Retrieve Sports data in Python


Keywords
nfl, college, football, data, epa, statistics, web, scraping, cfb-data, college-basketball, college-football, data-science, espn, hockey, nba, nba-stats, nflfastr, nhl, nhl-api, python, sports, sports-analytics, sports-data, sports-stats, sportsdataverse, wnba, womens-basketball
License
MIT
Install
pip install sportsdataverse==0.0.24

Documentation

sportsdataverse-py

Lifecycle:experimental PyPIPyPI - Down
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See CHANGELOG.md for details.

The goal of sportsdataverse-py is to provide the community with a python package for working with sports data as a companion to the cfbfastR, hoopR, and wehoop R packages. Beyond data aggregation and tidying ease, one of the multitude of services that sportsdataverse-py provides is for benchmarking open-source expected points and win probability metrics for American Football.

Installation

sportsdataverse-py can be installed via pip:

pip install sportsdataverse

# with full dependencies
pip install sportsdataverse[all]

or from the repo (which may at times be more up to date):

git clone https://github.com/sportsdataverse/sportsdataverse-py
cd sportsdataverse-py
pip install -e .[all]

Our Authors

Citations

To cite the sportsdataverse-py Python package in publications, use:

BibTex Citation

@misc{gilani_sdvpy_2021,
  author = {Gilani, Saiem},
  title = {sportsdataverse-py: The SportsDataverse's Python Package for Sports Data.},
  url = {https://py.sportsdataverse.org},
  season = {2021}
}