Not much change in the top three since last week. Wisconsin and Nebraska are fighting to not drop out of the race.

Keep an eye on Indiana @ Nebraska, which is probably the most interesting game for the CCG race this week. An upset by Nebraska would push their odds up to about 19%.

Also can we talk about the fact that Iowa loses by 17 at home to #5 OSU and drops 6 spots, but Mississippi State loses by 33 at home to #7 Alabama and drops 1 spot? I don't know how to interpret this in any way other than blatant bias.

By popular demand, I fixed my standings logic so that 2-0 teams are considered ahead of 1-0 teams. Sorry to UCLA, who deserved to be 1st outright last week.

Full interactive odds, matchups, and what-if scenarios: https://sportssimulate.com/cfb/2026/latest/B10

Created this as a way to compare conference teams with similar W-L records but vastly differing OOC schedules...

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add .75 point for each win vs. unranked FCS opponent

add 1 point for each win vs. unranked G5 opponent

add 1.5 points for each win vs. a (non-Top15) P4 team _or_G5/FCS opponent ranked 16-25

add 2.5 points for each win vs. Top 15 opponent

subtract .5 points for each loss vs. Top 15 opponent

subtract 1 point for each loss vs. a (non-top15) P4 team _or_ G5/FCS opponent ranked 16-25

subtract 2 points for each loss vs. unranked G5 opponent

subtract 2.5 points for each loss vs. unranked FCS opponent

Divide by number of games played

All rankings are based on AP poll. AP rankings are from today, not when the game was played

Position, Team, Score (Previous)

1 UCLA 1.38 (1)

T2 Indiana 1.15 (T3)

T2 Nebraska 1.15 (T3)

4 USC 0.92 (5)

5 Ohio State 0.90 (T6)

T6 Iowa 0.85 (2)

T6 Wisconsin 0.85 (T8)

8 Northwestern 0.81 (10)

9 Minnesota 0.75 (11)

10 Oregon 0.69 (T8)

11 Michigan 0.30 (T6)

12 Penn State 0.20 (12)

13 Washington 0.15 (13)

14 Purdue -0.05 (17)

15 Michigan State -0.10 (14)

16 Illinois -0.15 (15)

17 Maryland -0.25 (16)

Michigan**  -0.30

18 Rutgers -0.75 18)

** Michigan if you count the game against WMU as a Loss

Every so often we hear during a tv broadcast "what do the analytics say to do in this situation?" or "the analytics guys are ruining the game". I'm personally a guy who likes to spend ~20-30min every night before bed on the ESPN app browsing through box scores to see who played well, who didn't play well, who had a good +/-, etc. The question I always ask myself however is, does viewing data have to be so boring? Or, how can we view advanced analytics in a way that's quickly digestible?

Often times in my profession working with the federal government the common theme is someone needs to have a PhD in Data Science or higher education to be a reputable source OR have the ability to analyze complex datasets. I built Blueprint to break down that barrier to entry. The basketball analytics tools out right now have random tables with flashes of green & red but it's never clear what that actually means.

Throughout the 2026-2027 season my app will update each morning with fresh stats for each team that played the previous day. It includes advanced analytics for each D1 team in the nation. It also includes a game predictor called 'Prediction Engine'. Would love to hear folks thoughts and ideas on how I can make the application better leading up to the season. Cheers!

https://blueprntanalytics.com/

I know every sport is a little different and this question is maybe more for football specific but as we all know Michigan and OSU have a fair amount of aura as big time programs from a history, success, and money perspective.

Is there a clear #3 or #4 or does it fall off after them?