Week 3 Ballot and Updated Projections

Submitted by The Mathlete on September 20th, 2010 at 11:48 AM

Right now the database appears to be overvaluing dominant wins against bad teams. This will change in the next two weeks as there is enough interplay to start doing better adjustments for team strength based on this season’s games.

There is obviously a lot of noise in here still but I want to keep the numbers clear of human intervention to see how they straighten out as the season goes on. As a reminder, the In Season rating is made up of one quarter of the rating from each game against a FBS opponent (or loss against a FCS opponent) and the remainder is pre season rating. A team with three FBS opponents is 75% in season, 25% pre season. A team like Indiana who has only played one FBS opponent to date, is 25% in season and 75% pre season. Michigan is 50/50 right now. Game success is adjusted for strength of opponent based on the pre-season PAN number.

Rank Team Conf Preseason PAN In Season PAN
1 Oregon PAC 10 10.1 20.6
2 Oklahoma St Big XII 5.0 17.9
3 Boise St WAC 11.2 17.5
4 Alabama SEC 8.7 17.3
5 Ohio St Big Ten 11.8 16.0
6 Florida SEC 13.5 15.9
7 TCU Mtn West 9.4 15.3
8 Utah Mtn West 5.6 15.1
9 Nebraska Big XII 5.0 14.1
10 Texas Big XII 16.4 13.6
11 Nevada WAC (0.3) 13.1
12 USC PAC 10 11.3 12.3
13 Stanford PAC 10 (1.1) 11.7
14 Texas Tech Big XII 7.0 11.3
15 W Virginia Big East 8.2 10.9
16 Oklahoma Big XII 12.4 10.8
17 Air Force Mtn West 0.4 10.7
18 S Carolina SEC 1.8 10.7
19 Arizona PAC 10 0.7 10.1
20 Auburn SEC 6.2 9.7
21 Kentucky SEC (1.3) 9.6
22 Arkansas SEC 5.2 8.9
23 Texas A&M Big XII (0.6) 7.7
24 Colorado Big XII (4.0) 7.6
25 Michigan Big Ten 5.6 7.5
  • Michigan holds on at #25. There change is a reflection of the movement of other teams. The UMass game had no factor in the final calculation although it would have if we had lost.
  • Oklahoma St’s high powered offense and multitude of weak opponents has them at a way too high #2 ranking.
  • A lot of conference hodge podge right now. No ACC teams, only W Virginia from the Big East. Michigan and Ohio St only two from the Big 10 after Iowa’s poor showing in Arizona. A lot of Big 12, SEC and PAC 10 in the ratings right now along with 5 teams from the future/past Mountain West conference.
    Michigan Projection
    Since Michigan scraped by UMass for the win, their is no knock on Michigan for their performance. The only adjustments are for changes to their remaining opponents. The projection is largely unchanged but still hovers around 8.5 wins.


Remaining Schedule

Bowling Green – rank 84, 97% chance of Michigan win

@ Indiana –67th, 67%

Michigan State –40th, 66%

Iowa –39th, 65%

@ Penn State –31st, 43%

Illinois –65th, 82%

@ Purdue –43rd, 52%

Wisconsin –26th, 59%

@ Ohio State –5th, 16%

Projected Big 10 finish

Ohio St

Penn St


Michigan St








The distinctions between Penn St and Purdue are very slight as the six teams between are projected between 4.2 and 5.1 wins. Right now it looks like a solid #1 (Ohio St), four bad teams (Illinois, NW, Indiana and Minnesota) with everyone else lumped in the middle. Michigan would look much better if not for their patsy free Big 10 schedule. Michigan only plays 2 of the bottom four while everyone else in the middle group plays at least 3 and Penn St and Purdue get all four.


U of M in TX

September 20th, 2010 at 12:03 PM ^

Is the biggest difference between our win percentage vs Purdue and Wisconsin home field advantage?


Your formula is based off of number of FBS schools played and is not similar to Sagarin's Bayesian calculations, correct?


September 20th, 2010 at 12:38 PM ^

How do you determine close? Should he rank FCS teams (a game played against DSU is not the same as a game against ASU or UMass)? What happens if a team goes up early and the 2nd or 3rd string allows for the game to even out?

Most FCS games are played more like scrimmages and he doesn't have enough data to distinguish between a closer than expected game and 3rd string players being 3rd string players. This process wouldn't even really work against FCS because there are so few data points that it becomes hard to rank FCS agasint FBS teams.


September 20th, 2010 at 8:46 PM ^

if all you did was make them the 121st best team, or even weighted it somewhat less, or used just the first half you'd be adding a better signal than nothing i would guess.  the typical scores against FCS teams are very telling.  as such, excluding the data point is making his ranking of michigan look considerably off.  having some kind of replacement level baseline would be very helpful too.