Impeesa said:Y'know, I only took one probability course, so I'm a bit hazy on the technicalities - maybe hong could fill us in here, I don't know. But if I recall correctly, if you've got a bunch of things weighted towards a central value (in this case, feats with an average power value), you're pretty much guaranteed of a few things. Some will be below average, some will be above average, most will be around the median. The more sample points you have (more feats from more supplements), the more likely it is that some will be more significantly above or below the central point.
I think what you are going for here is an application of the central limit theorem.
Unfortunately, the CLT relys on a number of assumptions on the random variables in question. One would be, that all the random variables (e.g. feat power levels in this case) are independent and identically distributed. In order to be sure that the requirements are met, the first thing you would need is a proper definition of the concept of 'feat power level' and an argument for the independence assumption. Without that any conclusions based on probability theory are dubious at best.