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Around SBN: Penn State Class of 2012: Reasons for Excitement on Defense

New and Improved Ratings, Etc.

The Ratings

Well, they're definitely new and when you start out really low then you're probably going to improve. So I've got that going for me.


Which is nice.

The previous version of the ratings had a couple of issues that bothered me. The first was that the composite ratings would occasionally have a team ranked higher or lower than they were in either the NMV or PMV ratings set. That kind of result was illogical and was frankly the result of what I consider to be some ad hoc input previously incorporated into the ratings. The ad hoc aspect of the ratings calculations has been removed in this new version and all inputs are either logically defensible or driven by the data.

The second issue was that no aspect of the ratings was either intended or suitable for predictive analysis of future matchups. My original intent when getting into generating computer ratings was actually to produce them for Texas High School Football. And with the high school football ratings I intended only to rank teams based on their performance over the course of the season. Consistent sources for accurate score information was too tedious to track down every year, so I no longer publish those, but I did become more interested in Sagarin's predictor model and the previously published Massey predictions.

So the new version of the ratings will contain both the "Season Rankings" section which I consider to be the better one to look at to rank teams based on the season performance while the "Power Ratings" section is intended to predict future outcomes based on that past performance. The Season Rankings version is still based on the previous idea of assigning a game outcome value that substitutes as the ratings' guess for the probability that the winning team will win a rematch. The PMV ratings are calculated first where that probability can vary from just above 50% to just shy of 100%. The NMV ratings are calculated next using the PMV win correlation as the game outcome value for the winner of each contest. The actual margin of victory from each game is not considered. The final rating is a composite of these two ratings.

The Power Ratings is the new aspect and determining how to calculate this part of the ratings was based on discussions on various boards. In more than one place recently the Big 12 offense versus SEC defense debate has been raging. In support of the Big 12 teams' defensive abilities, several fans have compared the number of points and yards allowed by Texas and others compared to those teams' average outputs. The first time I saw this kind of analysis it was on the old GoBig12 board and the late PhxHorn was using them to forecast the Cotton Bowl against Mississippi State. The only shortcoming then, of course, was that doing the calculations by hand made it too time-consuming, just short of impossible, to account for a teams' opponents and their opponents' opponents. What the Power Ratings do is essentially the same analysis but they use the score of every game played and iterate as many times as necessary until the ratings converge to an acceptable level.

So, here are the All Teams ratings and the D-1A only ratings. The left half of each output is the Season Rankings and the right half is the Power Ratings. In order to predict the margin of an upcoming game, simply subtract a team's "Pow" number from their opponent's and account for the overall homefield advantage as necessary. In order to predict the score of a specific team in the contest, start with their "Off" rating and subtract the opponent's "Def" rating. Add half the homefield advantage to the home team's score and subtract half from the visiting team's score. All of these calculations have to be done from the "All Teams" page.

The classification-specific pages have normalized values for all of these power rating figures. This will allow me to compare units across seasons, e.g., offer an answer to the question of which offense was the greatest of all time. I will be calculating historical seasons as time permits. Something to keep in mind is that the Offense and Defense ratings are based on point totals. Therefore dominating special teams units can help both units or just one in the case of a dominant kick returner, for example. Let me know if you see any errors or have any questions.

Quick Title Belt Update

Texas won the belt on Saturday.

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Conference Ratings (numbers are average for all teams in league):

Conf Rating Power Offense Defense Big 12 94.67 90.64 61.48 29.16 Big 10 92.96 86.76 54.88 31.88 SEC 92.61 85.80 53.78 32.02 ACC 92.19 82.97 52.47 30.51 Pac-10 91.13 84.59 56.23 28.36 Big East 89.38 78.80 51.28 27.52 MWC 89.04 76.60 50.70 25.90 Ind 86.14 73.05 47.25 25.80 WAC 85.67 68.03 47.14 20.88 MAC 84.60 71.19 48.37 22.82 C-USA 83.86 71.94 51.76 20.18 Sun Belt 81.19 66.32 46.81 19.51

by Huckleberry on Oct 27, 2025 7:13 PM CDT reply actions  

if you will allow me to misinterpret your data, i find it most interesting that, while sec defenses are 10% better than big 12 and the big 12’s offenses are 14% better than those of the sec, our conference’s offenses are nearly twice as good as their defenses, numerically.

but seriously, big 10 comes in above sec, on average? but big 10 games are unwatchable. does that affect your numbers?

by DrkBgrk on Oct 27, 2025 10:15 PM CDT reply actions  

Well, unlike the season rankings the power ratings aren’t really meant to be interpreted percentage-wise. And comparing the offense numbers to the defense won’t work. The defense number is basically the points that a defense will hold you under your expected offensive output. Obviously then the defense numbers will be less than the offense numbers.

The way to look at it is that the average Big 12 offense is 7.7 points better than the average SEC offense while the average SEC defense is 2.86 points better than the average Big 12 defense.

As for overall ratings, taking the mean rating for a conference’s members isn’t really the best way to look at it, but it’s all I could do quickly this evening.

by Huckleberry on Oct 27, 2025 10:32 PM CDT reply actions  

far too dignified a response, thanks for it and putting together the ratings. we going to see some predictions soon so we can judge your success?

by DrkBgrk on Oct 27, 2025 11:03 PM CDT reply actions  

So am I right that the predicted score for the Tech game would be a 38-28 win for Texas?

by FightTexasFight on Oct 28, 2025 8:39 AM CDT reply actions  

That’s correct. It’s closer to a 9.5 point margin, but with rounding that is the prediction.

by Huckleberry on Oct 28, 2025 9:29 AM CDT reply actions  

A couple of tables below of imbalanced football teams. By subtracting a team’s Defensive rating from their Offensive rating, we can approximate how many points their offense would score against their defense. This doesn’t mean they have best offense if their number is high, of course, just that their offense is relatively much better than their defense. And vice versa.

Tulsa50.61 Rice48.08 Oregon45.05 Oklahoma44.47 Missouri41.80 Houston40.74 Nevada40.33 UTEP40.27 Louisiana-Lafayette38.06 Kansas St.37.83 Wake Forest5.96 Temple8.96 South Carolina10.25 Auburn11.24 Vanderbilt11.84 Army11.95 San Jose St.12.60 Arizona St.13.28 Tennessee13.53 Ohio St.13.72

by Huckleberry on Oct 28, 2025 11:32 AM CDT reply actions  

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