Posts in Analytics
Weighted EPA Methodology & Performance

Summary

  • WEPA is a framework that weights EPA to improve its predictive power

  • The goal of WEPA is to use publicly available play-by-play data to create an open source model that is free, reproducible, and more predictive than proprietary alternatives

  • The 2018 WEPA proof-of-concept suffered from overfitting and used forward looking data to train, resulting in an unreliable model

  • This post addresses these issues while improving the model through an expanded dataset and feature group

  • The new WEPA model is substantially more reliable and predicts future point margin better than current proprietary alternatives

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An Initial Exploration of Home Field Advantage in the NFL
  • HFA trends are volatile at the individual season level, but long term trends show a steady decline. From 2000 to 2019, trailing 10 season HFA declined from 2.9 points to 2.2 points

  • Individual teams may experience periods of elevated HFA, but elevated HFA is not predictive of future elevated HFA across any window of games

  • Variation in HFA for individual games does not appear to be significantly influenced by the mileage traveled by the away team. Away travel correlates with divisional games, which exhibit a much stronger relationship with HFA

  • Modeled HFA is 2.95 non-divisional games and 1.59 for divisional games

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What's the Best NFL Game Grade?
  • Final scores are  reasonable predictors of future performance, but game grades like DVOA and WEPA are measurably better

  • Individually, WEPA was the best game grade tested, beating both DVOA and PFF in descriptive and predictive power

  • Even when a game grade isn’t as predictive of future performance as other game grades, incorporating it into a blended game grade yields a metric that is more predictive than any individual game grade

  • Depending on implementation, a game grade that blends Point Differential, WEPA, and PFF tends to perform best

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