College Football Computer Rankings: January 2011

Tuesday, January 11, 2011

2010 Final Rankings

1 AUBURN 13.407
2 OREGON 12.421
3 STANFORD 11.682
4 TCU 11.054
5 BOISE ST 10.233
6 OHIO STATE 9.672
7 VIRGINIA TECH 9.357
8 ALABAMA 9.163
9 LSU 8.091
10 ARKANSAS 7.863
11 OKLAHOMA ST 7.814
12 OKLAHOMA 7.762
13 WISCONSIN 7.725
14 NEVADA 7.228
15 MISSOURI 6.991
16 MICHIGAN ST 6.305
17 FLORIDA ST 6.164
18 SOUTH CAROLINA 5.843
19 NEBRASKA 5.554
20 TEXAS A&M 5.061
21 NORTH CAROLINA ST 4.570
22 NOTRE DAME 4.356
23 IOWA 3.954
24 MISSISSIPPI ST 3.860
25 FLORIDA 3.735
26 AIR FORCE 3.485
27 WEST VIRGINIA 3.462
28 UTAH 3.410
29 SOUTHERN CAL 3.389
30 SAN DIEGO ST 2.785
31 PITTSBURGH 2.665
32 CENTRAL FLORIDA 2.562
33 NORTHERN ILLINOIS 2.487
34 ARIZONA 2.458
35 NAVY 2.250
36 ILLINOIS 2.232
37 MARYLAND 2.105
38 HAWAI`I 1.991
39 MIAMI FL 1.959
40 ARIZONA ST 1.897
41 TULSA 1.718
42 CLEMSON 1.533
43 GEORGIA 1.328
44 NORTH CAROLINA 1.240
45 WASHINGTON 1.185
46 PENN STATE 1.126
47 SOUTHERN MISS 1.035
48 OREGON ST 1.024
49 CALIFORNIA 0.997
50 KANSAS ST 0.707
51 BOSTON COLLEGE 0.592
52 MICHIGAN 0.498
53 TEXAS TECH 0.449
54 TENNESSEE 0.234
55 IOWA ST 0.180
56 FRESNO ST 0.157
57 COLORADO 0.120
58 TOLEDO -0.049
59 BAYLOR -0.052
60 LOUISVILLE -0.062
61 BRIGHAM YOUNG -0.104
62 TEXAS -0.260
63 SOUTH FLORIDA -0.262
64 KENTUCKY -0.343
65 CONNECTICUT -0.435
66 GEORGIA TECH -0.725
67 MIAMI OH -0.781
68 MISSISSIPPI -0.784
69 SMU -0.833
70 TROY -0.928
71 TEMPLE -1.036
72 UCLA -1.071
73 SYRACUSE -1.171
74 ARMY -1.192
75 OHIO U. -1.242
76 LOUISIANA-MONROE -1.350
77 NORTHWESTERN -1.426
78 FLORIDA INT'L -1.513
79 IDAHO -1.557
80 EAST CAROLINA -1.796
81 WESTERN MICHIGAN -1.893
82 INDIANA -2.318
83 HOUSTON -2.374
84 PURDUE -2.402
85 MINNESOTA -2.639
86 CINCINNATI -2.763
87 WAKE FOREST -3.210
88 MARSHALL -3.452
89 ARKANSAS ST -3.544
90 UTEP -3.626
91 VIRGINIA -3.813
92 DUKE -3.996
93 KANSAS -4.104
94 LOUISIANA-LAFAYETTE -4.143
95 ALABAMA-BIRMINGHAM -4.304
96 KENT ST -4.407
97 RUTGERS -4.497
98 WASHINGTON ST -4.727
99 UTAH ST -4.759
100 WYOMING -4.920
101 COLORADO ST -5.306
102 MIDDLE TENNESSEE ST -5.358
103 CENTRAL MICHIGAN -5.755
104 VANDERBILT -5.833
105 RICE -6.390
106 BALL ST -6.463
107 UNLV -6.736
108 NORTH TEXAS -7.204
109 FLORIDA ATLANTIC -7.279
110 TULANE -8.039
111 SAN JOSé ST -8.062
112 BOWLING GREEN -8.147
113 LOUISIANA TECH -8.588
114 WESTERN KENTUCKY -9.302
115 NEW MEXICO ST -9.955
116 NEW MEXICO -10.366
117 EASTERN MICHIGAN -10.647
118 MEMPHIS -11.872
119 AKRON -12.955
120 BUFFALO -13.704

Description of Ratings System

My goal was to devise a system that relied exclusively on simple mathematical calculations without any built-in biases. This ranking system is based solely on the resulting score of the games played to date of the current season and the teams win-loss record. I will briefly cover some of my thoughts and philosophies while developing the system in the following.
After analyzing game statistics I concluded that the final score of a game is an all encompassing summary of the statistics. For example, if a team outgained an opponent by 200 yards of offense but still lost the game, the loss was usually due to turnovers or penalties. I started by developing a system that would record and determine the average margin of victory (AMV) for a team. A system based on this alone has obvious flaws due to teams winning by large margins over lesser opponents. After crunching data with various limitations on margin of victories, I decided to limit the margin of victory to a maximum of 21 points. However, this still allowed teams that play weak opponents to remain high in the rankings. To penalize teams that play weak opponents and give credit to teams that play strong opponents, I then added the team’s opponents’ average margin of victory (OAMV) and their opponent’s opponents’ average margin of victory (OOAMV) to their AMV. This process is carried out 5 times (OOOOOAMV) which mathematically relates every team to each other by the end of the season. This effectively lowered the teams rankings that had a high AMV due to playing weak opponents. However, this allowed teams with high AMVs and multiple losses to be ranked higher than no-loss or one-loss teams at the end of the season. I factored in the win-loss record by lowering the final result of a team with a positive ranking value by the ratio of the team’s losses over the total games played and raising the final result of a team with negative ranking value by the ratio of the team’s wins over the total games played.
To illustrate this more clearly, I will use a couple of examples.
As of week 6 of the 2000 season, TCU had the highest margin of victory of the 115 Division 1-A teams at 26.750. However, their opponents AMV was -12.400 indicating that TCU has played weak teams but have outscored these teams by a larger margin than the other opponents of these teams. Summing the AMV and the OAMV reduces their ranking value to 14.350. Carrying this process out 5 times (OOOOOAMV) results in a ranking value of 21.623. TCU is currently undefeated (4-0) so 21.623 is their final ranking value. This places TCU 4th out of 115 teams.
As of week 6 of the 2000 season, Texas A&M’s AMV is 15.000 and their opponents’ AMV was 0.438. Summing these two numbers increases their ranking value to 15.438. Carrying this process out 5 times (OOOOOAMV) results in a ranking value of 16.284. Texas A&M has played four 1-A opponents and their win-loss record is 3-1. Since Texas A&M has a positive ranking value they are penalized for the game they lost by reducing their result by the total number of games they have lost divided by the games played, or 25%. This result is 12.213 which places them 13th out of 115 teams. If Texas A&M wins their game in week 7 their record will then be 4-1 and their final result will be reduced by only 20%. This will enable them to possibly move up in the rankings by continuing to win games, similar to what would be seen in the AP or Coaches poll.
Additional comments:
The results from previous years have no effect on this years rankings. I feel that the two years are independent from each other. This causes some anomalies early in the season but everything settles out after week 6 or 7. I believe this is also why the BCS does not publish their rankings until late October although some ranking systems carry over from the previous year.
This system only uses the 120 Division 1-A teams. Any team that plays a team from another division receives no credit for the win. There can be a slight penalty for playing a team outside of Division 1-A. For instance, a team that has a victory over a 1-AA opponent does not receive credit for that victory in the win column. If their actual record is 7-2 this would be recorded as 6-2, therefore the penalty for the 2 losses would be 25% instead of 22.2 %. Likewise, losing to a 1-AA opponent would not be recorded in the loss column but this rarely happens.
This system is simple compared to some of the other systems being used but the results similar. I would welcome any comments or questions from anyone. I can be contacted at smaurer@kc.rr.com
Scott

College Football Computer Rankings

Tuesday, January 11, 2011

2010 Final Rankings

Description of Ratings System

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