The best way to predict a team's four factors in a future game is to create a linear regression involving their four factors, and their opponent's four factors.
Unfortunately, Ken Pomeroy has not yet adjusted the Four Factors for quality of opponent play (and for good reason - it's quite complicated). So we need to estimate how strength of schedule affects actual four factors. Unfortunately, I don't have any good way to run this analysis on every team. The best theory of adjustment would apply to all teams, but since there is a good chance that individual teams affect these numbers differently, it's not entirely bad to only regress on a team-by-team basis.
The next part of this is much harder.
We need to find the standard deviation of actual versus predicted four factors stats in order to run it through a Monte Carlo simulation that takes all likely normally-distributed values for all of the four factors+pace (which is 9 variables), which in turn spits out a point margin (whose values come from the previous post).
I'll be coming up with this system pretty soon, so watch out.
