Hi John, great idea and legwork looking up the data and running the correlations!! Although I have read Twins Daily since you all set it up, this is the first post that has caused me to actually register in order to post. You seem to be showing what baseball pundits and statisticians alike believe. However, I think the correlations may be limiting because it merely shows, well, correlation, and not causation. And since in this case, you clearly have a testable hypothesis (more regular season wins causes greater postseason success) with a clear causal arrow and no chance of reverse causality (e.g. postseason success causing more regular season wins), wouldn't it make more sense to run a regression? That way you could determine the precise statistical significance as well as the substantive significance of the effect (iff statistically significant, of course). You could begin by running a bivariate regression with the two variables you just used, and then could *really* play around to see what factors increase/decrease postseason success--or if it is indeed a crapshoot. You could add pitching, hitting , and fielding numbers and basically play with the specification ad nauseum. Something interesting it bound to pop up, right? Maybe fielding is more important, or player age, or postseason experience, or whatever. But this is a pretty simple model that savvy front offices must be familiar with. Of course, this may all be for naught, seeing as your correlation coefficient is so small! But with extra time, it might be a fun game.