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Why do some metrics love Michael Pineda?

While he has been one of the worst pitchers in the league based on results, he somehow gets a bump from peripheral metrics.

MLB: New York Yankees at Seattle Mariners Joe Nicholson-USA TODAY Sports

I am a lover of sabermetrics, as many of you probably know by now. I think you’re going to get a much fuller picture of the sport if you’re looking at many of the advanced metrics of the day, then pretty much any of the standard metrics used before the century began. I feel like that kind of statement is always followed by, “but here’s something that can’t be proved by sabermetrics!” I guess you could say that’s the case here, but this is more inquisitive than pejorative.

One of the areas in which publicly accessible sabermetrics is only decent at best is comprehensive pitching metrics. For those who don’t know, RA9 pitching WAR is for calculating value based on runs allowed. fWAR is based on FIP per inning, with some league adjustments thrown in.

PWARP, the Baseball Prospectus pitching metric, uses what’s called Deserved Run Average (DRA), which calculates what an ERA should be based on a number of factors out of a pitcher’s control: weather, team defense, opposing team offense, park factors, batter handedness, and the effects of the catcher and umpire. This means that you can be credited for facing better players and with poor framing catchers, for example, and debited for the opposite. For a more comprehensive look, I recommend their introduction article.

I am, admittedly, a fan of this metric. It correlates year-to-year performance better than any other metric, and I believe that it strips pitching down to a relative degree of skill that nods to the DIPS theory of FIP, but doesn’t make the assumption that pitchers have no control over what happens. It’s the best we have in the public sphere.

That doesn’t mean there aren’t quirks, which brings me to the point of: Michael Pineda. Pineda, as every single person here knows, is having a horrid year on the mound. He has pitched to a 5.02 ERA over 141.2 innings, while also allowing a whopping 22 home runs (1.4 per nine innings). His FIP is a more respectable 3.86, but he had a good FIP last year, too (3.34), and his ERA then was 4.37.

Even with the eye test, we know this to be true. He has allowed a .207/.233/.347 line through 0-2 counts, which is pretty unacceptable given his stuff. He bounces that slider in the dirt, falls behind, then makes a poor pitch. With runners on, he has allowed a .360 wOBA, very similar to his FIP-beating 2014 when it was .359.

Even so, both fWAR and PWARP seem to like him. He has put up an 87 FIP-/2.4 fWAR and a 2.76 DRA/4.4 PWARP this year. He somehow has the 17th lowest RA9-WAR, but the 14th highest PWARP in baseball. Considering what we know and have seen, this seems unbelievable. Why is this the case?

One thing about both FIP and PWARP we have to understand is that they remove context, so we have to understand cases where context may actually be hurting, where it has an actual effect when the metric says there is none. This is incredibly difficult, but here are a few theories.

One of those cases, which seems explainable, is 0-2 counts with runners on base. I am a believer in the mental side of baseball, of course, so I think it’s fair to believe that in “crucial spots” (at least in his mind) he does not locate his pitches well whatsoever. It’s also a large enough sample (about 300 innings) to show that this could be a consistent issue.

Another one is shifts, which might just be bad luck. With shifts (both traditional and non-traditional) on, he has allowed a .392 wOBA in 33.1 innings, as opposed to .299 without (Last year it was .351). Maybe he doesn’t pitch well with shifts, which would explain why when you strip defense, he may look better in comparison. Why the Yankees don’t change their approach is a whole other question entirely, but they must believe that it doesn’t have that much of an effect. Again, it’s just a theory.

He also checks a lot of the boxes for context-neutral statistics, as well. He posts a high strikeout rate (10.16 per nine innings) with a low walk rate (2.54 per nine innings). The home run rate, as I mentioned, is incredibly high, but park factors allow that to be regressed a fair amount. Most projection systems believe his true talent home run rate to be about 1.1 per nine innings.

When you throw these things together: good peripheral numbers, park factors in your favor, and failing to produce in higher leverage spots, this is the result you get. I think there is some reason to believe that he can put the pieces together, a la AJ Burnett in 2012. There was another case where the mental side was clearly playing games with him, so a change of scenery and mechanics worked wonders.

I don’t think Pineda does that in New York. That’s unfortunate, because there are so many instances where the talent just does not align with what we want the results to be. If this DRA/ERA discrepancy tells us anything, it just tells us what we already know: Michael Pineda is immensely talented, if only he did it in sequence.