Conference Attendance: a Double Shot of Reality

Attention all college presidents, AD's, and wussy coaches - I've got a deal for you.

Us fans will acknowledge the fact that in order to be prudent stewards of your college or university, sometimes you have to do what's fiscally sound (aka, schedule cupcakes in order to make money, get an easy win, and go to a bowl game). Sometimes.

But if we accept that, you have to acknowledge the fact that a lot of us fans think that despite the money, this is a cowardly and bullshit path that leads to uncompetitive games that none of us want to watch. (You can't ignore the fact that when playing non-BCS opponents your attendance drops an average of -14%, and when playing I-AA teams it drops an average of -22%.)

Deal?

Non-conf games (2000-2008)	Home Games	Total Attendance	Average Attendance	Drop from Average	% Drop
ACC vs BCS	65	3,623,533	55,747
ACC vs non-BCS	88	4,512,727	51,281	-4,465	-8.0%
ACC vs I-AA	53	2,673,821	50,449	-5,297	-9.5%
Big10 vs BCS	62	4,562,836	73,594
Big10 vs non-BCS	130	9,299,744	71,536	-2,057	-2.8%
Big10 vs I-AA	36	2,034,731	56,520	-17,073	-23.2%
Big12 vs BCS	41	2,580,134	62,930
Big12 vs non-BCS	142	8,197,073	57,726	-5,204	-8.3%
Big12 vs I-AA	66	3,184,454	48,249	-14,680	-23.3%
BigEast vs BCS	53	2,614,131	49,323
BigEast vs non-BCS	90	3,580,581	39,784	-9,538	-19.3%
BigEast vs I-AA	41	1,573,839	38,386	-10,936	-22.2%
CUSA vs BCS	61	2,254,231	36,955
CUSA vs non-BCS	53	1,477,181	27,871	-9,083	-24.6%
CUSA vs I-AA	49	1,339,694	27,341	-9,613	-26.0%
MAC vs BCS	38	930,994	24,500
MAC vs non-BCS	32	594,874	18,590	-5,910	-24.1%
MAC vs I-AA	82	1,511,589	18,434	-6,065	-24.8%
MtnWest vs BCS	47	1,929,690	41,057
MtnWest vs non-BCS	60	2,183,753	36,396	-4,661	-11.4%
MtnWest vs I-AA	37	1,163,088	31,435	-9,622	-23.4%
Pac10 vs BCS	49	3,056,303	62,374
Pac10 vs non-BCS	98	4,843,257	49,421	-12,952	-20.8%
Pac10 vs I-AA	26	1,169,157	44,968	-17,405	-27.9%
SEC vs BCS	52	4,124,898	79,325
SEC vs non-BCS	169	12,529,826	74,141	-5,183	-6.5%
SEC vs I-AA	57	3,730,076	65,440	-13,885	-17.5%
SunBelt vs BCS	12	247,774	20,648
SunBelt vs non-BCS	40	738,810	18,470	-2,177	-10.5%
SunBelt vs I-AA	42	709,942	16,903	-3,744	-18.1%
WAC vs BCS	36	1,234,032	34,279
WAC vs non-BCS	59	1,670,569	28,315	-5,963	-17.4%
WAC vs I-AA	48	1,222,606	25,471	-8,807	-25.7%

Speaking of attendance, we seem to have found actual proof of a diving line between the haves and the have-nots. It's at about 36,000. (Note to the Mountain West fans - I know you want to be taken more seriously as a conference and be a part of the BCS, but in addition to winning more games against BCS competition, it wouldn't hurt if you'd start buying more tickets. Your 2008 average attendance was your lowest this decade...)

I'm just sayin'.

A Study of Losses in the AP & Coaches Polls

What type of loss do the voters hate? What teams and conferences do they love? Last year it was non-conference schedules - this year it's the polls.

We’re going to be asking (and answering) two main questions here: first,
are there any constants in how far teams drop in the polls after a loss?
And second,
have the polls shown any biases for or against teams or conferences?

the Setup

As usual, this study only deals with the BCS era, the past 11 seasons from 1998-2008. All in all, there were 183 weeks of AP rankings and 184 weeks of Coaches rankings. (Yes, the coaches put out one more poll than the writers – I deal with that anomaly in the Methodology section.) At averages of 67 AP voters and 60 coaches per week, multiplied by the standard 325 votes per voter (25 “votes” for #1, 24 for #2, 23 for #3, etc.), that’s over 4 million AP votes and over 3½ million Coaches votes in the last 11 years. (Don’t worry, we’re not going to be dealing with all of them. Well, not really.) Dthose 183 and 184 weeks, there were 3,516 games played by AP Top 25 teams & 3,498 games played by Coaches Top 25 teams. Ranked AP teams lost 1,033 games and ranked Coaches teams lost 1,049 games, winning percentages of just over 70% for each. Not bad.

After dropping some games from each (again, check the Methodology section), we’re left with 1,028 AP games and 1,041 Coaches games to analyze and gather data from. So here’s our starting point:

0 - Base Numbers	AP games	avg. drop	Co games	avg. drop
Total Number of Top 25 Losses 1998-2008	1,028	-7.9	1,041	-7.7

In all those 1,028 AP losses, the average drop in the polls was -7.9 spots, while the average of the 1,041 CO games was -7.7 spots. The way we’re going to make sense of all these games is to divide these games into groups based on possibly relevant factors. Factors such as…

Factor #1: Upset - was the loss an upset? (upset = beaten by a lower-ranked team)

1 - Upset?	AP	avg drop	Co	avg drop
Number of Top 25 Upsets (U)	656	-9.1	671	-8.6
Number of Top 25 non-Upsets (noU)	372	-5.7	370	-5.9

Relevant? Yes, considerably. About 64% of the losses in the Top 25 were upsets, and teams that were upset dropped around -3 spots more in the polls than teams which were beaten by a higher ranked team. Let’s look at some others to get the feel of them.

Factor #2: Margin of Loss - does it matter how much you lose by?

2 - Margin of Loss	AP	avg drop	Co	avg drop
3 points or less	241	-7.0	244	-6.8
4 to 8 points	252	-7.2	258	-7.0
9 to 16 points	212	-7.5	215	-7.6
more than 17 points	323	-9.3	324	-8.9

Relevant? Maybe, at least in the Coaches poll. There's progression, but not much difference between a -1 point loss and a -15 point loss in the AP...

Factor #3: Month - does it matter when you lose?

3 - Month	AP	avg drop	Co	avg drop
Sept (+Aug)	252	-10.6	250	-10.3
Oct	317	-8.2	327	-7.9
Nov (+Dec)	329	-6.6	330	-6.6
Bowl	130	-4.9	134	-4.9

Relevant? Yup. Definitely for both polls.

Factor #4: Location - does it matter where you lose?

4 - Location	AP	avg drop	Co	avg drop
Home (vs)	325	-8.5	322	-8.1
Neutral (v)	187	-5.4	192	-5.4
Away (@)	516	-8.3	527	-8.2

Relevant? Doesn't look like it. Even though there were significantly more away game losses by Top 25 teams, they dropped the same average number of spots as home game losses. (But what's up with the neutral site games? 3 whole spots less?)

Factors #3 + #4: Month + Location

Month	Loc.	AP	avg drop	Co	avg drop
Sept	vs	91	-11.0	88	-10.3
Oct	vs	124	-8.2	128	-7.9
Nov	vs	110	-6.9	106	-6.6
Sept	v	13	-12.1	12	-11.6
Oct	v	14	-6.4	16	-7.1
Nov	v	30	-4.4	30	-4.4
Bowl	v	130	-4.9	134	-4.9
Sept	@	148	-10.3	150	-10.1
Oct	@	179	-8.4	183	-8.0
Nov	@	189	-6.8	194	-6.8

Ah, that's it. The vast majority of neutral site games are conference championships or bowl games, played really late in the season. A September neutral site game actually dropped teams an average of between -1 and -2 spots more than a September home or away loss. So this confirms that Month is relevant and Location isn't.

So that’s how this whole study works. Here are the other categories I looked at and whether or not they’re relevant:

the Results

Location - does it matter where you lose? No
Number of Losses – does it matter how many losses you have? No
Overtime – does it matter if the game was tied in regulation? No
Conf. Game – does it matter if the loss was a conference or non-conference game? No
Initial Rank – does it matter how highly you were ranked to start the season? No
Previous Year’s Wins – does it matter how good you were the year before? No
Previous 3 Year’s Wins – does it matter how good you were the last three years? No
Difference in Rank – does it matter how evenly you're matched with your opponent? Not really. (Yes, sort of, when it's a neutral site game, but no when it's a home or away game.)

Upset - does it matter if you were beat by a higher-ranked team? Yes
Margin of Loss (MoL) - does it matter how much you lost by? Yes
Month - does it matter when you lost? Yes
BCS Conf – does it matter if you’re in a BCS conference? Yes
Opp. BCS Conf – does it matter if the team you lost to is in a BCS conference? Yes
Rank – does it matter how highly you’re ranked? Yes
Opp. Rank – does it matter how highly your opponent was ranked? Yes
Opp. Previous Year’s Wins – does it matter how good your opponent was the year before? Yes
Opp. Previous 3 Year’s Wins – does it matter how good your opponent was the last three years? Yes
# of Weeks at Ranking – does it matter how long you’ve been ranked that high? Yes

(If you’re interested in all of these categories' breakdowns, click here. If you can think of any other statistically measurable category that you think might be relevant and correlate, just let me know and I’ll check it out.)

So now that we have a better idea of which categories are relevant, let’s go deeper and gauge just how much of a correlation there is for each one. We can do this by combining categories, just like we did with the earlier Month+Location. When we do so we see that:

In the AP Poll, the three most relevant factors are Upset, Month, and Rank.
In the Coaches Poll, the three most relevant are Upset, Month, and MoL (Margin of Loss).

So to answer our first question, yes, there are some patterns that we can follow to gauge (very generally) what a factors are involved in how far a team drops after a loss. We can say with certainty that, all other things being equal, getting upset will drop you more than losing to a higher ranked team; losing in September will drop you more than losing a bowl game; losing as the #23 team will drop you more than losing as the #3 team, etc. But here’s the thing – there is no magic formula that you can apply that will tell you exactly how many spots a team is going to drop after a loss. Sometimes a Top 5 teams that is upset by a TD in September drops -4 spots, sometimes they drop -11 spots. Sometimes a team ranked just outside the Top 10 that loses to a higher-ranked team in October by two TD’s drops -3 spots, sometimes they drop -10. That’s just the nature of a subjective ranking system.

Despite this, we can examine those above relevant factors to create a base of averages that we can use to compare and contrast how the polls see each team and answer our second question. Here’s the averages that we’ll be using:

pink=highest drop avg - blue=lowest drop avg AP Poll_____________Coaches Poll

Upset Month Rank AP avg drop noU Bowl #01-05 10 -2.3 noU Bowl #06-10 12 -3.3 noU Bowl #11-15 11 -3.6 noU Bowl #16-20 16 -4.5 noU Bowl #21-25 13 -4.5 noU Nov #01-05 4 -2.8 noU Nov #06-10 11 -4.0 noU Nov #11-15 28 -4.8 noU Nov #16-20 30 -5.1 noU Nov #21-25 39 -5.9 noU Oct #01-05 4 -4.3 noU Oct #06-10 22 -4.7 noU Oct #11-15 28 -6.5 noU Oct #16-20 33 -5.0 noU Oct #21-25 30 -7.5 noU Sept #01-05 4 -7.5 noU Sept #06-10 8 -5.5 noU Sept #11-15 16 -5.6 noU Sept #16-20 23 -8.0 noU Sept #21-25 30 -8.9 U Bowl #01-05 13 -3.8 U Bowl #06-10 14 -4.6 U Bowl #11-15 17 -5.5 U Bowl #16-20 13 -7.3 U Bowl #21-25 11 -9.0 U Nov #01-05 53 -5.3 U Nov #06-10 43 -7.1 U Nov #11-15 36 -7.6 U Nov #16-20 45 -7.7 U Nov #21-25 40 -9.9 U Oct #01-05 35 -6.7 U Oct #06-10 36 -7.8 U Oct #11-15 36 -9.1 U Oct #16-20 40 -10.1 U Oct #21-25 53 -12.6 U Sept #01-05 24 -7.6 U Sept #06-10 37 -10.0 U Sept #11-15 32 -11.4 U Sept #16-20 40 -12.4 U Sept #21-25 38 -17.0

Upset Month MoL Co avg drop noU Bowl -3 or less 15 -3.1 noU Bowl -4 to -8 12 -3.2 noU Bowl -9 to -16 15 -3.5 noU Bowl -17 or more 22 -5.6 noU Nov -3 or less 13 -3.8 noU Nov -4 to -8 20 -2.8 noU Nov -9 to -16 25 -5.2 noU Nov -17 or more 52 -6.7 noU Oct -3 or less 18 -3.3 noU Oct -4 to -8 26 -4.7 noU Oct -9 to -16 30 -6.4 noU Oct -17 or more 42 -8.4 noU Sept -3 or less 14 -3.6 noU Sept -4 to -8 17 -5.8 noU Sept -9 to -16 13 -9.3 noU Sept -17 or more 36 -9.9 U Bowl -3 or less 18 -5.0 U Bowl -4 to -8 14 -5.1 U Bowl -9 to -16 20 -5.1 U Bowl -17 or more 18 -7.3 U Nov -3 or less 54 -6.6 U Nov -4 to -8 64 -6.8 U Nov -9 to -16 46 -7.6 U Nov -17 or more 56 -7.8 U Oct -3 or less 65 -8.6 U Oct -4 to -8 58 -8.2 U Oct -9 to -16 36 -8.8 U Oct -17 or more 52 -9.8 U Sept -3 or less 47 -9.3 U Sept -4 to -8 47 -11.0 U Sept -9 to -16 30 -12.1 U Sept -17 or more 46 -13.5

the Payoff

So how do we use those averages? By examining every game and comparing how many spots a team dropped to the average for that combination of factors. For instance, if you click on each of the school names below, you'll be taken to their school page where you'll see something like this:

Iowa State Losses while in the Top 25, 1998-2008
date	AP rk	CO rk	vs/@	oAP rk	oCO rk	oConf	Opponent	MoL	AP drop	avg	diff	CO drop	avg	diff
10/19/02	#09	#13	@	#02	#02	Big12	Oklahoma	3-49	-8	-04.7	-03.3	-5	-08.4	03.4
10/26/02	#17	#18	@	#07	#07	Big12	Texas	10-21	-5	-05.0	00.0	-5	-06.4	01.4
11/09/02	#21	#22	@	#12	#12	Big12	Kansas St	7-58	-9	-05.9	-03.1	-8	-06.7	-01.3
10/01/05	#23	#26	@	NR	#42	Big12	Nebraska	20-27	-9	-12.6	03.6	-	-	-
11/26/05	#26	#25	@	NR	NR	Big12	Kansas	21-24	-	-	-	-8	-06.6	-01.4

Iowa State's first loss happened in October, they were ranked #6-10 (AP), but it wasn't an upset = the average for all teams with those factors was a -4.7 spot drop. The Cyclones dropped -8 spots, which was not only significantly more but was one of the biggest drops for a team with that combination of factors (signified by the red background). Game #4 counts for the AP since the Cyclones were ranked #23, but not for the Coaches since they were out of the Top 25 - vice versa for game #5.

Combining all those games, we get this:

Team	AP L's	+/-	AP Avg	leasts	mosts	Co L's	+/-	Co Avg	leasts	mosts	AP-CO diff	All L's	All +/-	Tot. Avg
Iowa St	4	-2.7	-0.7	0	1	4	2.1	0.5	0	0	4.8	8	-0.7	-0.1

the +/- is the sum of the "diff" columns from above (differences between the average drops and the amount the team actually dropped). The higher it is, the more the polls like that team, the lower (negative) it is, the more the polls dislike them. (Why? who knows - that a study for another time. And somebody else.) Leasts & mosts are the times when a team's dropped spots were the least or most of all losses by teams with that combination of factors. AP-CO diff is the difference between the AP and Coaches polls - the higher the number, the more the Coaches liked the team, the lower (negative) the number, the more the AP liked the team.

The most important numbers are the colored averages. Those represent the average number of poll spots more than or less than the average that each team dropped PER GAME. So looking at Iowa's 10 losses while ranked in the AP, for instance, the Hawkeyes dropped -2.5 spots more per loss than the average team did in the same circumstances.

Got all that? Great. Here you go - have fun arguing.

(click on the column headers to sort)

Losses while in the AP & Coaches Polls, 1998-2008
Team	AP L's	AP +/-	AP diff Avg	leasts	mosts	Co L's	Co +/-	Co diff Avg	leasts	mosts	AP-CO diff	All L's	All +/-	Tot. Avg
Boston Coll	15	1.8	0.1	2	2	13	5.1	0.4	3	2	3.3	28	6.9	0.2
Clemson	17	-18.8	-1.1	1	5	19	-4.4	-0.2	1	2	14.4	36	-23.2	-0.6
Florida St	32	-16.0	-0.5	5	4	32	2.0	0.1	6	5	18.0	64	-14.0	-0.2
Georgia Tech	22	17.3	0.8	4	3	23	17.2	0.7	4	1	-0.1	45	34.4	0.8
Maryland	10	-5.5	-0.6	2	3	10	2.2	0.2	1	1	7.8	20	-3.3	-0.2
Miami (FL)	18	-2.0	-0.1	4	4	17	13.3	0.8	2	0	15.4	35	11.3	0.3
N. Carolina	5	-4.0	-0.8	1	0	3	-6.6	-2.2	0	1	-2.6	8	-10.6	-1.3
NC State	10	20.3	2.0	2	0	11	-0.8	-0.1	1	1	-21.1	21	19.6	0.9
Virginia	16	10.3	0.6	3	1	17	-4.1	-0.2	1	2	-14.4	33	6.1	0.2
Virginia Tech	28	6.7	0.2	4	3	28	5.8	0.2	3	2	-1.0	56	12.5	0.2
Wake Forest	6	-4.4	-0.7	0	1	5	-8.8	-1.8	0	2	-4.4	11	-13.2	-1.2
Illinois	8	-2.0	-0.3	0	1	8	-3.2	-0.4	0	1	-1.2	16	-5.2	-0.3
Iowa	10	-24.5	-2.5	0	5	12	2.6	0.2	0	0	27.1	22	-22.0	-1.0
Michigan	30	0.1	0.0	2	5	31	-1.1	0.0	5	4	-1.2	61	-1.0	0.0
Michigan St	15	-10.5	-0.7	1	3	17	-14.1	-0.8	1	5	-3.5	32	-24.6	-0.8
Minnesota	14	4.4	0.3	2	2	14	6.8	0.5	3	1	2.3	28	11.2	0.4
Northwestern	8	-6.6	-0.8	1	4	10	-4.2	-0.4	0	2	2.4	18	-10.8	-0.6
Ohio St	27	-6.4	-0.2	4	5	25	20.0	0.8	5	2	26.4	52	13.6	0.3
Penn St	19	18.1	1.0	2	1	20	-3.1	-0.2	2	3	-21.2	39	15.0	0.4
Purdue	21	18.7	0.9	4	1	23	-13.6	-0.6	1	5	-32.2	44	5.1	0.1
Wisconsin	24	-14.3	-0.6	3	4	26	-24.2	-0.9	2	6	-10.0	50	-38.5	-0.8
Colorado	14	-25.4	-1.8	1	4	15	-22.2	-1.5	1	4	3.2	29	-47.6	-1.6
Iowa St	4	-2.7	-0.7	0	1	4	2.1	0.5	0	0	4.8	8	-0.7	-0.1
Kansas	4	3.8	0.9	1	1	4	7.8	2.0	2	0	4.1	8	11.6	1.5
Kansas St	18	-1.9	-0.1	3	4	16	7.2	0.4	2	2	9.1	34	5.2	0.2
Missouri	16	24.9	1.6	3	0	16	20.8	1.3	4	1	-4.1	32	45.7	1.4
Nebraska	21	-4.8	-0.2	2	3	21	10.7	0.5	3	3	15.5	42	5.9	0.1
Oklahoma	19	21.2	1.1	7	1	18	31.9	1.8	5	1	10.8	37	53.1	1.4
Oklahoma St	12	12.2	1.0	4	0	12	-3.7	-0.3	3	2	-15.9	24	8.5	0.4
Texas	25	-11.2	-0.4	4	4	24	7.2	0.3	2	0	18.4	49	-4.1	-0.1
Texas A&M	23	41.4	1.8	7	2	24	12.9	0.5	4	2	-28.5	47	54.3	1.2
Texas Tech	10	-6.0	-0.6	1	2	14	10.1	0.7	1	1	16.0	24	4.1	0.2
Cincinnati	4	0.0	0.0	0	1	4	2.4	0.6	0	0	2.3	8	2.4	0.3
Connecticut	3	-7.6	-2.5	0	1	3	-9.7	-3.2	0	1	-2.1	6	-17.4	-2.9
Louisville	11	-11.5	-1.0	1	3	11	-8.6	-0.8	0	1	2.9	22	-20.0	-0.9
Pittsburgh	12	-16.6	-1.4	2	3	11	-6.4	-0.6	1	2	10.1	23	-23.0	-1.0
Rutgers	5	-7.3	-1.5	1	1	4	3.7	0.9	1	0	11.0	9	-3.6	-0.4
S Florida	7	-11.1	-1.6	0	2	7	-20.9	-3.0	0	2	-9.8	14	-31.9	-2.3
Syracuse	6	-14.1	-2.3	1	4	7	-11.5	-1.6	0	1	2.6	13	-25.5	-2.0
West Virginia	15	-34.7	-2.3	1	7	18	-25.0	-1.4	1	3	9.6	33	-59.7	-1.8
Arizona	5	-6.3	-1.3	0	2	5	1.6	0.3	0	1	7.9	10	-4.6	-0.5
Arizona St	17	18.0	1.1	4	1	19	33.2	1.7	5	1	15.3	36	51.2	1.4
California	16	0.5	0.0	2	2	14	-6.5	-0.5	1	1	-7.0	30	-6.1	-0.2
Oregon	26	-1.4	-0.1	3	5	24	-22.2	-0.9	3	6	-20.8	50	-23.6	-0.5
Oregon St	6	-3.4	-0.6	1	1	5	7.7	1.5	2	0	11.1	11	4.4	0.4
Stanford	4	8.6	2.2	1	0	5	4.9	1.0	1	0	-3.7	9	13.5	1.5
UCLA	16	-18.5	-1.2	2	3	18	-15.2	-0.8	3	5	3.3	34	-33.7	-1.0
USC	15	12.2	0.8	2	0	15	17.9	1.2	2	1	5.8	30	30.1	1.0
Wash St	8	5.0	0.6	1	0	7	10.5	1.5	1	0	5.6	15	15.5	1.0
Washington	13	4.5	0.3	2	1	13	14.9	1.1	2	2	10.4	26	19.4	0.7
Alabama	18	18.4	1.0	3	1	16	6.4	0.4	5	2	-11.9	34	24.8	0.7
Arkansas	17	26.9	1.6	6	0	17	14.2	0.8	7	2	-12.7	34	41.0	1.2
Auburn	24	-23.6	-1.0	3	8	23	-37.1	-1.6	2	6	-13.4	47	-60.7	-1.3
Florida	34	-2.9	-0.1	3	3	34	23.3	0.7	7	2	26.2	68	20.4	0.3
Georgia	31	19.2	0.6	8	4	32	33.7	1.1	5	1	14.5	63	53.0	0.8
Kentucky	4	-4.4	-1.1	0	1	6	1.0	0.2	2	2	5.3	10	-3.4	-0.3
LSU	23	1.1	0.0	3	5	23	11.2	0.5	4	0	10.1	46	12.3	0.3
Mississippi	6	14.9	2.5	1	0	7	3.7	0.5	0	0	-11.2	13	18.6	1.4
Miss St	12	13.5	1.1	3	1	11	12.8	1.2	4	2	-0.7	23	26.3	1.1
S Carolina	17	6.5	0.4	2	3	14	-8.1	-0.6	1	2	-14.5	31	-1.6	-0.1
Tennessee	31	-12.0	-0.4	7	7	31	-8.3	-0.3	3	6	3.7	62	-20.3	-0.3
Vanderbilt	2	1.6	0.8	0	0	2	-3.0	-1.5	0	0	-4.6	4	-1.5	-0.4
Air Force	4	11.6	2.9	0	0	6	-2.8	-0.5	0	1	-14.4	10	8.8	0.9
Ball St	2	-3.4	-1.7	0	1	2	-4.9	-2.5	0	0	-1.5	4	-8.3	-2.1
Boise St	6	-2.1	-0.3	2	1	6	-10.7	-1.8	0	1	-8.6	12	-12.8	-1.1
Bowl Green	3	-2.7	-0.9	0	0	5	-9.4	-1.9	0	2	-6.7	8	-12.0	-1.5
BYU	8	1.3	0.2	1	1	10	2.8	0.3	0	0	1.5	18	4.1	0.2
Colorado St	7	14.6	2.1	1	0	8	-5.6	-0.7	1	2	-20.2	15	9.0	0.6
E Carolina	5	5.4	1.1	0	0	4	5.7	1.4	1	1	0.3	9	11.2	1.2
Fresno St	10	11.5	1.1	2	1	10	-23.7	-2.4	1	5	-35.2	20	-12.2	-0.6
Hawaii	2	0.3	0.1	1	1	3	1.1	0.4	0	0	0.8	5	1.3	0.3
LA Tech	1	0.9	0.9	0	0	0	0.0	0.0	0	0	-0.9	1	0.9	0.9
Marshall	2	-3.4	-1.7	0	1	3	-3.7	-1.2	0	0	-0.3	5	-7.1	-1.4
N Illinois	2	0.0	0.0	0	0	3	2.1	0.7	1	0	2.2	5	2.1	0.4
Notre Dame	24	-22.4	-0.9	4	7	21	-6.6	-0.3	2	2	15.7	45	-29.0	-0.6
S Miss	7	-9.1	-1.3	0	2	7	-12.0	-1.7	1	3	-3.0	14	-21.1	-1.5
TCU	10	-7.9	-0.8	0	1	9	-6.3	-0.7	1	1	1.6	19	-14.3	-0.8
Toledo	1	1.6	1.6	0	0	1	-7.8	-7.8	0	1	-9.4	2	-6.1	-3.1
Tulsa	1	-6.1	-6.1	0	1	1	-8.2	-8.2	0	1	-2.1	2	-14.3	-7.1
Utah	1	0.6	0.6	0	0	1	-0.3	-0.3	0	0	-0.9	2	0.4	0.2
UTEP	2	-1.2	-0.6	0	0	2	0.2	0.1	0	0	1.4	4	-0.9	-0.2
Wyoming	1	0.9	0.9	0	0	1	-2.2	-2.2	0	0	-3.1	2	-1.3	-0.7

If your school doesn't appear, it for one of two reasons. First, it could be that your team has never lost while ranked in the Top 25. Those schools are:

Memphis, Tulane, Navy, & Miami (OH).

Props. Sort of. (Tulane and Miami (OH) spent 11 and 6 weeks in the Top 25 without losing, but Navy and Memphis had all of 1 week in the Top 25.)

Second, your team doesn't appear because they have never been ranked in the Top 25 during the BCS era. My condolences. Those schools are:

Duke, Indiana, Baylor, Central Florida, Houston, Rice, SMU, UAB, Army, Western Kentucky, Akron, Buffalo, Central Michigan, Eastern Michigan, Kent St, Ohio, Temple, Western Michigan, New Mexico, San Diego St, UNLV, Arkansas St, Florida Atl, Florida Intl, LA-Lafayette, LA-Monroe, Middle TN St, North Texas, Troy, Idaho, Nevada, New Mexico St, San Jose St, & Utah St.

The good news is that if your team has ever beaten a Top 25 team, they get their own page & their name above in blue is hotlinked like the teams in the table.

Analysis

In looking at those figures in the table, it seems that some teams need to be sending the voters thank-you cards (Texas A&M, Oklahoma, Georgia, Arizona St...), and some should be sending the voters do-better letters (West Virginia, Auburn, Colorado...) And there are a whole lot of other interesting situations to be found with each individual team. For instance, even though Ohio State has been much maligned for the past three years, the polls don't show it - in each of their six losses, they dropped less spots than the average every time in the Coaches poll and half the time in the AP Poll. (And even when they dropped more than the average in the AP, it was less than one spot more.) And did you know that while Oklahoma has 33 wins over Top 25 teams, only 4 of them were over non-conference foes?

But the real meat of this study comes not necessarily in looking at individual teams but taking in the larger picture.

BCS vs non-BCS Teams

Sure, most non-BCS teams have a legitimate complaint that the polls never give them enough respect in the preseason rankings. But does that bias carry over once teams start losing? In the AP, that's a resounding no - 11 of the 19 non-BCS teams actually have a zero or positive average in the AP (meaning they dropped less spots than the average). That's a much better percentage of teams than the BCS conferences where only 29 of 63 teams have a positive average. Air Force and Colorado State are in the Top 5 of teams who get a break, dropping over 2 spots less than the average for comparable teams when they lose. So if anything, the AP voters make up for their preseaon apprehension of non-BCS teams by dropping them less than BCS teams when they inevitably lose.

But the Coaches poll is a different story. Only 5 of the 18 non-BCS teams have a positive average, meaning that the overwhelming majority of non-BCS teams drop further in the Coaches poll after a loss than the average team does. (It's true that in general, the Coaches drop teams further for a loss than the AP, but not by that much - it's a difference of 0.2 spots.) In fact, the Coaches dropped non-BCS teams more than the average in nearly 2/3's of their losses. Looking at it one final way, all of the BCS teams combine for the average 0.0 in the Coaches poll - non-BCS teams combine for a -1.6 average, losing a spot and a half more per game than BCS teams. Remind me again why keeping their ballots secret is a good thing?

Conference vs Conference

What about the conferences? Are there any that receive better (or worse) treatment from the polls? Here's the numbers...

Conf	AP L's	+/-	AP Avg	leasts	mosts	Co L's	+/-	Co Avg	leasts	mosts	AP-CO diff	All L's	All +/-	Tot. Avg
ACC	149	-2.7	0.0	22	22	149	11.5	0.1	16	17	14.2	298	8.8	0.0
Big10	176	-23.0	-0.1	19	31	186	-34.2	-0.2	19	29	-11.1	362	-57.2	-0.2
Big12	166	51.4	0.3	33	22	168	84.8	0.5	27	16	33.4	334	136.2	0.4
BigEast	88	-95.5	-1.1	11	25	89	-60.6	-0.7	9	11	34.9	177	-156.1	-0.9
Pac10	126	19.2	0.2	18	15	125	47.0	0.4	20	17	27.7	251	66.2	0.3
SEC	219	59.0	0.3	39	33	216	49.8	0.2	40	25	-9.2	435	108.8	0.3
CUSA	22	-13.2	-0.6	1	4	21	-21.7	-1.0	2	6	-8.4	43	-34.9	-0.8
MAC	10	-7.8	-0.8	0	2	14	-23.6	-1.7	1	3	-15.8	24	-31.4	-1.3
MtnWest	24	24.1	1.0	2	1	28	-13.4	-0.5	1	4	-37.5	52	10.8	0.2
WAC	23	10.0	0.4	5	4	24	-33.0	-1.4	2	6	-42.9	47	-23.0	-0.5

That pretty much confirms what we just found looking at BCS vs non-BCS conferences: non-BCS teams get the shaft in the Coaches Poll but the AP doesn't seem to distinguish between BCS & non-BCS. The MtnWest drops a whole spot less than the average in the AP, but they drop half a spot more with the Coaches. And check out the BigEast - they're not getting any love anywhere. Pac10 vs SEC? Pretty much equal when they lose, but the AP tends to prefer the SEC while the Coaches prefer the Pac10.

Year by Year Since 1997, both the number of Top 25 losses to account for (usually between 80-100 per year) and the average number of spots dropped fluctuated, bobbing up and down. But there's no correlation between the two - more losses in a year doesn't mean teams drop further for each one. But there is an unmistakable trend that both the Coaches and AP Polls are punishing teams more for a loss now than they did before the BCS. This tells us two things: first, that wherever the premium was before (whether it was winning or playing a tough schedule or defending home-field), has shifted to not losing. Second, this trend towards more spots dropped per loss could be because there's more quality choices (teams) for voters to choose from when filling out their ballots. But this doesn't prove that there's more parity in the game today - it proves that people BELIEVE that there's more parity in the game today.

____________________________________

So that's that. Again, you can click on each team's name in the table (and paragraph) above to see a breakdown of their individual losses while in the Top 25 & wins against the Top 25.

What's that? More? Oh, alright. These tables detail teams' number of weeks in the Polls & the number of votes received during the BCS era and a comparison of teams' performances in and against the Top 10 / Top 25. Both of these new stats pages can now be found on the left sidebar and will be updated weekly during the season.

If you've made it this far, thanks for reading.

Did You Know...

...that nearly 75% of the first-place votes cast during the BCS era have been for one of only 5 teams?
Of the 12,418 AP votes and 11,213 Coaches votes:

USC (2,247 AP / 2,163 Coaches) has received 19% of them,
Ohio State (1,922 AP / 1,856 Coaches) has received 16% of them,
Oklahoma (1,900 AP / 1,728 Coaches) has received 15% of them,
Miami (FL) (1,881 AP / 1,674 Coaches) has received 15% of them, and
Florida State (1,247 AP / 954 Coaches) has received 9% of them.

28 teams (3,221 AP / 2,837 Coaches) have combined for the remaining 25% of the first-place votes.

The Arguments For & Against a DI-A College Football Playoff

The possibility of Division I-A college football deciding its champion by using a playoff is one of the biggest issues in the sport today, and there are many differing opinions on the propriety and feasibility of such a course of action. To the casual sports fan, everything starts with the fact that most people aren’t satisfied with how college football names its champion. In fact, most fans are rather furious about it. Part of what they’re furious about is that on the surface, it seems like such an easy problem to fix. Have a playoff – problems solved!

Oh, if it were that simple.

It’s not, which is the main thing I hope you’ll realize from reading through this whole section. People are always going to be split on the playoff argument, no matter how it gets resolved (if it ever is), and not many of us are under the delusion that reaching a consensus is possible. There are a lot of complex issues and parties involved, and they all must be looked at together as a whole – it’s impossible to untangle and separate them out, as you’ll see from the following. My aim in developing this section is to present both sides of the arguments equally, showing supporting evidence and ideas both for and against a playoff. But I’m not only writing about the issues – I’m also trying to show how people fight and argue about and manipulate the issues as well. Both sides employ dubious logical tricks to confuse the situation and muddy the waters, which is part of the overall problem. Whether you’re in favor of some type of playoff, against one, or on the fence, mull the issues over, post replies and rebuttals, and in general, step back and look at the problem as a whole.

For easy reference, arguments that support a playoff are in green and those against a playoff are in red. And a word of caution: at points in the discussing of these issues, you’ll think that I’ve skipped over something, or have omitted a counterpoint, or don’t take the argument to the next logical level. The reason for that is because my writing and your reading is linear – the issues are not. They’re a big, tangled web, and each issue is informed by and informs other arguments and issues related to it. Each one has multiple counterpoints and multiple next levels. I’ve tried to point this out as much as I can, but it’s not gonna be pretty. We’re going to be jumping around a lot – just hang on. (This isn't rocket surgery people, but it's not tiddlywinks either...)

Setting the Scene

“Championships are clear-cut and objective”

vs

“Championships are for the best, even if that’s subjective”

How mythical do you want your champion to be? This is where it begins. From a pure, competition standpoint, most of the overall playoff argument boils down to how to name a champion and two competing definitions. In sports that hold a playoff at the end of the regular season, the champion is the team which is good enough to make it into the playoff and then wins the playoff. It’s an solution that cannot be argued with and is very objective. Either your team wins the playoff and they’re clear-cut champions or they don’t and they’re not. But there’s another, equally valid definition of champion – the team which performed the best over the course of the whole season. This definition is subjective, since there’s rarely a definitive way to answer which team performed the best. A ranking system is used, and a majority of votes determines the champion. The vast majority of sports use the first definition, including a playoff after their regular season, while college football is the only major sport that uses rankings to determine their champion(s). Right now, most people would prefer that college football have a clear-cut champion instead of one that is the best. But the problem with reconciling these two types of champions is that the systems that produce them don’t overlap – they’re designed to do two different things. A playoff is designed to produce an objective champion that is clear-cut, not one that is the best: the rankings are designed to produce a subjective champion that is the best, not one that is clear-cut. So in order to get the clear-cut champion that they want, a lot of people are pro-playoff.

Before we move on, we have to flesh out this objective vs subjective landscape a bit, since it’s important to most, if not all, of the competition-based arguments and issues we’ll run into. Even though I think this objective vs subjective approach is the most rational way to look at the playoff issue, don't think that I’m presenting it and basing everything on it simply because it’s my pet and I prefer it. Let's examine the situation in more detail to and I hope you'll see that it is a good, solid point of view.

the Objective-Subjective Landscape

What is the overall goal or purpose of any competition or sport? To find out who’s better. That’s what everything boils down to on most levels – who is better. At one end of the landscape, the most simple unit of team sports is purely objective – the game. Either you win or you lose. It’s not up for debate, and you can’t argue with the scoreboard. (Thankfully for our purposes here, college football doesn’t have ties anymore, so we don’t have to deal with them.) The game decides who’s better on that day between two teams. Period. But once you get past the level of the game, when you expand to look at multiple teams playing multiple games and trying to find out who’s better over the course of a long season, you slide into subjective territory. There’s no realistic way to avoid it – it’s part of sports when you’re dealing with a whole season. Why is this so?

We can see it in the simplest example. On the first day of the season, Team A beats Team C. We know for certain that Team A is better. There’s no question, and no discussion (or arguing) needed. But let’s add in another game: Team B beats Team D. We know that Team B is better than Team D, no question, but who is better, 1-0 Team A or 1-0 Team B? Any answer is going to be subjective. Add in another week: Team A beats Team D, and Team B beats Team C. Now who’s better, 2-0 Team A or 2-0 Team B? Whatever your answer is, it’s subjective. You might want more information, like the scores, or locations, or stats, to help you decide who’s better, but that’s a judgment call – not everyone uses the same information or places the same value on aspects of the game. And that’s just four games over two weeks. Now try doing that with seven hundred games over fifteen weeks. Subjectivity is there, whether we like it or not. (Of course it’s not always that ambiguous or definite, as we’ll see.)

Technically, there’s only one way for a whole season to be completely objective – make the whole season a single-elimination playoff. Play the first round of games, the winners move on, the losers are done. Keep playing until there’s only one team left standing, the champion. Team A beats Team C, and Team B beats Team D, then Team A beats Team B = Team A is the best. Another way that comes close to pure objectivity is if every team plays every other team in the league the same number of times home and away. In theory, that would get rid of strength of schedule, home-field advantage, and a host of other subjective considerations. But that setup would only work if the season ended with just one team having the best record – more than one and you have to get subjective to determine the champion. (For instance, if we add one more week to our first example – Team A beats Team B, therefore at 3-0, Team A is seasonally better than any of the other teams.) But the whole point is rather moot because no major sport sets their season up in either of these fashions, mainly because they’d end up with too few or too many games. Teams play each other different amounts of games or even not at all, and the playoff isn’t instituted until the regular season is done. So there is some subjectivity involved no matter what.

Achieving Fairness in Competition

Most fans understand that no sport can make their system and championship competition 100% fair for everybody – it just doesn’t happen. Somebody or some team is always going to have some problem with the way things are done. Most team sports try to make their championship competition fair by avoiding as much subjectivity as they can, basing important things past the game level (such as standings, playoff spots, seeds, etc.) on objective win-loss records. The more you win, the better you are, the further you go. Simple as that. But even this setup isn’t completely fair – the fact that teams are divided up into conferences and divisions makes things partially unfair. Don’t believe me? What about when teams are included in a playoff at the expense of teams who have better win-loss records? It happens all the time, most notably this past NFL season when the New England Patriots went 11-5 and were left out of the playoff while the San Diego Chargers went 8-8 and were included. Sure it was going by division champions, which is a type of objectivity, but was it fair? No. But most fans generally accept the minute amount of unfairness in most playoff systems because they feel it’s better to err on the side of objectivity rather than subjectivity.

College football on the other hand uses rankings to decide most things past the game level. I know that there’s a lot of people out there who think that the rankings are hugely subjective (they are) and that they’re unfair (they can be). But few will argue that we don’t need the rankings at all – they’re necessary to college football, as annoying as that can be. Most fans understand that even though some sports (usually professional) can create mostly fair competition by going by win-loss records, thereby eliminating subjectivity, other sports (usually collegiate) must create fair competition by using rankings and making their inherent subjectivity work for the sport. The big question is how much do we need or should we use the rankings to maximize fair competition? There are advantages and disadvantages to being on either side of the landscape, and each sport has it’s own fair balance. So when it comes to naming a champion, the trick for all sports is how to find a fair, competitive balance between the objectivity of the game and the subjectivity of the season.

Regarding the competitive aspects of the playoff issue, the vast majority of the time pro-playoff fans think the balance is on the objective side while anti-playoff fans think the balance is on the subjective side. These are their territories, so to speak, complete with different sets of rules for naming a champion and different ideas of what’s fair and what’s not. That isn’t to say that the pro-playoff side doesn’t use subjective arguments, or that the anti-playoff side doesn’t use objective arguments – both sides are willing to use whatever weapons they can if it helps them support their ultimate goal of finding the clear-cut or best champion. More often than not, each side ends up proving the other’s point and shooting themselves in the foot, throwing many an argument onto a merry-go-round of logic that can be impossible to escape from. It’s quite fascinating/laughable, as I hope you’ll see.

the Betters

One of the main problems in discussing these objective-subjective issues, which I brought up at the end of last season, is the use of the term ‘better’. Corresponding quite nicely with our divided landscape, there are two main definitions of better: what we’ll call on that day better and seasonally better. On that day better is completely objective and cannot be argued with – either your team won on that day and they were better than their opponent, or they lost and their opponent was better. Because of the way seasons are structured, seasonally better is subjective and is argued about all the time. They’re VERY different and mean completely different things, yet people fail to distinguish between them constantly. You’ve seen these types of arguments:

Oklahoma is better than Texas.

No way – Texas beat them 45-35!

So what? Going by that, then you have to say
that Texas Tech is better than Texas,
since the Red Raiders beat the Longhorns.

Texas obviously had a better season than Texas Tech.
The Longhorns didn’t get blown out 65-21 by Oklahoma –
their one loss was by 6 points on the last play of the game.

And on and on, around in circles we go. Oklahoma, Texas, and Texas Tech all were on that day better than one of the others, and since seasonally better is subjective, we’re stuck. This is what happens when you don’t keep your betters separate, people – you get caught up in a big, circular tug of war that doesn’t accomplish anything. So for the sake of alleviating misunderstandings, please keep your betters separate. If you purposefully use the betters interchangeably in order to win arguments and feel smart, stop it – that’s a dick thing to do and you’re not helping the situation.

So that’s the basic lay of the land that we’re going to be covering here. Let’s look at some other variations of this objective clear-cut champion vs subjective best champion feud. The space between the two sides is illuminated a little better by switching the definitions, attempting to equate a playoff with a subjective champion and a ranking system with an objective champion. We know that a playoff produces a clear-cut champion 100% of the time, and that rankings produce the best champion 100% of the time – but can each system produce the other?

(Top) <> Fair Competition I: Switching Sides

2008 Versions of the BCS (unofficial)

Greetings, all. As you might have noticed, I didn't post my usual addition the Versions of the BCS section of this site this past December. That was mainly because 1) the rankings are still incomplete and even in the best circumstances involve a lot of guesswork, (especially since two of the computers are no longer ranking teams); 2) the trend these past three years is for all versions to name the same top two teams; and 3) it's a lot of damn work to gather all the data and crunch the numbers.

But since a loyal reader asked, here's an unofficial version - let's take the data we do have and see what happens.

You remember the official rankings from December, don't you?

Version E-2: 2008
Rank	Team	Harris	Votes	Harr%	Coach	Votes	Coach%	Comp%	Total
1	Oklahoma	2	2699	0.9554	1	1482	0.9718	1.000	0.9757
2	Florida	1	2776	0.9827	2	1481	0.9711	0.890	0.9479
3	Texas	3	2616	0.9260	3	1408	0.9233	0.940	0.9298
4	Alabama	4	2442	0.8644	4	1309	0.8584	0.810	0.8443
5	USC	5	2413	0.8542	4	1309	0.8584	0.750	0.8208
6	Utah	7	2119	0.7501	7	1134	0.7436	0.860	0.7846
7	Texas Tech	8	2090	0.7398	8	1132	0.7423	0.870	0.7840
8	Penn State	6	2186	0.7738	6	1193	0.7823	0.660	0.7387

Going back ten years, let's look at what Version A might have been. Columns in green are ones that I don't have numbers for but am guessing at.

Version A: 2008
Rank	Team	AP	Coach	Polls	Computers	SoS	Losses	Totals
1	Oklahoma	2	1	1.5	1	0.16	1	3.66
2	Florida	1	2	1.5	4	0.16	1	6.66
3	Texas	3	3	3	2.5	0.16	1	6.66
4	Utah	7	7	7	3.5	2.00	0	12.5
5	Alabama	4	4	4	6	1.60	1	12.6
6	USC	5	4	4.5	7	1.60	1	14.1
7	Texas Tech	8	8	8	4	1.40	1	14.4
8	Penn State	6	6	6	8	1.40	1	16.4

The computers used in Version A were Jeff Sagarin's, Anderson & Hester, and the NY Times (which we no longer have). Since we only have two of the three, I just averaged their two rankings for the overall. Oklahoma was #1 in all computers this year, so they get a rank of 1. Florida was #4 in both, while Texas was #2 & #3. We don't know how things would've played out had the NYT ranking been in play, but it would've been close to that, probably.

As far as the strength of schedule goes, I took the liberty of ranking Oklahoma, Florida, and Texas all the same in this category - it's my best guess and an attempt to make things fair. They'd all be at about #4 in SoS. Utah gets a 2.00 for the 50th toughest schedule, Alabama and USC the 40th toughest, and Texas Tech and Penn State at the 36th toughest. (If you happen to know the real SoS rankings according to the way they used to be tabulated, or if you're so inclined to crunch the numbers, send them along and I'll put them in - here's the formula.

Oklahoma would be in no doubt, but #2 would be razor-thin between Florida and Texas. The NYT didn't care too much about losses (not that it would help us here), but SoS was of major importance - so basically whoever had the tougher schedule was in. Let's move on.

Version B: 2008
Rank	Team	AP	Coach	Polls	Computers	SoS	Losses	Totals
1	Oklahoma	2	1	1.5	1	0.16	1	3.66
2	Florida	1	2	1.5	3.75	0.16	1	6.41
3	Texas	3	3	3	3	0.16	1	7.16
4	Alabama	4	4	4	5.75	1.60	1	12.35
5	Utah	7	7	7	4.5	2.00	0	13.50
6	USC	5	4	4.5	6.5	1.60	1	13.60
7	Texas Tech	8	8	8	4	1.40	1	14.40
8	Penn State	6	6	6	9.5	1.40	1	17.90

The only major thing that changed in Version B were the computer rankings, since there were a lot more of the in this version. For the most part, they'd probably put Florida ahead of Texas, solidifying the Gators at #2. Even if the Longhorns had a significant edge in SoS, which is debatable, it probably wouldn't be enough to help get them to #2.

Version C: 2008
Rank	Team	AP	Coach	Polls	Computers	SoS	Losses	Q-wins	Totals	(quality wins)
1	Oklahoma	2	1	1.5	1.00	0.16	1	-1.5	2.16	TX Tech, TCU, Cincy, OK State
2	Florida	1	2	1.5	3.67	0.16	1	-1.2	5.13	Alabama, Georgia
3	Texas	3	3	3	2.67	0.16	1	-1.5	5.33	Oklahoma, OK State
4	Alabama	4	4	4	5.83	1.60	1	0.0	12.43	(none)
5	Utah	7	7	7	4.50	2.00	0	-0.2	13.30	TCU
6	Texas Tech	8	8	8	4.17	1.40	1	-1.2	13.37	Texas, OK State
7	USC	5	4	4.5	6.83	1.60	1	-0.5	13.43	Ohio State
8	Penn State	6	6	6	9.33	1.40	1	-0.5	17.23	Ohio State

When we get to Version C, the Quality Wins component is added in. It helps Oklahoma pad their lead at #1 even more, and makes things close between Florida and Texas. But I'd bet the Gators would still be ahead, since they have the edge in the polls.

Version D: 2008
Rank	Team	AP	Coach	Polls	Computers	SoS	Losses	Q-wins	Totals	(quality wins)
1	Oklahoma	2	1	1.5	1.00	0.16	1	-0.3	3.36	Texas Tech
2	Florida	1	2	1.5	3.67	0.16	1	-0.6	5.73	Alabama
3	Texas	3	3	3	2.67	0.16	1	-1.0	5.83	Oklahoma
4	Alabama	4	4	4	5.83	1.60	1	0.0	12.43	(none)
5	Utah	7	7	7	4.50	2.00	0	0.0	13.50	(none)
6	Texas Tech	8	8	8	4.17	1.40	1	-0.7	13.87	Texas
7	USC	5	4	4.5	6.83	1.60	1	0.0	13.93	(none)
8	Penn State	6	6	6	9.33	1.40	1	-0.5	17.73	(none)

The only difference between C and D was the you only got quality win points for beating teams in the Top 10 instead of the Top 15. Pretty similar.

Version E: 2008
Rank	Team	AP	Votes	AP%	Coach	Votes	Coach%	Comp%	Total
1	Oklahoma	2	1540	0.9477	1	1482	0.9718	1.000	0.9732
2	Florida	1	1602	0.9858	2	1481	0.9711	0.890	0.9490
3	Texas	3	1530	0.9415	3	1408	0.9233	0.940	0.9349
4	Alabama	4	1410	0.8677	4	1309	0.8584	0.810	0.8454
5	USC	5	1372	0.8443	4	1309	0.8584	0.750	0.8176
6	Utah	7	1225	0.7538	7	1134	0.7436	0.860	0.7858
7	Texas Tech	8	1193	0.7342	8	1132	0.7423	0.870	0.7821
8	Penn State	6	1259	0.7748	6	1193	0.7823	0.660	0.7390

And finally the first Version E, with the AP Poll instead of the Harris. No significant changes here - still Oklahoma at #1 and most likely Florida at #2.

Overall, Oklahoma would've been there undoubtedly. And the big difference between Florida and Texas in most of the versions is the fact that the Gators were #1 in the AP while the Longhorns were #3 - that 1.5 points in most polls would've been hard to make up. Alabama, Utah, USC, Texas Tech, and Penn State are all significantly behind those big three.