One problem with using wins between teams as "votes" is that in this case the "voters" are the games played, so an A>B voter is different from a C>D voter and no "voter" ranks more than 2 alternatives. It's as good as a way as any to put random numbers into a pairwise matrix, but it's a lot faster to just generate 100*R and 100*(1-R) if you've got a computer.
But here's a source for ranked ballots that could be used to model any system. Kenneth Massey has collected up nearly 100 polls and ranking systems for American College Football. Each of these is a "ranked ballot" that orders (possibly a subset) of the 117 teams in division 1A. On this page the "voters" are listed across the top, and the candidates down the side. The data as it exists is not very interesting, because there's really not that much disagreement at the top and bottom of the ballot, since even though all of the "voters" have different weights for "issues" (margin of victory versus opponents' winning percentage, etc) they all have the same goal of picking the most dominant team, which is by definition likely to be very highly rated in "issue" that is relevant. However, if you threw out all the options that appeared on any voters top 10, I think you'd have a pretty good set of data to test against various alternatives (and lots of cycles and sub-cycles). His site is at http://www.mratings.com/cf/compare.htm ---- Election-methods mailing list - see http://electorama.com/em for list info
