[Irieguy]

In theory, you are absolutely correct... and I used to get frustrated by this concept as well.

But Aleo did some very important and underrated work when he compared emperical results to those predicted by assumptions of a normal distribution. What he found is that over enough trials (and "enough" is surprisingly few), SNG results for a standard winning player resemble a normal distribution with remarkable similarity. In fact, by the time you get to a few hundred, you can barely tell the difference.

What that means is that you can apply statistical measures for normal distributions to SNG results and make reliable inferences if you have enough data. There hasn't been much discussion about it since, but I found it remarkably important at the time and didn't thank Aleo appropriately, I fear.

I am not a statistician, so it's quite possible that I am completely misguided by what I've learned. But I have a lot of experience deciphering statistical measures applied to biologic models... something that was formerly felt to be impossible but is now the basis for evidence-based medicine, and I think there is a similar utility here (with regard to an imperfect application working surprisingly well.)

Irieguy