# sportsdataverse-py <a href='https://py.sportsdataverse.org'><img src='https://raw.githubusercontent.com/sportsdataverse/sportsdataverse-py/master/sdv-py-logo.png' align="right" width="20%" min-width="100px" /></a>
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See [CHANGELOG.md](https://py.sportsdataverse.org/CHANGELOG) for details.
The goal of [sportsdataverse-py](https://py.sportsdataverse.org) is to provide the community with a python package for working with sports data as a companion to the [cfbfastR](https://cfbfastR.sportsdataverse.org/), [hoopR](https://hoopR.sportsdataverse.org/), and [wehoop](https://wehoop.sportsdataverse.org/) R packages. Beyond data aggregation and tidying ease, one of the multitude of services that [sportsdataverse-py](https://py.sportsdataverse.org) provides is for benchmarking open-source expected points and win probability metrics for American Football.
## Installation
sportsdataverse-py can be installed via pip:
```bash
pip install sportsdataverse
# with full dependencies
pip install sportsdataverse[all]
```
or from the repo (which may at times be more up to date):
```bash
git clone https://github.com/sportsdataverse/sportsdataverse-py
cd sportsdataverse-py
pip install -e .[all]
```
# **Our Authors**
- [Saiem Gilani](https://twitter.com/saiemgilani)
<a href="https://twitter.com/saiemgilani" target="blank"><img src="https://img.shields.io/twitter/follow/saiemgilani?color=blue&label=%40saiemgilani&logo=twitter&style=for-the-badge" alt="@saiemgilani" /></a>
<a href="https://github.com/saiemgilani" target="blank"><img src="https://img.shields.io/github/followers/saiemgilani?color=eee&logo=Github&style=for-the-badge" alt="@saiemgilani" /></a>
## **Citations**
To cite the [**`sportsdataverse-py`**](https://py.sportsdataverse.org) Python package in publications, use:
BibTex Citation
```bibtex
@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}
}
```
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