Review: Football Analytics with Python & R

This article was first published on python - Stringfest Analytics , and kindly contributed to python-bloggers. (You can report issue about the content on this page here)
Want to share your content on python-bloggers? click here.

Look what touched down in my mailbox today… 🏈

_Football Analytics with Python & R_ by Eric Eager and Richard Erickson. I had the pleasure to be a tech reviewer for this book and recommend it to anyone interested in, as the subtitle suggests, learning data science through the lens of sports.

What I particularly love about this title is that it stands squarely on the three pillars of the famous “Data Science Venn Diagram:”

1. Math & stats — dive inside the mechanics of linear regression, principal components analysis and other fundamental data science techniques

2. Hacking skills — get up and running with Python and R from scratch and learn how to gather and clean your data from a variety of football analytics data sources.

3. Substantive expertise — learn how to tell a story with the data and weave it into the greater context of what you’re looking to explore (Just like they did in _Moneyball_ 🧢)!

Congrats again to the authors for quarterbacking this title; I’m sure it will score lots of points… and I’ll stop now 😁

The post Review: Football Analytics with Python & R first appeared on Stringfest Analytics.

To leave a comment for the author, please follow the link and comment on their blog: python - Stringfest Analytics .

Want to share your content on python-bloggers? click here.