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Noelthemexican Ballot for 2026 Week 4

Ballot Type: Computer

Submitted: Sept. 21, 2026, 11:33 a.m.

Overall Rationale: Every year I've done some variation of the Colley Matrix (introducing bias to the famously "bias-free computer poll"), and this year is no different. Two years ago the teams were biased by FPI. This was probably good as far as accuracy goes, if you consider accuracy "closer to human polls." But in practice it was pretty much the Colley matrix with G5 teams down a lot of spots and P5 (especially SEC) teams up a lot of spots. Last year, I biased the teams by PFF rating. Specifically their "Overall" rating. This wasn't too bad, it boosted a few teams and dropped others. But the black box of PFF made it a little uninteresting to me.

This year the bias is going to come from excess score. I will run a regression where I use the rating(1) of the teams facing each other to predict the scoreline, so:

Home Team Score - Away Team Score = a+b(Home Team Rating - Away Team Rating)

Then I will take the residuals from this regression, and average by team. The averages will be converted to numbers between 0-1. And this number will be the bias number.

At this point there's mostly 1 observation per team so the results will be very funky. But as the season progresses, teams will get punished for winning close games that had no business being close, and rewarded for big wins in games that should have been competitive. This also applies on the other side too, teams will get rewarded for making games close they should have been blown out in, and so on. I guess in a way, you can consider this a "beat the spread bias" but the spread comes from me, not Vegas.

(1) The rating used in this calculation is the rating with the previous weeks bias, but the current weeks results.

Note: Hey look! Texas is #1! Still early but this ranking does highlight something strange. LSU is sort of rewarded more for losing close to Ole Miss than Ole Miss is rewarded for winning. [LSU is like 75th percentile for margin above expected but Ole Miss is like 25th]. I expect this is an artifact of the low sample size still, as it usually takes ~7-8 weeks for my older rankings to get close to the consensus.

FCS results are very important right now. One difference between my calculations and the actually Colley matrix is that they have a very structured way to separate FCS teams into groups, and I do no such thing. Which means that my model treats all FCS teams as the same. Therefore playing South Dakota State will have the same expected margin of victory as Bethune-Cookman where there is a large gap in quality. So, many teams getting boosts just happened to play worse FCS teams. I think this should shake out in the coming weeks.

Also my rankings adore the SEC.

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