A win forecasting model for the NFL
Note: This package is still under development. For now, you can play around with it via the command line.
The model will predict whether or not the offense team will win.
An output of
1 means the model is forecasting a win for the offense
0 means the model is forecast a loss (or tie) for the
$ pip install -r requirements.txt $ python >>> import numpy as np >>> from wincast.train import Trainer >>> >>> model = Trainer() >>> model.train() >>> # Now you can make predictions. Input features are as follows: >>> # (quarter, minute, second, points offense, points defense, >>> # t.o.l. offense, t.o.l. defense, down, yards to go, >>> # yards from own goal) >>> >>> # Here is an example of a call to predict, where the model >>> # forecasts a win for the team on offense: >>> model.predict([[4, 0, 5, 20, 7, 3, 2, 1, 2, 20]]) array([], dtype=int32) >>> # Get the probability of each class 0/1: >>> model.predict_proba(np.array([[4, 0, 5, 20, 7, 3, 2, 1, 2, 20]])) array([[ 0.00880867, 0.99119133]], dtype=float32)