Skip to main content

Package for scraping soccer data from a variety of sources.

Project description

This is sportstat, a Python package that I hope will give more people access to soccer data. Gone are the days of downloading spreadsheets one-by-one, copy-pasting, or entering data into spreadsheets by hand. I try to make sportstat as easy-to-use as possible so that anybody with a bit of Python experience can use it.

To install sportstat, run pip install sportstat from the command line.

Data can be scraped from the following sources:

  • FBRef
    • Match and seasonal data for players and teams
  • Understat
    • Match and seasonal data for players and teams
  • FiveThirtyEight
    • Several FiveThirtyEight metrics on a match level (SPI, win probabilities, xG, NSxG, and more)
  • ClubELO
    • ELO scores for teams on a specific date
  • Capology
    • Player salary data
  • Transfermarkt
    • Market value, transfer history, market value history, and more

For documentation, head over to the GitHub's wiki page

For usage examples, look at Examples.ipynb in the code directory or some of my example analyses in the analytics_examples folder.

I'd love to hear your feedback, bugs you find, or new features you want! You can reach me via email at osmour043@gmail.com or my Twitter handle is @owen_seymour.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sportstat-2.0.0.tar.gz (36.1 kB view hashes)

Uploaded source

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page