Envision life
Adjustments once again to the division power and conference strengths as well as a top four upset resulted in some shifting of the rankings for the last week of the regular season.
| Rank | Team |
|---|---|
| 1 | Ohio State |
| 2 | Indiana |
| 3 | Texas Tech |
| 4 | Notre Dame |
| 5 | BYU |
| 6 | Oregon |
| 7 | Georgia |
| 8 | Utah |
| 9 | Texas A&M |
| 10 | UConn |
| 11 | Ole Miss |
| 12 | Arizona |
| 13 | Vanderbilt |
| 14 | Alabama |
| 15 | Miami |
| 16 | Oklahoma |
| 17 | North Texas |
| 18 | USC |
| 19 | James Madison |
| 20 | Iowa |
| 21 | Michigan |
| 22 | South Florida |
| 23 | Houston |
| 24 | Tennessee |
| 25 | Texas |
Several out-of-conference games last week shifted the conference strengths around a bit which resulted in different starting ratings for the teams. That translated downstream to some shifts in the rankings this week, notably Texas Tech ranking 4th this week, down from 1st the last few weeks.
| Rank | Team |
|---|---|
| 1 | Ohio State |
| 2 | Indiana |
| 3 | Texas A&M |
| 4 | Texas Tech |
| 5 | Notre Dame |
| 6 | Georgia |
| 7 | Ole Miss |
| 8 | Oregon |
| 9 | UConn |
| 10 | Alabama |
| 11 | Oklahoma |
| 12 | Vanderbilt |
| 13 | BYU |
| 14 | Utah |
| 15 | Tennessee |
| 16 | Arizona |
| 17 | Michigan |
| 18 | Miami |
| 19 | Texas |
| 20 | Washington |
| 21 | USC |
| 22 | North Texas |
| 23 | James Madison |
| 24 | Missouri |
| 25 | Iowa |
Rankings after the November 15 games.
| Rank | Team |
|---|---|
| 1 | Texas Tech |
| 2 | Ohio State |
| 3 | Indiana |
| 4 | Texas A&M |
| 5 | Ole Miss |
| 6 | Georgia |
| 7 | Notre Dame |
| 8 | BYU |
| 9 | Utah |
| 10 | Oregon |
| 11 | UConn |
| 12 | Oklahoma |
| 13 | Vanderbilt |
| 14 | Alabama |
| 15 | Arizona |
| 16 | Tennessee |
| 17 | USC |
| 18 | Missouri |
| 19 | Houston |
| 20 | Miami |
| 21 | Michigan |
| 22 | North Texas |
| 23 | Texas |
| 24 | Cincinnati |
| 25 | James Madison |
Today we will get the second installment of the College Football Playoff committee’s rankings. Theirs will likely be wrong. That’s okay. Here is mine based on my algorithm. It is probably also wrong, but that is okay. I think it is close. This is just the math, no bias or emotion from me.
| Rank | Team |
|---|---|
| 1 | Texas Tech |
| 2 | Ohio State |
| 3 | Indiana |
| 4 | Texas A&M |
| 5 | Ole Miss |
| 6 | Alabama |
| 7 | Georgia |
| 8 | Notre Dame |
| 9 | BYU |
| 10 | Vanderbilt |
| 11 | Utah |
| 12 | UConn |
| 13 | Oklahoma |
| 14 | Oregon |
| 15 | Texas |
| 16 | Arizona |
| 17 | USC |
| 18 | Tennessee |
| 19 | Houston |
| 20 | Cincinnati |
| 21 | Pittsburgh |
| 22 | Miami |
| 23 | Michigan |
| 24 | Missouri |
| 25 | Iowa |
You make like or despise or completely not care about the College Football Playoff committee rankings. I have an interest and am curious about how “right” they get things. (There is a serious contention that they don’t care about getting it right, just about creating profitable matchups in the post-season.)
I have my own method to rank teams. I use a modified Elo ranking system which is non-discrete. The system considers strength of schedule, home field advantage, and point spreads up to 19 points (because anything beyond that is functionally meaningless). The system first ranks the FBS, FCS, Division II and Division III divisions based on cross-division games. The system then ranks the conferences, using the division rankings as the starting points, based on cross-conference games. The system then ranks the teams, using the conference rankings as the starting points, based on all games.
Disclaimer: I am a BYU fan. I have thought all season that BYU should be ranked above Miami and Boise State. You can see that my math does not agree with me. Here are the rankings based on my system.
| Rank | Team |
|---|---|
| 1 | Oregon |
| 2 | Indiana |
| 3 | Ole Miss |
| 4 | Texas |
| 5 | Georgia |
| 6 | South Carolina |
| 7 | Notre Dame |
| 8 | Tennessee |
| 9 | Alabama |
| 10 | Florida |
| 11 | Miami |
| 12 | Ohio State |
| 13 | LSU |
| 14 | Army |
| 15 | Arizona State |
| 16 | Penn State |
| 17 | Missouri |
| 18 | Texas A&M |
| 19 | Memphis |
| 20 | Kansas State |
| 21 | BYU |
| 22 | Vanderbilt |
| 23 | Minnesota |
| 24 | Clemson |
| 25 | Iowa |
With the World Cup starting this week, I had to create the obligatory probability models. I’ve used the FIFA ratings as my starting point, adjusted for geographical differences in travelling to Russia, and crunched the numbers. I get the follow for the top five teams and their associated probability of winning the championship.
| Team | p |
|---|---|
| Germany | 6.8% |
| Portugal | 4.9% |
| Belgium | 4.4% |
| Brazil | 4.2% |
| France | 3.5% |
Interestingly, the percentages here give Portugal a slight edge over Belgium, even though Belgium is ranked higher in the FIFA rankings. This has to do with the first round groupings and the way the bracket gets structured. Even though they are the higher ranked team, Belgium’s path to the championship likely goes through more difficult teams than Portugal’s path. Even so, what should be very apparent is that any team’s path is difficult as evidenced by the favorite’s probability sitting at only 6.8%.
Worth noting is the presence of only one South American team among the model’s favorites. Going into the World Cup, Brazil is ranked second in the world. However, the historical data suggests that South American teams will under perform in Europe (and yes, I am counting Russia as geographically Europe for this World Cup). Applying a 10% deduction to the South American teams, the model takes both Brazil and Argentina out of the tournament in the quarterfinals matches.
Most probable results:
| 1st place | Germany |
| 2nd place | Belgium |
| 3rd place | Portugal |
