Poll 2017: Which Group of Pitchers Performs Better?

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July 12, 2017

Since 2013, I have polled you dashingly attractive readers on which group of pitchers you think will post the better aggregate ERA post all-star break. The two groups were determined based on ERA-SIERA disparity, pitting the underperformers versus the overperformers during the pre-all-star break period.

I came up with this idea given my faith in using SIERA over smaller samples, rather than ERA, as I generally ignore ERA completely as late as the middle of the season and it’s interesting to learn how everyone else thinks. Will the SIERA outperformers continue to outperform, perhaps due to continued strong defensive support and/or more pitcher friendly ballparks, or will the magic vanish? And is it just bad luck that is due to reverse course for the SIERA underperformers or are they being hampered by one of the aforementioned factors that should continue to play a role the rest of the way?

My population group consisted of 114 starters with at least 70 innings pitched, which included some that are no longer in a rotation and/or are injured. I have decided to only include in the two groups those who will remain a starter and whose return from the DL is not up in the air. Group A is composed of the 10 largest SIERA outperformers, while Group B is composed of the 10 largest SIERA underperformers.

Group A – The SIERA Outperformers
Name K% BB% LD% GB% FB% IFFB% BABIP LOB% HR/FB ERA SIERA ERA-SIERA
Andrew Cashner 11.6% 10.4% 19.9% 49.8% 30.3% 3.7% 0.282 74.8% 7.4% 3.54 5.70 -2.16
Jason Vargas 18.2% 5.8% 18.9% 37.4% 43.7% 9.4% 0.276 84.7% 7.9% 2.62 4.63 -2.01
Ervin Santana 18.8% 8.3% 15.2% 44.3% 40.5% 12.9% 0.217 83.6% 12.9% 2.99 4.75 -1.76
Gio Gonzalez 23.5% 10.5% 19.5% 44.1% 36.4% 11.1% 0.259 85.0% 13.0% 2.86 4.45 -1.59
Jose Urena 15.9% 8.2% 18.3% 39.5% 42.2% 10.8% 0.245 78.2% 10.8% 3.54 5.10 -1.56
Brandon McCarthy 18.5% 7.0% 22.8% 43.4% 33.8% 22.1% 0.272 72.3% 5.2% 3.12 4.57 -1.45
Dallas Keuchel 24.4% 6.4% 14.2% 67.4% 18.4% 5.7% 0.222 88.7% 17.1% 1.67 3.11 -1.44
Ivan Nova 13.9% 3.1% 22.8% 47.9% 29.3% 8.0% 0.267 79.1% 13.4% 3.21 4.52 -1.31
Chase Anderson 23.4% 7.4% 18.8% 38.1% 43.1% 10.7% 0.272 78.7% 7.8% 2.89 4.15 -1.26
Kyle Freeland 14.0% 8.8% 17.1% 55.0% 27.9% 12.6% 0.287 77.9% 12.6% 3.77 5.03 -1.26
Group Average 18.0% 7.6% 18.8% 46.3% 35.0% 10.7% 0.260 80.5% 11.0% 3.04 4.62 -1.58
League Average (All Starters) 21.6% 8.6% 20.2% 44.3% 35.5% 9.5% 0.297 72.5% 13.7% 4.35 4.27 0.08
*All Group Average metrics (excluding ERA & SIERA) were calculated by weighting total batters faced, which isn’t perfectly accurate, as the batted ball data should be weighted based on balls in play, but that would have been too time-consuming; these averages are close enough

Group B – The SIERA Underperformers
Name K% BB% LD% GB% FB% IFFB% BABIP LOB% HR/FB ERA SIERA ERA-SIERA
Ubaldo Jimenez 19.3% 11.2% 19.0% 44.7% 36.4% 9.8% 0.272 64.1% 20.7% 6.67 4.96 1.71
Masahiro Tanaka 23.2% 6.1% 17.7% 48.9% 33.4% 12.7% 0.316 71.2% 22.5% 5.47 3.86 1.61
Josh Tomlin 17.5% 2.7% 24.7% 39.4% 35.9% 5.4% 0.347 64.8% 15.2% 5.90 4.31 1.59
Trevor Bauer 25.8% 8.5% 20.7% 47.3% 32.0% 9.8% 0.336 67.9% 17.1% 5.24 3.88 1.36
Jeff Samardzija 26.2% 2.9% 24.7% 43.2% 32.1% 8.3% 0.323 67.1% 16.7% 4.58 3.26 1.32
Matt Moore 17.9% 9.0% 20.8% 37.3% 41.9% 5.8% 0.347 66.2% 10.9% 6.04 5.01 1.03
Kyle Gibson 13.6% 10.1% 22.3% 50.7% 27.0% 2.6% 0.335 68.8% 21.1% 6.31 5.32 0.99
Marco Estrada 24.9% 8.8% 20.9% 32.1% 47.0% 11.9% 0.325 72.0% 12.6% 5.17 4.22 0.95
Adam Wainwright 20.7% 7.7% 24.7% 47.7% 27.7% 12.0% 0.347 67.4% 12.0% 5.20 4.25 0.95
Kevin Gausman 18.4% 9.6% 23.8% 41.4% 34.8% 10.8% 0.371 70.6% 12.6% 5.85 4.93 0.92
Group Average 20.9% 7.6% 22.0% 43.1% 34.9% 9.0% 0.333 68.1% 16.0% 5.59 4.35 1.24
League Average (All Starters) 21.6% 8.6% 20.2% 44.3% 35.5% 9.5% 0.297 72.5% 13.7% 4.35 4.27 0.08
*All Group Average metrics (excluding ERA & SIERA) were calculated by weighting total batters faced, which isn’t perfectly accurate, as the batted ball data should be weighted based on balls in play, but that would have been too time-consuming; these averages are close enough

I would have liked to include additional metrics for comparison, namely Hard%, but there’s simply not enough room to display every relevant one.

It’s quite interesting that Group B has actually posted slightly stronger skills (lower SIERA) than Group A, with a significantly higher strikeout rate. The most notable difference comes in the line drive rate, which we know highly correlates with BABIP. Even though there’s limited consistency within the stat, it’s an important backward-looking indicator of performance. So the gap there goes a long way to explaining the ridiculous BABIP difference of .73 points.

In addition to the difference in LD%, Group A has been more adept at inducing pop-ups, another BABIP suppresser. Naturally, all those extra hits, along with the much higher HR/FB rate, has pushed down Group B’s LOB%.

So let’s get to the poll questions. I will close the poll before games start up again.


 

 





 

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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Jeff Zimmermanmember
6 years ago

If the ball stays live, I would not be surprised to see the first group perform better since they have a higher GB%. It’s a tough time to be a flyball pitcher.

Mike, if you’re completely bored at some point, I’d be interested in the average HR/9 for each group.

5
Nevin
6 years ago
Reply to  Jeff Zimmerman

My exact first reaction. Lotta GB% upside in that first group.

2
Mike Podhorzermember
6 years ago
Reply to  Jeff Zimmerman

The two groups have essentially the same FB% though, so I don’t think that makes sense. The difference is B allowed more liners instead of grounders, which should have no effect on homers allowed. Now maybe you can argue that B’s liners will become flies in the second half, and some might, but also maybe A’s grounders become flies or liners as well since their LD% is below league average.

2