Creation of predictive modelsΒΆ
Backtesting
The extracted training data (X_train, Y_train, O_train)
can be used
to backtest the performance of predictive models that are represented
by bettor objects. Calculating various backtesting statistics on
(X_train, Y_train, O_train)
is straightforward:
>>> from sportsbet.datasets import DummySoccerDataLoader
>>> from sportsbet.evaluation import ClassifierBettor
>>> from sklearn.dummy import DummyClassifier
>>> dataloader = DummySoccerDataLoader()
>>> X_train, Y_train, O_train = dataloader.extract_train_data(odds_type='interwetten')
>>> bettor = ClassifierBettor(DummyClassifier())
>>> bettor.backtest(X_train, Y_train, O_train)
ClassifierBettor(classifier=DummyClassifier())
>>> print(bettor.backtest_results_)
Training Start Training End Training Period Testing Start Testing End Testing Period Start Value End Value Total Return [%] ...
0 1997-05-04 1998-03-04 304 days 1999-03-04 1999-03-04 1 days 1000.0 1002.5 0.25 ...
...
Value bets
The extracted fixtures data can be used to predict the value bets:
>>> X_fix, Y_fix, O_fix = dataloader.extract_fixtures_data()
>>> bettor.bet(X_fix, O_fix)
interwetten__home_win__odds interwetten__draw__odds interwetten__away_win__odds
0 True False False
1 False False False