Skip to main content

sportsdataverse-py

Lifecycle:experimental PyPI Contributors Twitter
Follow

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

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

git clone https://github.com/saiemgilani/sportsdataverse-py
cd sportsdataverse-py
pip install -e .

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://sportsdataverse-py.sportsdataverse.org},
season = {2021}
}