Last year I used what I called a "surprise factor" to assign a weight to "upsets" according to the various rating systems. I never really liked the weighting I used in the Weighted Retrodictive Ranking Violation report, because the weights tended to zero too quickly. An upset of #25 only contributed .04 × ΔScore×ΔRank.
During the college baseball season I finally got around to defining an improvement, using these criteria:
The improved calculation is:
 

For FBS football with 120 teams, N=25 seems a logical choice, and the resulting weightings by loser's rank look like this:
With the new calculation, the WRRV for 2007 looks like this. Be careful with the interpretations, QPR is only "best" by this metric because it only ranks 50 teams.
Top 10 Games for 28 Aug1 Sep  

To find the most interesting games, just use Game Interest = (M+1−MAX(R1,R2))×ƒ(R1,R2) (where M is the number of ranked teams  in all of this, M+1 is the rank assigned to any unranked team.)
The coefficient (M+1)(rank of lowerrated team) just gives a multiplier of 1 for the worst team up to 120 (for D1A) for a game involving the #1 team. The highest value for a regularseason game in 2008 based upon 2007 rankings is 1086.9 for #4 Georgia at #1 LSU. In fact, the top 9 are all games involving LSU, but this is ok  games involving the #1 are inherently of interest. Even if the opponent's rank is really bad, the game is interesting because an upset would be a really big one.
For the first weekend, the algorithm gives these as the top 10 games.
If strikes me that if we choose N so that playing the team ranked last counts as close to ½ as we can get we can define another reasonable measure of schedule strength. The derivation of that will come in another essay.