Steamer and I: Sonny Gray — A Review

Alas, we have reached the end of our Steamer and I reviews and I left the best for last…just kidding. Though I was surprisingly far more bullish on Sonny Gray than Steamer was, his season was an unquestioned disaster. So we certainly know whose forecast was better before even beginning our deep dive! But let’s get to the two projections sets anyway and compare what Steamer and I were expecting versus what actually transpired.

Steamer vs Pod vs Actual: Sonny Gray
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%
2016 Actual 117 5.69 1.50 7.2 3.2 1.38 18.2% 8.1% 0.319 63.9%

Sonny Gray had been a divisive name since he debuted in 2013. Since we still haven’t deciphered the code behind BABIP and HR/FB rates, we have been left wondering how much Gray’s suppressed marks are his own doing and an extraordinary skill, or just several seasons of great fortune…or, a combination of both. So, naturally, projections of his next season performance were going to be all over the place. This is how Gray ended up here, because a computer system that heavily regresses toward league average like Steamer is going to assume that Gray has little, if any, BABIP and HR/FB rate suppression skills.

Unfortunately, Gray’s season was riddled by injury, as he missed time due to trapezius and forearm issues. So his performance when he was healthy enough to take the mound was likely affected by his health, and it rendered all our projections hilariously wrong.

Let’s start with the strikeout rate, which I was slightly higher on than Steamer. Curiously, Steamer was actually projecting a career low mark, as Gray had been posted anything below 20.3%. The system turned out accurate, but again, who knows how much injury played a role. There wasn’t any particular pitch to blame for a loss in strikeouts, as his fastball and several of his secondary pitches all lost small, but meaningful, points of SwStk%. He also simply threw fewer strikes, and you can’t strike batters out with balls.

Speaking of balls, we were nearly identical on our walk rate projections, which represented a jump from 2015, back up to what his career average had been. His strike percentage fell to a career low, which pushed his BB% back up above 8.0%. Because his season ended up due to a forearm injury, you have to wonder if he was hurting all season and that hampered his ability to throw strikes.

Heading into the season, Gray sported a career .268 BABIP. There was little chance he owned legit .268 BABIP skills, but the question was how much of that suppressed mark represented his true talent level versus good fortune versus great defensive support. Steamer didn’t believe in the BABIP prevention skills at all, projecting an inflated .302 mark, actually above the league average. I hedged, thinking perhaps he did own some BABIP skills, and went with .285. Steamer somehow managed to be on the right track, as regression arrived in a hurry.

His batted ball profile look nearly identical to his career average with one exception — his Hard% surged above 30% for the first time. We haven’t found much correlation between Hard% and BABIP, though, so this may just be a coincidence. His LD% still remained below average, though his HR/FB rate nearly doubled. Did he ever actually own these suppression skills or was this just a lost season marred by injury where we should take the results with a grain of salt?

The inflated HR/FB rate boosted his HR/9 rate well above 1.00, or the first time it rose above the 0.74 mark he posted in 2015. So, technically Steamer was slightly closer, but still way off.

My LOB% projection is calculated for me and it’s an inferred number, meaning the ERA is calculated first and then the LOB% is derived based on the ERA. Gray had never been below 74.5%, so my forecast looked fair, while Steamer was projecting a career low and turned out to be closer.

Overall, there was an enormous 50 point difference in our ERA projections and .09 point difference in WHIP. By virtue of Gray’s disastrous performance, the more bearish forecast proved closer.

While health now becomes a concern, I’m still intrigued by Gray’s high ground ball rate, paired with his excellent slider-curve ball combination. Since many of us waited for his luck to run out, now that it seemingly has, he finally could be quite undervalued next year. I’m willing to roster him, assuming he seems healthy in the spring, and will to give him a pass on this season’s results. We know what he has done from 2013 to 2015, so that remains the most optimistic of upsides, and the cost should be cheap. A classic low risk/high reward play.

Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year. He produces player projections using his own forecasting system and is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. Follow Mike on Twitter @MikePodhorzer and contact him via email.

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