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Charlemagne42 Ballot for 2018 Week 4

Ballot Type: Hybrid

Submitted: Sept. 16, 2018, 1:38 p.m.

Overall Rationale: I switched to hybrid last week, but for some reason my ballot wasn't submitted. My model has started to produce some recognizable results, so I'm tweaking them as little as possible to counteract any glaring errors. Of note: I measure the convergence speed of a model by "time to Bama #1". My model's convergence speed was 3 weeks. Let that sink in. It only took 3 weeks for an Excel spreadsheet I spent about two hours coding to recognize Alabama as the best team in college football. _______________________________________ For each team I report 3-4 values. The first is the model's raw score, the second is the bonus or penalty I apply to correct the model, the third is the final score I use to rank the team, and finally I may give some kind of explanation if I think it's needed. For example, for Clemson I might give the reason "348, +20, 368", which means the model gave it a score of 348, I manually added 20 points to correct that score, and 368 is the score I used to rank Clemson. This week I tried not to add or subtract more than 40% of the model's score for each team. The biggest bonus went to Georgia and the biggest penalty went to Indiana. 8 teams got no bonus or penalty. The median absolute value of bonus or penalty was 18 points. ________________________________________ 4 teams had model scores which, if unaltered, would have ranked them. Those teams were: Maryland (311, #9); Hawaii (304, #9); Minnesota (285.5, #9); and Vanderbilt (269, #17). The median bonus or penalty including these four teams was 32.1 points. ______________________________________ Why are Wisconsin and TCU (etc) missing? The model punished them so severely for their losses this week that I can't boost them up into the rankings without punishing all the 15-25 teams unnecessarily. Some of those teams are already pushing the maximum penalty because the model likes them too much. Why is VT (etc) so low? Same reason. They have a 40% bonus already, and teams above them already have a 40% penalty (Indiana). Rest assured, I personally think they belong higher, but if I didn't stick to my own rules, they'd be worthless. Why is BC (etc) so high? When possible, I tried to leave the model's score unchanged. BC is one example. Kentucky and Boise are two more.

Rank Team Reason
1 Alabama Crimson Tide 451, +0, 451
2 LSU Tigers 354, +17, 371
3 Ohio State Buckeyes 370, +0, 370
4 Oklahoma Sooners 286, +69, 355; The Sooners get a somewhat large bonus this week because the model thinks Iowa State is hot garbage. That's simply not true.
5 Georgia Bulldogs 256, +93, 349; UGA comes out with the biggest absolute bonus of the week, pushing the maximum of 40%. Like ISU, the model thinks SCar is bad, and like ISU, SCar has had a weather cancellation, which sets them even further behind than they would otherwise be.
6 Clemson Tigers 348, +0, 348
7 Mississippi State Bulldogs 329, +0, 329
8 Penn State Nittany Lions 385, -59, 326; Penn State gets a moderate penalty because App State still shouldn't have gotten that close. The penalty will keep getting smaller as a fraction of their model score as they keep winning.
9 Stanford Cardinal 285.2, +0, 285.2; I'm excited that 5 of my top 9 needed no modifications at all. It's a good sign that the model is converging quickly to something that makes sense.
10 Notre Dame Fighting Irish 372, -89, 283; Large penalty for playing Ball State too close, and then playing Vanderbilt too close.
11 USF Bulls 262, +14, 276; Why so high? Because they've beaten two P5 teams in two weeks, that's why. What? They were Illinois and GT? Doesn't matter, you'd put Clemson even higher for the same performance. Don't lie. You totally would.
12 Oklahoma State Cowboys 266.2, +7.8, 274; They needed to be slightly higher than the model would have had them, which was a fraction of a point above Boise. They didn't just barely beat Boise, they showed them why they don't play with the big boys.
13 Boston College Eagles 273, +0, 273; Why so high? See the overall rationale.
14 Auburn Tigers 232, +40, 272; A one-point loss on a last-second FG to the #2 team isn't cause for that big of a drop. Bad computer.
15 Washington Huskies 239, +32, 271
16 West Virginia Mountaineers 229, +41, 270; Moderate bonus for the Mountaineers because the model is docking them for not playing this week.
17 Texas A&M Aggies 251, +18, 269; Same as Auburn, close loss to strong team, decent bonus.
18 Kentucky Wildcats 268, +0, 268
19 Boise State Broncos 265.8, +0, 265.8; The model still really likes them even after their loss. Probably because both of their wins also won this week.
20 Indiana Hoosiers 429, -171, 258; Maximum penalty for the Hoosiers. The model likes how FIU and Virginia have one loss: them. What the model isn't considering is how bad FIU and UVA are, and how the teams each has beaten are even worse somehow. Sorry Hoosiers, you aren't almost as good as the Crimson Tide.
21 Duke Blue Devils 403, -146, 257; Same story for Duke. Wins over bad teams who have wins over worse teams. Last week I'd have said Northwestern was a good win, but this week they lost to Akron. Baylor is looking improved, which is the only reason the Blue Devils aren't getting the maximum penalty. Sorry Duke, you aren't almost almost as good as Alabama.
22 Virginia Tech Hokies
23 California Golden Bears 270, -15, 255
24 Army West Point 330, -76, 254; The model loves Hawaii because they've played an extra game and won most of them. So it loves Army for beating Hawaii.
25 BYU Cougars 274, -21, 253; Teams the model would have ranked: Maryland (311), Hawaii (304), Minnesota (285.5), Vanderbilt (269). Next 5 out: Syracuse (252), Buffalo (250), Ole Miss (245, ineligible), Washington State (243), Missouri (242)

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