You're taking his analysis as gospel when he himself does not.
Again he allows for contradictory work to his own.
So he comes up with a hypothesis which is it itself flawed - that differences in competition should even out. Why? This hypothesis is just a restatement of the conclusion he is trying to reach. He then does some serious post-hoc to try to make those two come together.
For example, if a player is 4th line shouldn't their QoC be uniformly poor? If he plays with other 4th line players, shouldn't that normalize whatever results they get? If he is correct about WOWY numbers being more consistent then he should have found correlating data to back up his claim. But he doesn't.
Essentially his base argument is that Ferrari screwed up and that all the corrections he used to come to his 55% were pointless in the first place. But he has almost no data to back that up besides invoking a symmetry argument that might be false to begin with.
But that essentially means that his chosen metric is insufficient to show fine grain changes in these factors.
This is a common problem with these advanced stats guys. Their statistical analyses are frankly very basic. They almost never stop to think about whether Corsi or shot differential is a good predictor to begin with. And remember, I think this is an example of a pretty good article.
Oh yeah, and then at the end he admits he might have been wrong about everything.
Finally, the 95% CI he invokes at the end is missing a major factor. If you don't have enough resolution to your data to discern small changes that might be large relative to the rest of the data (i.e. differences in QoC) then your distribution is incapable of telling you anything.
