Okay, so one of the things a data scientist might like to do in a spot like this is trim the data for outliers, then make the comparison across the entire group.

I.e., define a point at which a bad performance becomes an "outlier" for a given goaltender. It could be 1.5 standard deviations off the mean, for example. Then you trim off these games, and see how everyone stacks up.

I believe that hockey reference already does this by some standard but that is actually a really good idea for myself to try and do. I might set up some python codes and graph it all out too.

Now, my argument is that I don't expect this would change things much. Seasons are not aberrations. Multiple bad performances - bad months, apparently? - can and should be used to measure the quality of a goaltender.

Not quite sure what your point here is meant in regards to the argument I've presented.

If you want to make this claim, then do the statistical analysis yourself; you can post a detailed analysis on the front page and we can all perhaps gain some perspective.

Do you have any suggestions on who else I shall compare this to?