A few years ago an SEBaseball.com subscriber suggested that I create a report for D1 Baseball similar to the one the NCAA uses to select and seed the Hockey tournament. The idea is pretty simple:
Although such a report is most useful in sports with a requirement to select and seed a tournament, nothing prevents us from creating one for FBS football. I wouldn't use it by itself to characterize teams' resumes, but for any two teams the reports provide relevant data that is otherwise hard (or at least inconvenient) to obtain.
After week 7, there are 81 such teams. In other sports we'd add a second criterion: "ranked in the top N or leading their conference" because in other sports there's an NCAA-specified computer ranking and conference champions get automatic bids regardless of record.
For FBS football there's no tournament with automatic bids, so we don't need the "leading their conference" criterion, and there's no pre-defined computer rating equivalent to baseball (/hockey/basketball) RPI. However, there's a good reason to include the "rank ≤ N" criterion: if weak teams are included in the field, the "wins vs teams under consideration" criterion we'd like to use would give too much weight to teams with wins over teams that are ≥ .500 only because they've played really bad teams other than this one.
So I add to the criteria list for field definition: "ranked in the top half of FBS." Which begs the question "ranked how?" In the absence of an official rating system (not even the BCS considers any version of the RPI for football, for good reasons) by default I use the Majority Consensus rank for the Computer Ranking Comparison maintained by Kenneth Massey.
If we let WW = #pairwise wins, LL = #pairwise losses, and TT = #pairwise ties, then we can define a "pairwise winning percentage" in the usual way:
|PW% = (WW+TT/2) ÷ (WW+LL+TT)|
Pairwise winning percentage is not likely to distinguish all teams in the "field." As a tiebreaker we can use the difference in total pairwise points (P) between each team ti and every other team tj. If we call the pairwise score of team x vs team y P(tx,ty), we can sum scores over all pairs by:
|*j ≠ i|
Of course, this is only one of many possible results analyses, but it is an especially useful one since it makes visible the comparisons that lead to the ranking. For each team, the comparison to every other team under consideration is provided.
For the 2009 report, see Pairwise Ratings - FBS.