Skip to main content

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for nflwin, version 1.0.1
Filename, size File type Python version Upload date Hashes
Filename, size nflwin-1.0.1.tar.gz (17.0 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page