Metadata-Version: 1.0
Name: wincast
Version: 0.0.7
Summary: UNKNOWN
Home-page: https://github.com/kahnjw/wincast
Author: Jarrod Kahn
Author-email: jarrod.kahn+wincast@gmail.com
License: MIT
Description-Content-Type: UNKNOWN
Description: # wincast
        
        A Real Time Win Forecasting System for the NFL
        
        Note: This package is still under development.
        For now, you can play around with it via the
        command line.
        
        ## Usage
        
        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
        team. A `0` means the model is forecast a loss (or tie) for the
        offense team.
        
        
        ```sh
        $ 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([[1]], 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)
        ```
        
Platform: UNKNOWN
