The first post prompts a fundamental confusion. (The poster may or may not be fundamentally confused--I don't know.)
To translate the poster's comment into classical test theory:
For any so-called clutch performer we have merely a sample of performances from an infinite domain of possible clutch performance situations. If the performer got to replay all the relevant clutch situations an infinite number of times (without fatigue or learning), sometimes he would succeed, sometime he would fail, but his success rate would be a really nice thing to know--this would be his "true" score. Of course we never get an infinite number of trials. We are always stuck with a sample. Because there is variance, we can never be sure about our inferences from the sample of performance to the domain of performance. This is why good test reporting uses error bands. The poster's main point, which is a good one, I believe, is that before we get all fired up about the performances that we observe from Vinatieri, Brady, Ortiz etc., we should consider the error bands that would inform our inference from the sample to the domain. Welcome to the world of quantifying measurement error.
Here is my concern:
Error bands go in both directions. The post might lead a reader to believe that error bands for outliers (e.g., superstar clutch performers) only stretch toward the average. While Vinatieri, Brady, or Ortiz might be the "beneficiaries" of variance, they may equally be the "victims" of variance.
Here is the tricky tricky part:
My point is only true for individuals cases! When we look at groups, we do want to pull in the outliers to account for measurement error. Measurement error artificially spreads out groups of performers when we compare them. However, when it comes to assessing the performance of a single individual, which I think we are trying to do, observed performances are just as likely to be above or below the average performance over infinite trials. I.e., variance 'helps" just as much as "hurts." Imagine if Ortiz, as kick-ass as he is, is nevertheless the victim of BAD luck!
BTW, great post!
Sean