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A Python implementation of NFL Win Probability (WP)

Project description

Build Status Documentation Status

Estimate Win Probability (WP) for plays in NFL games:

>>> import pandas as pd
>>> from nflwin.model import WPModel
>>> standard_model = WPModel.load_model()
>>> plays = pd.DataFrame({
... "quarter": ["Q1", "Q2", "Q4"],
... "seconds_elapsed": [0, 0, 600],
... "offense_team": ["NYJ", "NYJ", "NE"],
... "yardline": [-20, 20, 35],
... "down": [1, 3, 3],
... "yards_to_go": [10, 2, 10],
... "home_team": ["NYJ", "NYJ", "NYJ"],
... "away_team": ["NE", "NE", "NE"],
... "curr_home_score": [0, 0, 21],
... "curr_away_score": [0, 0, 10]
... })
>>> standard_model.predict_wp(plays)
array([ 0.58300397,  0.64321796,  0.18195466])

For full documentation, including information about methods and accuracy, click here.

License

MIT. See license file.

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Filename, size & hash SHA256 hash help File type Python version Upload date
nflwin-0.1.0.tar.gz (1.7 MB) Copy SHA256 hash SHA256 Source None Aug 7, 2016

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