Update: Nov 12, 2014: Wow, this got that TCU would be in the top 4 instead of Bama -- so far 2/2 in predicting the top 4 right every time!

Update: December 10, 2017: Well, after 3 years of spot on predictions, the model failed for 2017. The model did not call for Alabama over Ohio State, it did not even call for Ohio State... It called for a 3-loss Auburn to reach the final 4. For 2018 I am going to tweak the model to use something like margin of victory to hopefully converge on better mathematical rankings earlier in the season.

A positive rating bias indicates the committee places more value in a team than the computer would indicate and a negative rating bias indicates the committee places less value on a team than the computer indicates.

Each week the rating biases are computed for each team, and the average rating bias across all weeks is used for the next week's calculation. As long as the ratings biases do not materially change during the course of a season (for example, a single team has a high bias, but maintains that same bias week after week) then the method will very effectively predict the committee's actions.

Hey, this is the world of big data. If Google can predict what you are thinking before you think it, the method can predict the committee's output before the committee states it.

After Appalachian State beat a highly ranked Michigan in Ann Arbor in 2007, the Colley Matrix method was extended to "groups" of FCS teams. The net result is the FCS teams had a rating approximately equal to the worst FBS teams, and the matrix accounted for these games in a way that has a high accuracy to the human polls. The modification made by playoffPredictor.com is to account all FCS teams as a single team. That keeps the matrix much "purer" and the math much simpler than a calculated number of FCS groups. At the end of the season this single FCS team will have a record of something like 8 wins and 80 losses against all FBS opponents, giving the FCS schools a very low rating, significantly below the rating of even the worst FBS teams. To me, that's the right way to calculate it. You should be penalized heavily for scheduling an FCS team, and if you actually lose to an FCS team you should be severely penalized.

So, the true computer ratings given on this site are based on the Colley Matrix with all FCS teams grouped into a single team.

In addition, starting with the 2018 season the computer rankings are modified to include margin of victory. More details on that in this blog post.