If you're looking for fun data sets for learning, for teaching, maybe a conference talk, or even if you're just really into them, sports offers up a continuous stream of rich data that many people can relate to. Yet, accessing that data can be tricky. Sometimes it's locked away in obscure file formats. Other times, the data exists but without a clear API to access it. On this episode, we talk about PySport - something of an awesome list of a wide range of libraries (mostly but not all Python) for accessing a wide variety of sports data from the NFL, NBA, F1, and more. We have Koen Vossen, maintainer of PySport to talk through some of the more popular projects.

Links from the show

Koen on Twitter: @mr_le_fox
PySport on Twitter: @PySportOrg
Calling R from Python: medium.com
DuckDB: duckdb.org
PySport Playground: playground.pysport.org
NFLVerse: github.com
NBA Stats: nba.com
Sports Databases: opensource.pysport.org
Data sets: opensource.pysport.org
Visualizations: opensource.pysport.org
I/O: opensource.pysport.org
Models: opensource.pysport.org
Scrapers/APIs: opensource.pysport.org
Fast F1: docs.fastf1.dev
Fast F1 graphics: docs.fastf1.dev
Pysport Intro: pysport.org

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