Reviewing Pod vs Steamer Projections — ERA Downside
Yesterday, I recapped my comparison of the starting pitcher ERA Pod Projections vs Steamer projections in which I was more bullish. Today I finish reviwing the Pod Projections vs Steamer projections series by looking at the group of starters I projected for worse ERA marks. Since I mentioned in yesterday’s article that I projected a lower ERA than Steamer for the vast majority of starters (which is one of the reasons I performed so poorly in the results comparison), I only had 21 pitchers whose ERA I was projecting a higher mark for. So this group to review is much smaller and the gap in ERA between the two projections is as well.
2017 Pod ERA | 2017 Steamer ERA | 2017 ERA | Winner | |
---|---|---|---|---|
Jose De Leon | 3.96 | 3.57 | 10.13 | Pod |
Robbie Ray | 3.87 | 3.57 | 2.89 | Steamer |
Zack Wheeler | 3.82 | 3.62 | 5.21 | Pod |
Michael Pineda | 3.69 | 3.51 | 4.39 | Pod |
Tyler Skaggs | 3.73 | 3.56 | 4.55 | Pod |
Blake Snell | 3.81 | 3.67 | 4.04 | Pod |
Tyler Glasnow | 3.96 | 3.85 | 7.69 | Pod |
Yesterday, after noting my poor results, I said that I’m hoping it means I performed much better on the downside list, and luckily, it did.
For a rookie, Steamer was surprisingly bullish on Jose De Leon. The ERA discrepancy was primarily driven by a difference in projected strikeout rate, with Steamer being the optimist and me being the conservative dude. Turns out, De Leon battled injuries, pitched just 2.2 innings with the Rays and 41 innings overall. So this was as cheap a “win” for me as it gets!
By SIERA, Robbie Ray was almost an identical pitcher from 2016 to 2017, but his BABIP plummeted from .352 to .267 and LOB% jumped along with it, from 68.7% to 84.5%. The significantly better fortune pushed his ERA below 3.00, far better than either of us projected. Ray was the type of pitcher Steamer usually struggles with, as he had a history of inflated BABIP marks that Steamer would normally aggressively regress toward league average (and it did, forecasting a .296 mark). On the other hand, I projected a .305 mark. With an absurd Hard%, it’s a wonder how he managed such a strong BABIP, and with continued control issues and a fly ball tendency, he’ll be overvalued in 2018.
Zack Wheeler is another cheap win Steamer’s ERA projection was based on Wheeler’s innings primarily coming in relief. No one really had a clue what Wheeler was going to do anyway, and although most of his underlying skills were generally around where he had been, a high BABIP and severe gopheritis pushed his ERA above 5.00. I’m still intrigued by his potential, but injuries are making it hard to remain optimistic.
Michael Pineda was the AL version of Robbie Ray, which is how the typically bullish Pineda owner was actually more pessimistic than Steamer this time. He pitched about half a season before requiring TJ surgery, and did exactly what he has always done — post strong peripherals, but be crushed by an above league average BABIP and gopheritis. The BABIP actually came down this season, but HR/FB rate spiked into the stratosphere.
Steamer loved Tyler Skaggs and even projected a career best strikeout rate, which failed to manifest. I liked him too and even bought him in AL Tout Wars, but I wasn’t that bullish. The fastball velocity spike he enjoyed in 2017 was short-lived, as it dropped this season, and his SwStk% has been in a holding pattern below the league average. Since that 2014 ground ball rate now looks like a fluke, I’m not interested here any longer.
Steamer and I both projected similar underlying skills for Blake Snell, but we were off on his HR/9, perhaps because he posted a minuscule 5.6% HR/FB rate in 2016, a mark I completely ignored when making my forecast. Sure enough, his HR/FB rate just about doubled to 11%, keeping his ERA above 4.00. I remain excited here as over about a full season’s worth of innings, three of the four pitches he throws have generated double digit SwStk% marks. Soon, his strikeout rate will match the high quality of his stuff.
For Tyler Glasnow, remaining conservative on his strikeout rate ultimately was the right call. Of course, it wasn’t really the strikeout rate that led to his poor results, but more his control, or lack thereof. That had always been Glasnow’s bugaboo, but combine it with ridiculous BABIP and HR/FB marks, along with a suppressed LOB%, and you have the recipe for a disaster. Most concerning is that his SwStk% fell to just 8.2%. Strikeouts had been the only thing exciting in his profile, so without those, he’s just a bad minor league pitcher who can’t find the plate.
Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year and three-time Tout Wars champion. He is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. Follow Mike on X@MikePodhorzer and contact him via email.
I like these because they are on rate stats. These types of articles tend to just devolve into comments about playing time projections. If I’m reading about stolen bases, I care way more about rate (SB/PA) than playing time. Do the playing time article one time and be done with it. Yes the Steamer and POD PAs were extrapolated in the SB article but why wasn’t their MLB total extrapolated as well? The analysis ends up being, “Steamer projected less stolen bases and because he only made 100 plate appearances this year, Steamer won.” That’s not useful information for anyone.
Excellent point. Yeah, I thought I covered my bases by extrapolating their projection to my PA total but kinda forgot about if a player misses time or gets way more time than expected, the more bearish or bullish projection is going to win.
Next year, I’ll make sure to just stick to per plate appearance rates for counting stats. Thanks!