The Heisman Calculator is a one-of-a-kind regression model that processes simulated Heisman votes. By using player and voter data from years past, we can identify statistical influencers that drive Heisman votes. For the third consecutive year, HeismanWatch.com foretells the Heisman Trophy outcome with greater accuracy than ESPN’s panel of experts and USATODAY’s Gannett Heisman [voter] survey.
Congratulations to Baker Mayfield, your 2017 Heisman Trophy winner.
There was no second guessing who was going to win the Heisman Trophy this year. The Heisman Calculator was clear; Baker Mayfield wins by +1,073 points. Turned out to be a near bullseye prediction; Mayfield ended up winning by a margin of 1,098.
The calculated marginal difference between placeholders, was a mere flush. Further validation the Heisman Calculator’s regression analysis is closely simulating the conditional expectation for the average value of the dependent variable when the independent variables are fixed. In other words, it’s getting easier and easier with each passing year to predict who wins the Heisman and by how many points/votes.
The Heisman Calculator has been able to list Heisman candidate results in perfect sequential order — #1 through #6 — flawlessly the two previous seasons. While the Heisman Calculator foretold #1, #4, #5, and #6 correctly in this year’s race, it incorrectly assumed the #2 (Bryce Love) and #3 (Lamar Jackson) candidate position. We have a few ideas of why this may have happened, we plan to add-in a few independent variables during the off-season to anticipate such scenarios. For example, a drop-in-points for Heisman Trophy incumbents (assuming the regression model supports such notion).
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