A blog post about the Royals and expectations and mutilating math
07/09/2014 9:54 AM
I would like to apologize right here at the top for the abuse of sound mathematic and sabermetric principles that the rest of this blog post is probably going to unleash, but as long as each and every one of you promise to be kind if you see something stupid in here we can continue.
I can wait, you know.
C’mon, just promise.
OK, good. Thank you.
Now, I alluded to this in the Twitter Tuesday yesterday, but there is an interesting development with the Royals offense. Alcides Escobar and Lorenzo Cain are, basically, the only two players outperforming what would’ve been a reasonable expectation before the season.
Through a combination of good pitching and very good defense, the Royals are allowing the third-fewest number of runs in the American League. What’s keeping the Royals merely in a playoff race, instead of leading a playoff race, is the offense.
That’s nothing new.
But I got curious about how much of this is fair to put on who, which is where the mutilation of math likely begins. Basically, I looked at how each player has performed so far this season compared with the average of two prediction models offered on the awesome FanGraphs, in particular with Runs Created based wOBA (wRC). Yes, I realize a large number of you just cussed at me.
Anyway, if we use the generally accepted idea that 10 runs equals a win or a loss, we can very roughly convert this into a nerdy guess on what the Royals’ record would look like if each player was performing up or down to that preseason expectation.
Some of the numbers are what you’d expect, many aren’t. Some make sense, and some don’t. So just keep in mind that this is all a sort of sabermetric hypothetical and that only math, and not animals, was harmed in the making of this blog post. So again, please be kind.
The nine regulars, in order of outperforming preseason expectations:
Alcides Escobar. Prediction: .266/.302/.358. Currently: .287/.325/.395. Difference in wRC: +14. Wins: +1.4.
Salvador Perez. Prediction: .286/.323/.433. Currently: .282/.328/.435. Difference in wRC: +12. Wins: +1.2.
Lorenzo Cain. Prediction: .269/.320/.386. Currently: .322/.359/.450. Difference in wRC: +11. Wins: +1.1.
Alex Gordon. Prediction: .272/.346/.434. Currently: 268/.348/.425. Difference in wRC: +8. Wins: +0.8.
Omar Infante. Prediction: .281/.316/.395. Currently: .265/.307/.377. Difference in wRC: +3. Wins: +0.3.
Eric Hosmer. Prediction: .282/.338/.428. Currently: .259/.304/.357. Difference in wRC: -1. Wins: -0.1.
Nori Aoki. Prediction: .284/.344/.370. Currently: .263/.326/.324. Difference in wRC: -1. Wins: -0.1.
Mike Moustakas. Prediction: .245/.301/.415. Currently: .193/.258/.377. Difference in wRC: -2. Wins: -0.2.
Billy Butler. Prediction: .284/.356/.426. Currently: .269/.323/.344. Difference in wRC: -5. Wins: -0.5.
Again, some of this doesn’t make sense to me. Like, I’m not sure why Perez is performing almost identically to the prediction in the slash line but there’s such a difference in his wRC. There is more than just slash line in the wRC, but still.
I would’ve expected the negative numbers, particularly with Hosmer and Butler, to be bigger. But that’s one of the reasons I like to look at these things. If they just showed you what you expected, there’d be no point.