Jose Bautista continues to be an incredible hitter. He may very well be the best hitter in baseball right now. In a well publicized stat, he's hit 70 home runs since the start of last year (54 last year, 16 so far this year). Number two? Albert Pujols at 49. His current line is .368/.520/.868, good for an incredible 1.388 OPS, good for a .230 point lead. What is also incredible is that despite his power, he's only driven in 27 RBI. Given his 16 home runs, he's only driven in 11 team mates. That's only 40% of his RBIs are teammates, 10% lower than any other hitter in baseball.
The Indians/Royals 19-1 blowout was ugly, and was over after the Indians put up 10 runs in the fourth off of Vin Mazzaro. I thought I'd take a look at how fluid the Pythagorean winning percentages are at this point of the season, and how a single blowout can change the expected winning percentage dramatically. Pythagorean winning percentage is pretty easy to calculate, and was developed by Bill James to estimate what a team's winning percentage should be. It is runs scored squared, divided by the sum of runs scored squared and runs allowed squared. Coming in to the game, the Pythagorean winning percentages looked like this, with the Indians ahead, but the Royals still projected as an above .500 team:
|Pre Blowout||Scored||Allowed||Pythgorean||Season Wins|
After, it is a different story. The Indians, now the proud owners of the best run differential in baseball, which goes nicely with their best actual record in baseball, are now a 108 win team, based on the runs they've scored and allowed. The Royals were not quite so fortunate, dropping from a projected 87 win team, to a below .500 79 win team. That isn't to say that last night should really change anyone's opinion about the Royals by 8 games over the course of the season, but more of an illustration about how the tools we use can be sensitive to extreme results.
|Post Blowout||Scored||Allowed||Pythgorean||Season Wins|