematics, Computers, Sports & Recreation, Games & Activities

Item Length: 9.2 in

Author: Richard Erickson, Eric Eager

Item Width: 7 in

Format: Trade Paperback