Ballot Type: Human
Submitted: Aug. 18, 2019, 4:40 p.m.
Overall Rationale: Each season, I use a self-contained computer model to generate rankings. It looks only as far back as the beginning of the season, and only as far forward as the end of it. Because the only data the model has are games that have been played already, it will take several weeks to converge. For the preseason, and for weeks 0-3, I will use my own opinions instead of the model's results, because I expect the model to be nonsense. During weeks 4-8, I will tweak the model's results slightly, according to my own personal opinions, and at this time I will change my ballot type from "human" to "hybrid". Through this time, the size of tweak I can make to a particular team's model score will decrease steadily, until it disappears completely. By week 9 and later, I will be using exclusively the model's scores, with no human input. Fundamentally, the model is based on strength of schedule, scoring margins, and opponent-adjusted scoring performance. This year, I have included FCS teams as well as FBS teams. I will no longer treat every FCS opponent as equal in value for an FBS team; instead, I will treat every D2 opponent as equal in value for a D1 team, regardless of the D2 team's record or performance. At this time, I do plan to adjust the value of an FCS opponent downward compared to an FBS opponent. I may change this decision during the season, depending on how the results look by week 7 or 8. The expected effect is that, for an FBS team, one or more FCS opponents makes their schedule weaker than playing an FBS opponent with a similar record; while for an FCS team, playing one or more FBS opponents makes their schedule stronger than playing FCS opponents with similar records. I will definitely adjust the value of an FCS opponent, compared to an FBS opponent, so that FBS and FCS teams ranked around the same place by the model are worth approximately the same value. On to The Process. The base value of a game against an opponent, regardless of when the game happened, is that opponent's current record. The largest single adjustment to the base value is the result of the game: a win results in a large boost, a loss results in a large penalty, a game in the future has no change, and a cancellation removes the game from the schedule entirely (which almost always acts as a penalty). Other considerable adjustments include the scoring margin (capped at 25), the relative scoring performance compared to the opponent's other games, the game's location, and the discrepancy between the participants' model scores. Because the model essentially starts from scratch each week, but with an additional week of game data, and intrinsically depends on how opponents are assessed by the model, it is necessary to use the model's results to re-run the model again. The model runs to convergence - when the difference between the previous iteration's score and the current iteration's score are very small, for all 257 D1 teams. It frequently occurs that the iterations will become stuck in a repeating loop, usually two iterations long, and that one or more pairs of teams will trade places on each iteration. Because this requires two teams' scores to be very close, and scores among the top 25 tend to be at least a few points apart, it almost never affects the actual results I will post here. If it does, I will make a note of it, although the format of this poll requires me to put one team above the other. The model is intended to estimate a team's current status, which is why it uses a blend of backward-looking and forward-looking data, weighted heavily toward history. As a final note, I take this preseason ballot seriously, and these are my honest personal opinions on the current status of FBS football teams.
Rank | Team | Reason |
---|---|---|
1 | Clemson Tigers | |
2 | LSU Tigers | It's now or never. |
3 | Michigan Wolverines | |
4 | Alabama Crimson Tide | |
5 | Ohio State Buckeyes | Day takes the helm of a ship on course. |
6 | Georgia Bulldogs | |
7 | Notre Dame Fighting Irish | |
8 | Oklahoma Sooners | Injuries in camp are trouble for the 129th-ranked pass defense. |
9 | Texas A&M Aggies | Their best year in a while will be good for a distant third in the division. |
10 | Washington Huskies | |
11 | Iowa State Cyclones | Frightening development, whirlwind receiver speed, and shrewd coaching. |
12 | Army West Point | 10 wins should be a floor, not a ceiling. |
13 | Cincinnati Bearcats | The pieces are in place. |
14 | Texas Longhorns | |
15 | South Carolina Gamecocks | |
16 | Penn State Nittany Lions | It's not that they won't regress, it's that others will regress further. |
17 | UCF Knights | Their QBs should look into steel leg implants. |
18 | Stanford Cardinal | #2 in the division. |
19 | Florida Gators | |
20 | Utah Utes | |
21 | Mississippi State Bulldogs | |
22 | Boise State Broncos | I'll admit, this one is a bit of a crutch because they're always in the mix. |
23 | Oregon Ducks | |
24 | Iowa Hawkeyes | The annual sacrifice to... wait a second, Ohio State isn't winning the East? |
25 | Ohio Bobcats | Scary talent and good use of it should take the MAC by surprise. |
Teams Ranked:
Rank | Team | Unusualness |
---|---|---|
1 | Clemson Tigers | 0.00 |
2 | LSU Tigers | 1.19 |
3 | Michigan Wolverines | 0.84 |
4 | Alabama Crimson Tide | -1.35 |
5 | Ohio State Buckeyes | 0.00 |
6 | Georgia Bulldogs | -0.67 |
7 | Notre Dame Fighting Irish | 0.00 |
8 | Oklahoma Sooners | -1.83 |
9 | Texas A&M Aggies | 0.47 |
10 | Washington Huskies | 0.00 |
11 | Iowa State Cyclones | 1.90 |
12 | Army West Point | 3.35 |
13 | Cincinnati Bearcats | 5.87 |
14 | Texas Longhorns | -0.16 |
15 | South Carolina Gamecocks | 9.65 |
16 | Penn State Nittany Lions | 0.00 |
17 | UCF Knights | 0.00 |
18 | Stanford Cardinal | 1.12 |
19 | Florida Gators | -1.80 |
20 | Utah Utes | -0.28 |
21 | Mississippi State Bulldogs | 0.67 |
22 | Boise State Broncos | 0.00 |
23 | Oregon Ducks | -1.56 |
24 | Iowa Hawkeyes | -0.10 |
25 | Ohio Bobcats | 0.22 |
Omissions:
Team | Unusualness |
---|---|
Auburn Tigers | 1.25 |
Wisconsin Badgers | 0.61 |
Washington State Cougars | 0.24 |
Syracuse Orange | 0.36 |
Michigan State Spartans | 0.41 |
Total Score: 35.90