Name
Strength of Schedule
Combined Ranks
Average Game Score
Losses
Total
• Name
The University/School’s name, (EX: Ohio State, Oklahoma, Miami (FL), and Texas.)
• Strength of Schedule
Here is the first of 3 formulas in my BCS. This is the most difficult equation for me to keep track of. I have even made this formula more complex this year. I believe that the best way to describe these formulas is just to give examples of them. But first I must say that I used Richard Billingsley’s rankings (www.cfrc.com for more information) for this formula. (EX: Ohio State plays the 18, 28, 38, 48, 58, 68, 78 and 88 best teams for the entire season. Then I would average those numbers. That average is 53. Say their average margin of victory over these opponents is +13.0.
13.0 divide by 10 = 1.3
53 – 1.3 = 51.7
51.7 divide by 10 = 5.17
So Ohio State would then get a 5.17 for their strength of schedule.) (Example 2: Akron plays the 10, 20, 30, 40, 50, 60, 70, 80, 90, 100 and 110th best teams for the entire season. Then I would average those numbers. That average is 60. Say their average margin of victory over these opponents is +2.0
2.0 divide by 10 = 0.2
60 – 0.2 = 59.8
59.8 divide by 10 = 5.98
So Akron would then get a 5.98 for their strength of schedule.)
• Combined Ranks
This is the second formula included in my BCS. This also is the easiest formula in my BCS. However I have tweaked this formula from 2004 to 2005. For this formula I use five different rankings. For weeks #1 through #8 I use Richard Billingsley’s ranking of all 119 teams, James Howell’s rankings of all 119 teams and Kenneth Massey’s ranking of all 119 teams; Say Ohio State gets these ranks from the respective rankings:
3 (Billingsley)
4 (Howell)
3 (Massey)
Average 3, 4, 3, and Ohio State would get a 3.667.
• Average Game Score
Here is the 3rd and final formula inside of my BCS. However this is the most complicated of all of them. I just created this formula three weeks into the 2004 season. However this formula is not the same as last years. I have tweaked this formula a little bit so it makes more of an impact in the overall total. I will try to explain this to you as well as I can but this is very complicated so I will just do the best I can.
Wins:
Win Win Win Win
1-40 41-80 81-120 121-lower
-1.8 -1.2 -0.8 -0.4
This graph here shows the basic formula for a victory. You get -1.8 for beating a team ranked (in Richard Billingsley’s rankings) 1-40. You get -1.2 for beating a team ranked 41-80. You get -0.8 for beating a team 81-120. Finally you get -0.4 for beating a team 121-lower. Note: There are 119 teams in Division 1-A, so all but the #1 of Div 1-AA is in the 4th tier of a victory. When you beat a team that was higher ranked then you, you subtract 0.03 for every space that they were higher than you. When you beat a team lower ranked then you, you add 0.005 to every space that were lower ranked then you.
(EX1: The then ranked 45th best team beats the then ranked 5th best team. This is how that game would be scored for the 45th best team:
-1.6 (for beating a team ranked 1-40)
+ -1.2 (for beating a team ranked 40 spaces higher than they were. -0.03 x 40 = -0.8)
= -2.8 (their game score for this game.))
(EX2: The then ranked 10th best team beats the then ranked 20th best team. This is how that game would be score for the 10th best team:
-1.6 (for beating a team ranked 1-40)
+ 0.05 (for beating a team ranked 10 spaces lower than they were. 0.005 x 10 = 0.05)
= -1.55 (their game score for this game.))
(EX3: The then ranked 1st best team beats the then ranked 65th best team. This is how that game would be scored for the 1st best team:
-1.0(for beating a team ranked 41-80)
+ 0.32 (for beating a team ranked 64 spaces lower than they were. 0.005 x 64 = 0.32.)
= -0.68 (their game score for this game.))
(EX4: The then ranked 125th best team (8th best in Div. 1-AA) beats the then ranked 75th best team. This is how that game would be scored for the 125th best team:
-1.0(for beating a team ranked 41-80)
+ -1.5(for beating a team ranked 50 spaces higher than they were. -0.03 x 50 = -1.0)
= -2.5 (their score for this game)
Losses:
Loss Loss Loss Loss
1-40 41-80 81-120 121-lower
0.8 1.6 2.4 4.0
This graph here shows the basic formula for a loss. You get 0.8 for losing to a team ranked 1-40. You get 1.6 for losing to a team ranked 41-80. You get 2.4 for losing to a team ranked 81-120. Finally you get 4.0 for beating a team ranked 121-lower. When you lose to a team that was lower ranked then you, you add 0.03 for every space that they were lower ranked then you. When you lose to a team higher ranked then you, you subtract 0.005 to every space that they were higher than you.
(EX1: The then ranked 5th best team loses to the then ranked 45th best team. This is how that game would be scored for the 5th best team:
1.6(for losing to a team ranked 41-80)
+ 1.2(for losing to a team ranked 40 spaces lower than they were. 0.03 x 40 = 1.2.)
= 2.8(their game score for this game)
(EX2: The then ranked 20th best team loses to the then ranked 10th best team. This is how that game would be scored for the 20th best team.
0.8(for losing to a team ranked 1-40)
+ -0.05(for losing to a team ranked 10 spaces higher than they were. -0.005 x 10 = -0.05.)
= 0.75(their game score for this game)
(EX3: The then ranked 65th best team loses to the then ranked 1st best team. This is how that game would be scored for the 65th best team.
0.8(for losing to a team ranked 1-40)
+ -0.32 (for losing to a team ranked 64 spaces higher than they were. -0.005 x 64 = -0.32.)
= 0.48 (Their game score for this game)
(EX4: The then ranked 75th best team loses to the then ranked 125th best team (8th best in Div. 1-AA). This is how that game would be scored for the 75th best team.
4.0(for losing to a team ranked 121-lower
+ 1.5(for losing to a team ranked 50 spaces lower than they were. 0.03 x 50 = 1.5.)
= 5.5(their game score for this game)
I then average the teams’ game score for every game so far through the season. Let’s say for example that Ohio State’s average game score is -0.942. Also let’s say that Ohio State’s average margin of victory so far is +13.00
13.00 divide by 100 = 0.13
-0.942 – 0.13 = -1.072
So Ohio State would get a -1.072 for their Average Game Score.
• Losses
The total number of losses for this team. (EX1: Ohio State is 9-3; they get 3.0 for this part of the equation.)(EX2: Texas is 13-0; they get 0.0 for this part of the equation.)(EX3: Akron is 6-5; they get 5.0 for this part of the equation.)
• Total
Here is the total of my BCS equation. All you do for this one is add them up. Add up Strength of Schedule plus Combined Ranks plus Average Game Score (which could be a negative number because good teams usually have many more good games than bad games) plus losses. For this total the team with the lowest amount is the best team in college football. Every week I will be doing a ranking of all 119 teams in Division 1-A. However from the beginning ranking to the ranking on October 3rd (Week 5) I will have to average last season’s average game score and strength of schedule with this season’s average game score and strength of schedule.