sports-betting

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.. -- mode: rst --

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

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

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############## 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

Documentation

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