taking the mean of the projections of the top 90-odd starting pitchers, and then considering standard deviations from those means, ie giving each player a point for being one standard deviation above the mean in a given catagory and -1 point for each s.d. below the mean and adding, I get
Grienke: 0.67 0.39 -0.21 -0.54 0.39 0.62 0.83 0.98 2.66
Escobar: 0.83 0.79 0.77 0.96 1.19 -0.44 -0.69 -1.1 -0.79
for: IP, W, ERA, WHIP, K, K/BB, weighted ERA, weighted WHIP, total
where total is the sum of W, K, K/BB, weighted ERA, and weighted WHIP.
that's why i said their projections have Greinke well above Escobar
edit: i may have found my problem... i think i'm basing these std devs from the mean of all pitchers, relievers and starters. Therefore, Escobar's K difference is down-weighted since Greinke is still well over the mean number of Ks. I did it that way to try and compare starters and relievers' contributions, but that doesn't seem to be the way to go...
if i only consider starting pitchers, then the standard deviation of Ks is going to be much smaller, so Escobar's 40 more Ks counts much more. As both relievers and starters have fairly similar ERAs/WHIP, it's more narrowly peaked, and the std dev is smaller, so Greinke's advantages are worth more.
The problem with this approach is that it screws up the relievers... MR who have a few wins projected get big points for those few wins, because it's many deviaitons away from the mean number of reliever wins.