The way the formula works, if a player is having an above average season on a great team, then they project favorably in the MVP predictor. Having said that, the formula allows for players having exceptional seasons on mediocre teams to make an impact on the distribution of voting points.
Last post was filled with out-loud ruminations on WPA and how it appears to correlate highly with the eventual MVP winners. Appearances can be converted to number form thanks to the invention of statistics. The linear correlation coefficient for the AL was .47, and the NL it was .54. That’s a statistically significant relationship which suggests at some point voting points and WPA diverge from being independent data sets. The same can be said for WAR, which has a coefficient of .49 for the AL, and .57 for the NL.
WAR (bref version) was already included in the set of variables used for regression, and adding WPA appears to resolve more of the variance in voting points than before.
Here is the new AL MVP table:
Jacoby Ellsbury has made quite a surge lately, and when compared to the formula that doesn’t use WPA, his probability almost doubles. I should point out that I recently added stolen bases to the equation as well, which would explain why his chances increase by 100%, while Bautista, who has the highest WPA in the AL, only increases 2%.