Metadata-Version: 2.1
Name: sports-betting
Version: 0.2.1
Summary: Python sports betting toolbox.
Home-page: https://github.com/georgedouzas/sports-betting
Download-URL: https://github.com/AlgoWit/sports-betting
Maintainer: G. Douzas
Maintainer-email: gdouzas@icloud.com
License: MIT
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
License-File: LICENSE
Requires-Dist: pandas (>=1.0.0)
Requires-Dist: scikit-learn (>=1.0.0)
Requires-Dist: cloudpickle (>=2.0.0)
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Requires-Dist: rich (>=4.28)
Requires-Dist: vectorbt (>=0.22.0)
Requires-Dist: QuantStats (>=0.0.47)
Provides-Extra: docs
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Requires-Dist: sphinx-gallery ; extra == 'docs'
Requires-Dist: sphinx-rtd-theme ; extra == 'docs'
Requires-Dist: numpydoc ; extra == 'docs'
Requires-Dist: matplotlib ; extra == 'docs'
Requires-Dist: pandas ; extra == 'docs'
Provides-Extra: tests
Requires-Dist: pytest ; extra == 'tests'
Requires-Dist: pytest-cov ; extra == 'tests'

.. -*- mode: rst -*-

.. _scikit-learn: http://scikit-learn.org/stable/

.. _documentation: https://sports-betting.readthedocs.io/en/latest/

|CircleCI|_ |ReadTheDocs|_ |PythonVersion|_ |Pypi|_ |Conda|_

.. |CircleCI| image:: https://circleci.com/gh/georgedouzas/sports-betting/tree/master.svg?style=svg
.. _CircleCI: https://circleci.com/gh/georgedouzas/sports-betting/tree/master

.. |ReadTheDocs| image:: https://readthedocs.org/projects/sports-betting/badge/?version=latest
.. _ReadTheDocs: https://sports-betting.readthedocs.io/en/latest/?badge=latest

.. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/sports-betting.svg
.. _PythonVersion: https://img.shields.io/pypi/pyversions/sports-betting.svg

.. |Pypi| image:: https://badge.fury.io/py/sports-betting.svg
.. _Pypi: https://badge.fury.io/py/sports-betting

.. |Conda| image:: https://anaconda.org/gdouzas/sports-betting/badges/installer/conda.svg
.. _Conda: https://conda.anaconda.org/gdouzas

##############
sports-betting
##############

************
Introduction
************

The `sports-betting` package is a collection of tools that makes it easy to 
create machine learning models for sports betting and evaluate their performance. 
It is compatible with scikit-learn_.

*****
Usage
*****

The `sports-betting` package makes it easy to download 
training and fixtures sports betting data::

  >>> from sportsbet.datasets import SoccerDataLoader
  >>> dataloader = SoccerDataLoader(param_grid={'league': ['Italy'], 'year': [2020]})
  >>> X_train, Y_train, O_train = dataloader.extract_train_data(odds_type='market_maximum', drop_na_thres=1.0)
  >>> X_fix, Y_fix, O_fix = dataloader.extract_fixtures_data()

The historical data can be used to backtest the performance of a bettor model::

  >>> from sportsbet.evaluation import ClassifierBettor
  >>> from sklearn.dummy import DummyClassifier
  >>> bettor = ClassifierBettor(DummyClassifier())
  >>> bettor.backtest(X_train, Y_train, O_train)

We can get the value bets using fixtures data::

  >>> bettor.bet(X_fix, O_fix)

************
Installation
************

`sports-betting` is currently available on the PyPi's repositories and you can
install it via `pip`::

  pip install -U sports-betting

The package is released also in Anaconda Cloud platform::

  conda install -c gdouzas sports-betting

*************
Documentation
*************

Installation documentation, API documentation, and examples can be found in the
documentation_.


