Steamer and I: Sonny Gray

It’s time to move on to the starting pitching side of the ledger for our next set of Steamer and I entries. For the pitchers, I’ll be comparing my ERA Pod Projection to that of Steamer to identify who I am significantly more bullish and bearish on.

First, we’ll start with one of the pitchers I am far more optimistic on than Steamer is. But before we dive in, I wanted to note some of the pitchers I skipped over. Chris Young, Royals version, topped the list, for obvious reasons. He breaks all computer models and is a perfect example of why it is often better to rely on human forecasts than computer ones. After Young was the man that came back from the dead last year, Rich Hill. Obviously, a computer system is going to struggle with his projection and is also unaware of the work he did on his mechanics last season that may have been behind his improved control. He’s a total crapshoot though and a complete shot in the dark, so he’s not really worth discussing.

So after several more unexciting names, we get down to Sonny Gray. He’s yet another example of the type of player computer projection systems may struggle with. This is especially true of Steamer, which heavily regresses a pitcher’s luck metrics toward the league average. The majority of the time, this is the correct move. It’s how I generally forecast myself. But there are exceptions of course and Steamer is going to miss them, just like Young mentioned above.

Over his relatively short career, Gray has posted a 2.88 ERA, versus a far less impressive 3.59 SIERA. Let’s find out why I’m so much more bullish on his performance in 2016 than Steamer.

Steamer vs Pod: Sonny Gray

System	IP	ERA	WHIP	K/9	BB/9	HR/9	K%	BB%	BABIP	LOB%
2015	208	2.73	1.08	7.3	2.6	0.74	20.3%	7.1%	0.255	76.8%
Pod	210	3.24	1.21	7.5	2.8	0.71	20.3%	7.6%	0.285	74.5%
Steamer	208	3.74	1.30	7.5	2.8	0.79	19.8%	7.4%	0.302	71.6%

Let’s begin with the underlying skills. Steamer and I are projecting very similar strikeout and walk rates. Gray has actually outperformed his xK% marks in each of his first three seasons. I’m not necessarily expecting him to outperform again, but I think he could easily prevent any potential for regression. Last year, he doubled the usage of his slider and its SwStk% surged. Unfortunately, his curve ball’s SwStk% plummeted as well. So all he has to do is throw his slider a bit more often, while reducing his curve ball usage, and he may be able to fend off a decline in strikeout rate. Or, his curve’s effectiveness could rebound.

Steamer is obviously unaware of the change in pitch mix (at least I think it is) or his under 20% xK% marks the last two years. So it’s curious why it’s projecting a career low strikeout rate.

I’m slightly more bearish on Gray’s control than Steamer, but both systems are forecasting some regression from last year. While young pitchers often improve their control, it’s just a matter of looking at his career and expecting him to give up some of his gains.

Next, we’ll check in on the HR/9 rate, which I am projecting a slightly better mark than in 2015, but worse than his career. Gray has posted a career HR/FB rate of 9.2%, which perfectly matches with his home park’s 92 park factor. However, he has actually posted a significantly lower HR/FB mark in away parks than at home! That’s odd. I’m not sure why Steamer is projecting a career worst HR/9 mark, though a career low strikeout rate definitely plays a role.

Last, we get to the primary driver of our disagreement — the BABIP! We know that pitchers exhibit limited control over their BABIP marks, and what little control they have comes from their batted ball type distributions. Over 491 career innings, Gray has posted a .268 career BABIP, which is well below the league average. That still remains too small a sample to convince us that Gray has some special BABIP suppression skill. However, with a low LD%, maybe some of that is really skill.

Rather than completely ignore what he has done and automatically project around a league average mark, I’m willing to give him credit for a skill he potentially does own. My BABIP projection still easily sets a career high mark, so there’s definitely regression built in, but with the acknowledgement that maybe he’s an outlier. Steamer, on the other hand, is treating Gray with complete disregard for his history! I’m not sure if the system accounts for the team’s projected defense, though that may provide some of the explanation. The Athletics defense is poor. But it was last year too.

Thanks to my higher strikeout rate, and lower HR/9 and BABIP marks, I’m projecting Gray to strand a higher rate of base runners (LOB%) than Steamer. I should note that I don’t manually project LOB%. It’s actually an inferred number based on the ERA projection and the forecasted number of base runners.

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So which SOnny Gray projection do you think will prove more accurate — Pod or Steamer?