I think for simplicity the goal should be to come up with a ponderation law or ponderance curve, which is Mavic's pretentious term for "probability" or "histogram" or "distribution". Flo uses a description: percentage of time spent in yaw angle range. Trek uses something similar except that they bifurcated their research by probability data collected on two different IRONMAN course -- Kona and Wisconsin -- which is presented in a simple histogram with time on the y axis. Can you see who directed their report at consumers and who didn't. Anyways, they are saying the same thing just differently. We need to come up with a cumulative density function, effectively, on which to calculate "weighted average drag [change]" or "net drag reduction value", Mavic and Flo's terms, respectively. These are very simple calculations once you have the histogram and make an assumption about what to do beyond -10 and 10 with your discrete data points from those angles, given the reality that we don't know what happens at high yaw in terms of stalls and the like.
If TinyPic weren't broken I'd paste some charts, but here are the links.
Ponderation law (Mavic): link
Global results law (Mavic): link
Kona ponderation law (Mavic): link
Flo percentage of time at yaw angle range link
Trek probability (page 11, which you'll have to count to because they don't have page numbers -- shaking my head): link
This exercise is for you. What makes you most comfortable? Where do your biases lie -- toward the research that points to low you concentration or high yaw concentration?
Finally, I don't actually have any of this raw data except from Flo. I can't look at a bar chart pic and convert it into a spreadsheet. So if anyone is willing to provide the Mavic data raw, I would be grateful.