[wgardner]

Here's a generalized perspective.

Let's say you pick r1, r2, r3, b1, b2, b3 to minimize the following error
E(w)= w*[ (R-B) - ( (r1+r2+r3)-(b1+b2+b3) ) ]^2 + (1-w) * [ (R-(r1+r2+r3))^2 + (B- (b1+b2+b3))^2]

if w=1, you're computing the WMPR solution (or any of the set of WMPR solutions with unspecified mean).

if w=0, you're computing the OPR solution.

if w=1-small epsilon, you're computing the nWMPR solution (as the relative values will be the WMPR but the mean will be selected to minimize the second part of the error, which will be the mean score in the tournament).

if w=0.5, you're computing the EPR solution.

I wonder how the various predictions of winning margin, score, and match outcomes are as w goes from 0 to 1?