With Williams and Blum putting out a CF Preseason Ranking, I figured I would start putting together a conference record modeler. Obviously this is just for fun and I don't really think this is indicative of how the season will go. I started with their rankings, O/U from CBS, and the conference schedule. I used that information to create the distribution parameters from which I drew the random numbers that represent how well a team plays in a particular game. Whichever team gets the higher number "wins" the game, and the result of that game updates the distribution parameters. When you win, your random numbers skew higher and when you lose your random numbers skew lower. For everyone's first game, I equally weighted the preseason information. As games were played, I phased out the impact of preseason information. Then I simulated 5k seasons and plotted histograms of conference winning percentage. This way the unbalanced schedule gets modeled - who you play and when you play them matters.
I ran several different versions where the preseason-phase-out-period set to 1, 3, 6, and 9 games. Basically that means that by the end of the season only the records count, but how quickly the record overtakes the preseason information changes. I also ran one version with a "12 game phase out" which practically means even at the end of the season the preseason gets a 25% weight.
There wasn't much difference between the 6, 9 and 12 game phase outs - ASU, KSU, ISU and Tech were consistently towards the top. West Virginia and Arizona were at the bottom. As expected, phasing out the preseason information faster resulted in more variation.
With only 3 games of preseason influence, the impact of unbalanced schedules started to appear more strongly. Suddenly Kansas and BYU, who's first three games are against the bottom teams, are in the top 3 of the league. As they win those early games and their preseason ranking influence goes to 0, they look like great teams. Conversely, ISU, KSU and Tech take pretty big hits as ISU and KSU play each other in a toss-up and Tech plays three top-half teams. When the preseason information goes away so quickly, a single early loss can lead to a spiral.
And for you guys who think only results matter, here is the version where preseason info is only used for the first game. After that, it's all 100% driven by game results. Total chaos, with nearly every team capable of finishing almost anywhere. Again you can see the impact of schedule on Kansas and BYU, as well as Colorado and OSU.
As I have time I might try this again with other conferences. I can also try different weighting for both the CF Ranking and CBS O/U, or I can incorporate other sites' preseason information.