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Noelthemexican Ballot for 2026 Week 7

Ballot Type: Computer

Submitted: Oct. 11, 2026, 6:24 p.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: I like this poll idea, but it does feel like sometimes the MOV has toooo much influence over the positions. I will wait till the season is over to make any changes, but I'd like to see these settle into a normal "unusual" level in the next week or two.

To give *some* transparency to what's happening in here, the top 3 MOV boosts in the top 25 are Notre Dame, Miami, and OREGON. I mentioned in a previous week that the FCS have a lot of influence, and this is a good example. The top 3 getting a MOV discount are Indiana, USC, and Wake Forest. Things like Alabama > Georgia are mostly MOV generated (Bama is about 60th percentile, Georgia at 50th.)

At some point, maybe I will come up with a way to differentiate wins and losses in the MOV adjustment, since I think that may be where some discrepancies arise. A win by 10 more than expected is worth the same as a lost by 10 less than expected. It is not immediately obvious to me how to do this, but maybe I'll come up with something for next year.

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