@Knyte,
Wanted to get input from people like you and Buns again so I could figure out which potential confounding variables to weed out/etc. in the next step.
See, I wanted to give this istead of a sarcastic response, but then I started looking into what variables that was.... and that is a lot. Practically speeking, the following factor is what I would try to look into.
1. Rating.
a) Look at the avg. opponent rating for won and lost games. If the difference is too big, the data can not be used to determine stalling. If rating is close (within 100 points?) then the data is more relevant. This method has several obvious disadvantages, but might be interesting either way. At least it would show a difference for my case :p This works better on players who have been active in the ladder for more then a expiration period (5 months, continuously)
b) Look at the average time it takes a X rating player playing Y rating player to achieve Z result, across the whole ladder. Then compere it to any individual player to see how long time they take to loose, compered to the norm. Don't think this would work to well, tbh.
c) Only consider games that is within X (150?) rating of a players own rating, then do the calculations you have already done for win/loss time.
Armies, income
Use the same rules as Seasonal ladder does to determine ties, and apply to the last turn in every game. Compere avg. win number, with avg. loss number. Then rank players, based on the difference.
Anyway, just some ideas. All the methods listed above have flaws but they might be interesting nevertheless. Mainely, I see the challenge being how you include all metrics in one ranking way. As you see the Rating methods only accounts for time taken, blantetly assuming ther is some sort of avg. game comparison that can be made. While Armies, Income in my suggestion don't account for time taken, only turns. What I fear is that one might quickely have a small sample size if combining both.