Poll 2016: Which Group of Pitchers Performs Better?

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.

If you’re curious, here are links to the historical polls and results:

2013 | Poll | Results
2014 | Poll | No Results, apparently forgot to post them, oops!
2015 | Poll | Results

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 96 qualified starters, which included some that are no longer in a rotation and/or are injured. I have decided to only include 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 IP K% BB% LD% GB% FB% IFFB% BABIP LOB% HR/FB ERA SIERA ERA-SIERA
Steven Wright 114 19.8% 9.0% 19.8% 47.6% 32.6% 5.6% 0.271 71.0% 6.5% 2.68 4.49 -1.81
Martin Perez 107.2 11.3% 10.0% 20.5% 53.8% 25.6% 2.2% 0.276 73.8% 12.2% 3.85 5.35 -1.50
Jimmy Nelson 107 16.5% 10.4% 20.1% 48.1% 31.8% 11.9% 0.278 77.0% 11.9% 3.62 5.04 -1.42
Doug Fister 106.1 15.0% 8.2% 17.9% 48.5% 33.6% 6.3% 0.254 79.8% 13.5% 3.55 4.93 -1.38
Kyle Hendricks 98.2 21.6% 6.8% 17.6% 51.1% 31.3% 11.8% 0.245 74.1% 9.4% 2.55 3.92 -1.37
Tyler Chatwood 95.2 14.9% 9.1% 18.3% 58.0% 23.7% 5.7% 0.276 73.8% 8.6% 3.29 4.65 -1.36
Madison Bumgarner 129.2 28.5% 6.3% 19.9% 40.7% 39.4% 11.8% 0.255 85.6% 9.4% 1.94 3.30 -1.36
Marco Estrada 104.1 24.1% 9.5% 16.8% 34.3% 48.9% 17.6% 0.193 80.3% 10.7% 2.93 4.27 -1.34
Drew Pomeranz 102 28.0% 10.0% 15.1% 47.8% 37.1% 11.0% 0.240 80.8% 8.8% 2.47 3.75 -1.28
Danny Salazar 104.2 27.6% 10.8% 16.2% 48.5% 35.4% 10.9% 0.269 82.6% 9.8% 2.75 3.87 -1.12
Group Average 107 20.7% 9.0% 18.3% 47.7% 34.0% 9.4% 0.256 78.0% 10.1% 2.94 4.34 -1.40
League Average (All Starters) 20.2% 7.8% 20.8% 45.1% 34.0% 9.4% 0.299 71.9% 13.4% 4.36 4.32 0.04
*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
**Colby Lewis actually ranked second, but was removed due to injury

Group B – The SIERA Underperformers
Name IP K% BB% LD% GB% FB% IFFB% BABIP LOB% HR/FB ERA SIERA ERA-SIERA
Michael Pineda 95.1 27.2% 6.3% 22.9% 43.9% 33.2% 3.3% 0.349 66.7% 16.7% 5.38 3.38 2.00
Drew Smyly 100.1 25.2% 6.3% 19.8% 33.2% 47.0% 15.0% 0.313 63.2% 15.0% 5.47 3.78 1.69
Chad Bettis 102 17.1% 5.5% 22.8% 51.6% 25.5% 4.7% 0.344 63.7% 15.1% 5.65 4.13 1.52
Aaron Nola 96 25.5% 5.5% 21.0% 55.1% 23.9% 4.6% 0.331 60.5% 15.4% 4.69 3.20 1.49
David Price 124.1 27.1% 5.2% 25.0% 43.8% 31.3% 5.7% 0.321 70.9% 15.2% 4.34 3.27 1.07
Jon Gray 88.2 25.9% 7.9% 21.6% 48.5% 29.9% 8.7% 0.281 65.8% 17.4% 4.67 3.63 1.04
Robbie Ray 97.1 26.0% 9.1% 24.5% 44.2% 31.3% 5.7% 0.367 73.3% 14.9% 4.81 3.82 0.99
Dallas Keuchel 120 20.3% 7.2% 19.8% 57.4% 22.8% 12.0% 0.316 68.3% 18.1% 4.80 3.82 0.98
Marcus Stroman 116 16.9% 6.7% 20.1% 59.9% 20.1% 2.7% 0.306 65.0% 14.9% 4.89 3.93 0.96
Ricky Nolasco 108.2 18.4% 4.8% 18.3% 43.0% 38.7% 6.7% 0.330 62.8% 11.1% 5.22 4.27 0.95
Group Average 105 22.8% 6.4% 21.6% 48.3% 30.2% 6.9% 0.326 66.1% 15.4% 4.98 3.73 1.25
League Average (All Starters) 20.2% 7.8% 20.8% 45.1% 34.0% 9.4% 0.299 71.9% 13.4% 4.36 4.32 0.04
*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 rather interesting that Group B has posted significantly better strikeout and walk rates, leading to a far lower aggregate SIERA. Group A, however, has limited the quality of contact allowed by suppressing line drive rate and inducing a higher rate of pop-ups. I would bet the latter group has also posted a higher Soft% and lower Hard%.
 


 

 

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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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King Donko of Punchstania
Member
Member
King Donko of Punchstania

You’re going to currupt your own data by listing Group A first in the chart and then listing Group B first in the poll

Charlie Hustle
Member
Member
Charlie Hustle

jB, once you vote, the poll shows you the results top down based upon which group received the most votes. So Group B might appear to be listed before Group A when you view the results, but it was after Group A when you voted. You comment was off-base, but not to a degree that you deserve hate and downvotes.

jB4s7
Guest
jB4s7

Thank you for the explanation. This morning before I voted, it showed Group B listed first, which could potentially lead to some hasty voting mistakes. Looks like it’s fixed