FAQ's

These questions have been pulled from the comments sections, have been asked elsewhere, or have been thought of by me. Ask 'em and I'll try to answer 'em.

Q: Referring to your "Modified Season", isn't having so few non-conference games in September and October (1 per team) going to make it harder to compare conferences?

A: Ah, conference strength. One of the most debated topics in college football. In looking at the system there will still be over 100 non-conference games in September and October, more than enough for the computers to use and a decent number for pollsters to make a rough estimate of conference strength. We'll know that a Big10 that's 9-0 or 8-1 against other conferences is probably stronger than a 4-5 or 3-6 WAC. And all we need in those first two months is a rough estimate, since in November the strong teams play each other and the weaks teams play each other, giving us an even better idea of relative conference strength. At the end of the season it will result a more accurate measure of conference strength than the current format. Also, being able to only estimate conference strength in October might alleviate some of the blatant conference biases and would allow for a more balanced November schedule with more non-BCS conference teams making it into the top 32.

Q: How would the money work in tMS? There's no way the big whigs would buy into a modified season if it didn't guarantee them $$$

A:True. Money is one of the big issues, as we all know (and as I talked a bit about here.) I won't claim to know all the ins and outs of college football's finances, but it seems to be that this system could bring in just as much money as the current one if not more.

The questioner points out that no big school would buy into a system which didn't guarantee them as much money as they're making now, which I would fully agree with. As a generalization, right now the big schools make big dough by having home games, and little schools get decent size payoffs by playing at the big schools. The thing about the Modified System is that it maximizes its revenue potential by granting more home games to the teams which bring in the most money.

Right now, big schools usually have either 7 or 8 home games. In tMS, they could have at least 5 of those in September and October: 4 home conference games and 1 home non-conference game. In November, home games are awarded by attendance ranking and victories, so many of the best teams will have 3 or 4 more home games, bringing their total to 8 or 9. So most teams will have as many home games as they do now, if not 1 or 2 more.

In addition, their opponents would be much higher caliber, guaranteeing more demand for tickets. Only die hard fans want to see Georgia vs. Western Carolina. Georgia vs. USC, Texas Tech, and Virginia Tech would sell out in a matter of hours.

There's two "X" factors though. First, the conferences could renegotiate for a sweeter TV deal. With the top-tier matchups in November, ratings would probably go up (maybe not much, but who knows). Or the NCAA could negotiate as a whole. Either way, there would probably be more money coming in from TV and advertising. Second, all of the other college football playoffs (Division I-AA, II, & III) have clauses (found here) in their post-season rulebooks which state that in order for a school to be able to host post-season games, they have to be able to guarantee a certain number of fans and a certain amount of revenue. This type of statement could be used as a buffer by the Official Committee to insure that November games are held at the most profitable locations so that all teams (including "those-who-must-be-kept-happy") profit.

Even though the scheduling issue would be daunting, the financial payoff has huge possibilities, enough to make it worth the trouble.

Q: Where is the dividing line, or cut-off, where a team can possibly make it into the National Championship game? There's something slightly unappealing about the fact that group A games are often between one or even two teams which are 'out of it'.

A: These questions/points were raised by a commenter, and they're good ones. I'll try to break it down and explain as best I can.

First off, I'll say that the goal of the Modified System is to pair the two best teams from the regular season in the National Championship game. This is the exact same goal that the BCS currently has. The difference is that tMS sets up a logical way to identify which two teams are the best, while the BCS, well, doesn't. So our main concern will always be with Group A and pairing the most successful teams together. All of the other matchups are just icing on the cake (or not, depending on your take.)

The easy answer to where the cut-off line lies is that it depends on the number of upsets. The more the higher ranked teams fall, the more of a chance the lower ranked teams have of moving up. Let's work backwards, understanding that pollsters and computers rarely move teams more than 4-6 spots in a given week at the end of the season, possibly less since all of the competition at this level is solid. So in order to be top 4 by week 5, you'd have to be top 8 by week 4, top 12 by week 3, and probably top 16 in week 2, the starting week. So the cut-off seems to be around #16, halfway through Group A, but again, this depends on how the teams in front of you do. (If you're all the way back at #16 though, you're gonna need a lot of losses in front of you to move up all the necessary spots. If teams in front of you win you won't move, while if they lose you'll probably move up.)

So in order to be in the NC game, you'd definitely have to be in the top 4 in Week 5 and then win your #1 vs #4 or #2 vs #3 matchup. In order to do that, you'd pretty much have to be in the top 8 by week 4, but even at #8 it'd be tough to get in. The commenter wondered what would happen if in Week 4...
#8 beats #1
#2 beats #7
#3 beats #6
#4 beats #5
It's a great example to use. #2, #3, & #4 move up to #1, #2, & #3, so who's #4? Is it the previous #8 or previous #1? This gets to the crux of the issue, and the answer is that the voters (and computers) will have to decide that.

First off, there's going to be more variables than just #8 defeated #1. What was the score? Was it close? What are the teams records? These are all questions the voters (and computers) need to take into account when they make their rankings. Will there be controversy, no matter who gets chosen? Yes. (There's no way to completely eliminate the controversies that arise in college football. But I'd rather deal with this minor one than, say, in a single-elimination playoff where a #2 ranked 9-0 team might get knocked off by a #31 ranked 5-4 team and be done. At least with the Modified Season the regular season still counts.)

Q: Why the whole "32->16->8->4" setup? The 1/2 cutoff each week makes it tough for cinderellas to 'win their way up'. Suppose the system was slightly modified so the size of Group A didn't go down by 1/2 every week. What if it went like: 24->14->8->4?

A: I think there's positives and negatives to both of these setups. I guess it comes down to which one gives the most opportunity to the most teams, and in thinking about it, they both seem about equal. You've gotta be in the top 4 at the end of week 5 in both, and in the top 8 at the end of the week 4 (see the above question). Would a team have a better chance of moving up to the top 8 in a 32->16->8 setup or a 24->14->8 setup? They seem pretty equal to me at a glance.

In terms of appearances, I think the 32->16->8->4 system resembles a traditional playoff more, which I think people would find appealing and more understandable.

Ways to Fix the Rankings Right Now

This is a list of ways to make the human polls & computer rankings fairer (so that every Division I-A team has the same chance at making it to the National Championship game). These are things that would be relatively easy to implement and could be done between seasons - there's no need to wait until the next post-season incarnation, whether it's another version of the BCS, a playoff, etc.

1) Give official instructions to Official poll voters…

Part of the problem with voter differences in the polls is that people interpret the poll very differently. One voter may rank teams based on how well they’ve played so far in the season, another may rank them on their potential, another may rank them on who would beat who in a matchup (something nobody really knows until they play)… it makes for a very uneven poll that is more of an average than a near consensus. If there were more instructions for the voters, it would lead toward a common goal and would be more acceptable to more people. Part of the job of this committee would be to settle on a definition of “National Champion”.

2) … and then don’t release the Official Rankings until mid-October.

As it is now, the BCS doesn’t come out until October, which is a good thing. This shows that people recognize that when polls are released has an impact on the outcome of things. However, the Coach’s poll comes out in August, and since it’s part of the BCS rankings, that rather defeats the purpose, doesn’t it? Other polls, like the AP, are more than welcome to start in August – but the Official Rankings and all polls involved in them should not even be considered until mid-October.

3) Give the computer rankings and human polls the same weight in the Official Rankings

After 2004, when USC was left out of the national championship game after being ranked #1 in both polls, the weight shifted to the human polls being worth 2/3 of the BCS rankings and the computers being worth only 1/3. People seem to think that this solved the situation, but it begs more in-depth questioning. Each of the methods, computers and humans, have advantages and disadvantages. Let’s list some of each –

Humans: People are able to take into account more flexible data, such as how a team played, luck, bad referee calls, and other intangibles. On the negative side, people are always biased, as much as they claim (or would prefer) not to be, almost always tilting the scales in one direction unfairly.

Computers: Computers are unbiased (as much as their programming is) and are able to compare huge volumes of concrete data, mathematically examining teams in relation to one another. They’re also the same throughout the season, and usually years – they cannot be changed from one week to the next. On the negative side, they cannot take much flexible data into account and cannot see the intangibles that humans can.

All in all, we need the computer and humans to balance each other out. Each has strengths and weaknesses that the other can compensate for, so a balance of power between the two is preferred.

4) Margin of Victory should be factored into the computers (to an extent)

One of the main problems that people have with the computers is that since 2000 they’re not allowed to use margin of victory (MoV) as a factor. (Some polls the BCS used were even dropped because they refused to give up this component of their rankings.) To human eyes, if Team A beats Team C 54-3, and Team B beats Team C 24-21, Team A deserves more credit and has achieved more. But since computers are not allowed to factor this in, in theory they would rate Teams A & B the same. But what comes into play with MoV is sportsmanship. Part of the reason that MoV isn’t allowed to be factored in is that the powers that be don’t want teams running up the score on inferior opponents in an attempt to boost their rankings. But there are ways to factor in MoV without encouraging unsportsmanlike behavior. Putting a cap on the MoV at, say, 21 points, like the BCS had previously, does not encourage teams to run up the score, yet it rewards them more for a sound victory than for squeaking by. (I suggest using tiers of how many possessions it would take to change the game, such as 1-3 pts (field goal), 4-8 pts (1 TD), 9-16 pts (between 1 & 2 TD's), and 17+ (over 2 TD's).

5) Official Voter’s ballots need to be made public at all times

This mainly pertains to the Coach’s poll, which has historically been secretive and has only just recently been made public after the regular season is over. It will allow for more transparency in the system, which is definitely needed because of all the issues at hand. Coaches (and the people who may fill out their ballot for them) are human, with biases just like the voters whose ballots make up every poll taken in college football. A big difference though is that Coaches stand to gain considerably because of their biases – the higher they rank themselves or the team’s they’ve played, the better the chance that their school will reap benefits. That isn’t to say that all coaches disingenuously fill out their ballots in their own favor, though I’m sure some do. But the possibility is so much greater when they are allowed to keep their ballots secret and thus aren’t held accountable. By making their ballots public every week, it will probably reduce the amount of skewing, intentional or otherwise, especially at the end of the season when their ballots are made public.

*A Thought about Rankings... You know, it always grates on my nerves when people gripe and moan about Team A being ranked lower than Team B after Team A beats Team B. Let's think about this logically.

First, we wouldn't ever say that a 1-7 Temple team should be ranked higher than 6-2 Notre Dame, even after knocking the Fighting Irish off (in theory). Why? Because 6-2 is a lot better than 1-7, obviously, and in this case, the teams' records trump the on-field outcome. So right there we have two factors that come into play: 1) head-to-head outcome, and 2) record. Most of the griping comes when teams' records are close, usually within 1 or 2 games of each other, like if Temple had been 6-2 or 5-3 after the game. In this case, people use records to "prove" that the teams were close to equal, and that the head-to-head victor should be ranked higher.

But there's another factor: 3) opponents. If Notre Dame has beaten USC, Ohio State, and Michigan on their way to 6-2, while Temple has beaten Army, Duke, and UConn, people are going to give more credit to Notre Dame because their schedule is (seemingly) harder. I put the "seemingly" in there because strength of schedule is one of the most subjective things humans can try to measure without using computers. Computers have the ability to objectively look at and compare teams to each other using the same mathematical formula for each team. Even then, people disagree as to what the correct or best mathematical formula is for calculating SoS. Because they can do this, computers are often railed against because they don't automatically put Team A higher than Team B when all else is equal.

But is all else ever equal? No, I would argue never. With regards to SoS, unless teams play exactly the same opponents, which they usually never do, and play them in the same weeks, which is impossible, their SoS will always be different, providing that minute fraction which might keep Team B ranked above Team A. Or it could be some completely other factor which the computer takes into account which provides the margin of difference.

My point is that the rankings take the whole season into account, not just single weeks. So whenever you see Team A NOT jump Team B in the rankings after beating them, take a second to think about how many different factors are involved in determining those rankings and realize that it's a much more complex issue/calculation than just "Team A beat Team B so Team A is better".

2006 Strength of Schedule

Versions A-D of the BCS used Strength of Schedule as part of the equation, as we all know. The formula was 2/3 your opponent's winning percentage (oW & oL) and 1/3 your opponenet's opponent's winning percentage (ooW & ooL). (There's a good breakdown of the specifics here at Strength of Schedule Explained.)

According to this formula, here's how the SoS component would've looked in 2006...

Rank	Conf.	Team	W	L	oW	oL	ooW	ooL	SoS%	Q-Pts
1	Pac10	USC	10	2	77	51	823	694	0.5819	0.04
2	Big10	Michigan	11	1	78	50	746	724	0.5754	0.08
3	Pac10	Stanford	1	11	75	51	782	711	0.5714	0.12
4	SEC	Florida	11	1	81	55	799	767	0.5671	0.16
5	Pac10	UCLA	7	5	73	54	807	694	0.5624	0.20
6	Big10	Minnesota	5	6	71	48	695	745	0.5586	0.24
7	SEC	South Carolina	6	5	70	49	712	720	0.5579	0.28
8	SEC	Tennessee	9	3	72	53	773	722	0.5564	0.32
9	Pac10	Arizona	5	6	71	54	767	679	0.5555	0.36
10	BigEast	Cincinnati	6	5	71	49	685	741	0.5546	0.40
11	SEC	LSU	10	2	72	55	786	721	0.5518	0.44
12	Pac10	Washington	5	7	72	56	797	707	0.5516	0.48
13	SEC	Kentucky	6	5	69	53	721	722	0.5436	0.52
14	Pac10	California	8	3	66	56	791	669	0.5412	0.56
15	Big12	Texas	8	3	69	52	675	763	0.5366	0.60
16	Pac10	Oregon	6	5	67	57	776	697	0.5358	0.64
17	SEC	Auburn	10	2	70	58	770	731	0.5356	0.68
18	BigEast	Connecticut	3	8	68	53	666	724	0.5344	0.72
19	ACC	Florida State	6	6	71	56	723	770	0.5341	0.76
20	Pac10	Oregon State	8	4	73	61	806	768	0.5339	0.80
21	Indy	Notre Dame	10	2	69	59	781	722	0.5326	0.84
22	BigEast	Louisville	11	1	66	56	737	705	0.5310	0.88
23	Big10	Penn State	7	4	66	54	709	738	0.5300	0.92
24	Pac10	Washington State	6	6	66	60	813	687	0.5299	0.96
25	Big10	Ohio State	12	0	66	59	763	700	0.5258	1.00
26	SEC	Arkansas	9	3	71	63	807	754	0.5256	1.04
27	BigEast	Syracuse	4	8	66	58	745	721	0.5242	1.08
28	Big10	Indiana	5	7	65	55	696	734	0.5233	1.12
29	SEC	Mississippi State	2	9	64	57	719	714	0.5199	1.16
30	Big10	Illinois	1	10	65	56	691	749	0.5181	1.20
31	ACC	North Carolina	2	9	64	55	673	748	0.5164	1.24
32	Big12	Oklahoma State	5	6	68	56	641	778	0.5162	1.28
33	Big10	Iowa	5	6	62	55	698	739	0.5152	1.32
34	ACC	North Carolina State	2	9	64	55	682	778	0.5143	1.36
35	ACC	Boston College	8	3	65	58	685	752	0.5112	1.40
36	BigEast	West Virginia	9	2	63	58	690	715	0.5108	1.44
37	SEC	Vanderbilt	3	8	61	61	751	690	0.5071	1.48
38	SEC	Mississippi	3	8	63	59	710	747	0.5067	1.52
39	Big12	Oklahoma	11	2	68	66	800	791	0.5059	1.56
40	Big12	Nebraska	8	4	69	63	730	820	0.5055	1.60
41	BigEast	Rutgers	9	2	62	58	673	727	0.5047	1.64
42	Big10	Michigan State	4	8	63	64	772	710	0.5043	1.68
43	Pac10	Arizona State	6	5	61	62	753	703	0.5030	1.72
44	ACC	Virginia Tech	9	2	63	60	671	757	0.4981	1.76
45	WAC	Utah State	1	11	66	60	671	832	0.4980	1.80
46	SEC	Alabama	6	6	63	65	762	735	0.4978	1.84
47	Indy	Temple	1	11	66	62	694	809	0.4977	1.88
48	MtnWest	Air Force	4	8	65	61	674	793	0.4971	1.92
49	ACC	Maryland	7	4	63	61	674	752	0.4963	1.96
50	SEC	Georgia	7	4	59	62	730	703	0.4949	2.00
51	Big10	Northwestern	4	8	61	60	690	760	0.4947	2.04
52	ACC	Clemson	8	4	61	64	752	736	0.4938	2.08
53	ACC	Georgia Tech	8	4	67	66	724	813	0.4929	2.12
54	CUSA	Tulane	4	8	63	63	720	785	0.4928	2.16
55	BigEast	Pittsburgh	5	6	59	61	685	719	0.4904	2.20
56	Big12	Baylor	3	8	60	61	667	754	0.4870	2.24
57	Big12	Texas Tech	6	5	61	62	659	760	0.4854	2.28
58	Big12	Texas A&M	8	3	59	61	683	765	0.4850	2.32
59	ACC	Duke	0	12	59	61	672	756	0.4846	2.36
60	ACC	Miami (FL)	5	6	59	62	684	748	0.4843	2.40
61	CUSA	Rice	7	5	61	66	722	771	0.4814	2.44
62	Big12	Missouri	7	4	62	64	643	766	0.4802	2.48
63	MAC	Buffalo	2	10	64	66	693	848	0.4781	2.52
64	CUSA	Tulsa	7	4	62	63	613	828	0.4725	2.56
65	ACC	Virginia	5	7	58	68	730	746	0.4717	2.60
66	MtnWest	San Diego State	3	9	59	60	599	817	0.4715	2.64
67	CUSA	Southern Miss	7	5	64	71	731	854	0.4698	2.68
68	Big12	Colorado	2	10	56	62	652	765	0.4698	2.72
69	WAC	Fresno State	4	8	59	66	696	804	0.4693	2.76
70	Big12	Kansas State	6	5	55	62	655	753	0.4685	2.80
71	Big12	Iowa State	3	8	55	63	660	744	0.4674	2.84
72	MAC	Central Michigan	9	4	65	74	765	877	0.4670	2.88
73	Big10	Purdue	7	5	62	75	759	790	0.4650	2.92
74	ACC	Wake Forest	10	2	58	72	774	770	0.4645	2.96
75	BigEast	South Florida	7	4	53	64	680	726	0.4632	3.00
76	CUSA	UCF	3	8	57	65	657	789	0.4629	3.04
77	MtnWest	Brigham Young	10	2	57	68	698	772	0.4623	3.08
78	Indy	Army	2	9	59	67	622	785	0.4595	3.12
79	MtnWest	Utah	6	5	56	66	648	788	0.4564	3.16
80	WAC	Louisiana Tech	2	10	62	71	680	890	0.4552	3.20
81	MAC	Miami (OH)	2	10	65	77	688	845	0.4548	3.24
82	MtnWest	Wyoming	6	6	57	70	684	784	0.4545	3.28
83	CUSA	East Carolina	7	5	56	68	680	800	0.4542	3.32
84	Big10	Wisconsin	10	1	53	70	706	726	0.4516	3.36
85	MAC	Eastern Michigan	1	11	60	69	640	874	0.4510	3.40
86	MAC	Ball State	5	7	55	66	662	838	0.4501	3.44
87	SunBelt	Middle Tennessee	6	5	57	66	601	820	0.4499	3.48
88	CUSA	UAB	3	9	56	70	683	810	0.4488	3.52
89	WAC	Boise State	11	0	56	67	630	824	0.4480	3.56
90	MtnWest	UNLV	1	10	57	69	610	808	0.4450	3.60
91	CUSA	Houston	9	3	58	75	706	860	0.4410	3.64
92	CUSA	Southern Methodist	5	6	55	68	619	835	0.4400	3.68
93	WAC	Hawaii	9	3	57	73	696	906	0.4371	3.72
94	WAC	Idaho	3	8	54	72	648	810	0.4339	3.76
95	MtnWest	New Mexico	6	6	51	67	625	814	0.4329	3.80
96	Big12	Kansas	5	6	50	69	641	767	0.4319	3.84
97	MAC	Akron	5	7	54	75	691	834	0.4301	3.88
98	CUSA	Memphis	1	10	53	72	634	805	0.4295	3.92
99	CUSA	Marshall	4	7	52	73	645	777	0.4285	3.96
100	MAC	Ohio	8	4	56	75	696	925	0.4281	4.00
101	MAC	Western Michigan	8	4	53	78	709	823	0.4240	4.04
102	CUSA	UTEP	5	7	50	75	674	808	0.4183	4.08
103	MAC	Northern Illinois	6	5	52	78	670	806	0.4180	4.12
104	MtnWest	Colorado State	3	8	51	74	617	797	0.4175	4.16
105	MtnWest	TCU	9	2	48	72	636	770	0.4174	4.20
106	MAC	Bowling Green	4	8	52	79	687	851	0.4135	4.24
107	WAC	Nevada	8	4	49	75	670	822	0.4131	4.28
108	SunBelt	Florida International	0	12	50	74	631	840	0.4118	4.32
109	MAC	Toledo	4	7	50	72	604	865	0.4103	4.36
110	SunBelt	Louisiana-Monroe	3	8	48	72	596	834	0.4056	4.40
111	WAC	San Jose State	7	4	46	76	661	781	0.4042	4.44
112	SunBelt	North Texas	3	9	48	76	642	839	0.4026	4.48
113	SunBelt	Louisiana-Lafayette	5	6	50	77	590	830	0.4010	4.52
114	Indy	Navy	8	3	42	76	703	737	0.4000	4.56
115	SunBelt	Florida Atlantic	4	7	47	75	601	799	0.3999	4.60
116	SunBelt	Troy	6	5	47	76	607	828	0.3957	4.64
117	WAC	New Mexico State	2	8	48	76	565	822	0.3938	4.68
118	SunBelt	Arkansas State	6	6	44	79	646	831	0.3843	4.72
119	MAC	Kent State	6	6	42	86	709	810	0.3743	4.76

So we've got USC, Michigan, Stanford (who played 8-4 San Jose St, 9-3 Navy, and 10-2 Notre Dame), and Florida in 4th. Many people have been saying that Florida's schedule was the toughest in the country this year, mainly because they think the SEC was the toughest conference. I'm not saying that these standings disprove that (mainly because I don't think this "2/3 + 1/3" is very accurate), but the argument against them can be made.

Let's look at what Florida's SoS would have been had they not played 2-9 Western Carolina in the second to last week...

Rank	Conf.	Team	W	L	oW	oL	ooW	ooL	SoS%	Q-Pts
1	SEC	Florida	11	1	81	46	788	710	0.6005	0.04
2	Pac10	USC	10	2	77	51	823	694	0.5819	0.08
3	Big10	Michigan	11	1	78	50	746	724	0.5754	0.12
4	Pac10	Stanford	1	11	75	51	782	711	0.5714	0.16
5	Pac10	UCLA	7	5	73	54	807	694	0.5624	0.20

(For easy visual reference, here's the top 5 from above with Western Carolina included.)

Rank	Conf.	Team	W	L	oW	oL	ooW	ooL	SoS%	Q-Pts
1	Pac10	USC	10	2	77	51	823	694	0.5819	0.04
2	Big10	Michigan	11	1	78	50	746	724	0.5754	0.08
3	Pac10	Stanford	1	11	75	51	782	711	0.5714	0.12
4	SEC	Florida	11	1	81	55	799	767	0.5671	0.16
5	Pac10	UCLA	7	5	73	54	807	694	0.5624	0.20

My, my. If Florida would have just not played Western Carolina and gone 11-1, they would have jumped from 4th to 1st in the SoS. Their Opponent's Wins didn't go up at all (because Western Carolina didn't have any wins against D1-A opponents). Their Opponent's Losses would have dropped from 55 to 46, and while their ooW would have dropped from 799 to 788, their ooL would have plummeted from 767 to 710 (since Western Carolina's oW-oL was 11-57). Quite interesting...