.. image:: https://img.shields.io/pypi/v/statsnba-playbyplay.svg?maxAge=2592000 :target: https://pypi.python.org/pypi?name=statsnba-playbyplay&version=0.1.0&:action=display :alt: PyPi Version
.. image:: https://readthedocs.org/projects/statsnba-playbyplay/badge/?version=latest :target: http://statsnba-playbyplay.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status
NOTE: This project is still pretty much work in progress so it might introduce many breaking changes.
Introduction
_Use the data
_Benefits of this package
_Installation
_TODOs
_Basketball analytics using play-by-play data have been an shared interest for many people. However, the lack of processed play-by-play has prohibited such analysis by many.
This project is intended to provide parsing functionality for the
play-by-play data from http://stats.nba.com into more a comprehensive
format like that on
NBAStuffer <https://downloads.nbastuffer.com/nba-play-by-play-data-sets>
.
It is intended to accompany our research: Adversarial Synergy Graph Model for Predicting Game Outcomes in Human Basketball <http://www.somchaya.org/papers/2015_ALA_Liemhetcharat.pdf>
.
to prepare the data. If you are interested in more general statistics or
player information, you should definitely check out
py-Goldsberry <https://github.com/bradleyfay/py-Goldsberry>
__.
While there are still limitations with the current parsing strategy, it does not affect the tabulation of APM and other play-by-play based metrics.
If you just want to use the data that is processed with the package
without touching it, you can find a copy of the data
from here <https://www.doc.ic.ac.uk/~yl11416/statsnba-data/>
__. You
will find the gamelog and game files in JSON format.
You may inspect the JSON for the fields that are included in
them.
At the command line
.. code:: shell
$ pip install statsnba-playbyplay