These days, if you want to work in sports analytics, you need to know how to code. There's really no way around it. And while that can be scary for someone who's never written a line of code before, it's not as daunting as it seems.
The reality is that there are a variety of excellent (often free!) resources for learning how to code. Some of them are very general, some are focused on a specific programming language, and some are focused on a specific use case, like sports analytics.
Below is a list of fantastic resources for learning how to code specifically for sports analytics. Because sports analytics is typically done in either R or Python, most of what you'll find below is focused on those two languages, however, many of the methods used in R and Python can be applied to other languages and use cases beyond sports.
This list is based on (read: "essentially copied directly from") a thread I posted on the Measurables Twitter account earlier this year. I'm duplicating it here simply because some people might find a blog post easier to navigate than a Twitter thread. I'll be keeping this list updated with any new resources I discover.
If you're unsure where to start, reach out! You can find my contact info here.
🏈 Ben Baldwin's guide to using nflscrapR, an R package for NFL data analysis
🏈 Thomas Mock's guide to improving your nflscrapR graphics
🏈 Nathan Braun's eBook "Learn to Code with Fantasy Football"
🏈 Parker Fleming's Introduction to College Football Data with R and cfbscrapR
🏈 Garret McClintock's Introduction to College Football Data Using Python
🏈 Michael Lopez's "R for NFL analysis"
⚾ Daniel Poston's Scikit-Learn (a Python package) tutorial with baseball data
⚾ Brice Russ's "How To Use R For Sports Stats, Part 1: The Absolute Basics" on FanGraphs
⚽ FC Python, a site that teaches Python through soccer data
⚽ FC RStats, a site that teaches R through soccer data
⚽ Devin Pleuler's Soccer Analytics Handbook
⚽ Tom Whelan's "Python for Fantasy Football"
🏒 Meghan Hall's "An Introduction to R With Hockey Data" on Hockey-Graphs
🏀 Ryan Davis's tutorials for processing NBA data in Python
🏀 Robert Clark's "Python Sports Analytics Made Simple"
🏑 Chris Fry's tutorial on graphing in R using field hockey data
Updated 9/24/20 with new resources
