-
Books
-
Education
-
eBooks
-
Audio Books
-
Film & TV
-
Calendars, Diaries & Stationery
-
Giftshop
Browse through the navigation bar
-
Books
-
Education
-
eBooks
-
Audio Books
-
Film & TV
-
Calendars, Diaries & Stationery
-
Giftshop
Football Analytics with Python and R
Learning Data Science Through the Lens of Sports
by Eric A. Eager and others
RRP $125.50
$62.25
Save51%
RRP means 'Recommended Retail Price' and is the price our supplier recommends to retailers that the product be offered for sale. It does not necessarily mean the product has been offered or sold at the RRP by us or anyone else.
Spend another {0} to pay with
or 4 easy payments of $15.56 with
Paperback
Pub: 19/09/2023
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.… more
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
- ISBN:
- 9781492099628
- 9781492099628
- Category:
- Web programming
- Format:
- Paperback
- Publication Date:
- 19-09-2023
- Language:
- English
- Publisher:
- O'Reilly Media, Incorporated
- Country of origin:
- United States
- Dimensions:
- 233x177x19.13mm
- Weight:
- 0.62kg
This item is In Stock in our Sydney warehouse and should be sent from our warehouse within 1-2 working days.
Once sent we will send you a Shipping Notification which includes online tracking.
Please check the estimated delivery times below for your region, for after your order is despatched from our warehouse:
ACT Metro 2 working days
NSW Metro 2 working days
NSW Rural 2 - 3 working days
NSW Remote 2 - 5 working days
NT Metro 3 - 6 working days
NT Remote 4 - 10 working days
QLD Metro 2 - 4 working days
QLD Rural 2 - 5 working days
QLD Remote 2 - 7 working days
SA Metro 2 - 5 working days
SA Rural 3 - 6 working days
SA Remote 3 - 7 working days
TAS Metro 3 - 6 working days
TAS Rural 3 - 6 working days
VIC Metro 2 - 3 working days
VIC Rural 2 - 4 working days
VIC Remote 2 - 5 working days
WA Metro 3 - 6 working days
WA Rural 4 - 8 working days
WA Remote 4 - 12 working days
Express Post is available if ALL items in your Shopping Cart are listed as 'In Stock'.
Reviews
This product has no reviews yet.
Thanks for reviewing Football Analytics with Python and R. We will process your review. Accepted reviews will be posted within 3-7 business days.
You can find this item in:
You are buying a backorder title
×Be the first to know, stay up to date with what's trending and get staff picks in your inbox with our newsletter
Follow Us
Secured by:
Copyright 2025. All rights reserved.
Share This Book