Poll 2021: 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 overperformers versus the underperformers 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 overperformers 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 initial population group consisted of 105 pitchers who have thrown at least 70 innings, which included some that are no longer in a rotation and/or are injured (I excluded these pitchers from the tables). Group A is composed of the 10 largest SIERA overperformers, while Group B is composed of the 10 largest SIERA underperformers.

Group A – The SIERA Overformers
Name LD% GB% FB% IFFB% HR/FB BABIP LOB% K% BB% ERA SIERA Diff
Kyle Gibson 19.8% 50.9% 29.3% 7.2% 9.6% 0.254 84.3% 21.7% 7.6% 2.29 4.15 -1.86
Lance Lynn 20.5% 34.5% 45.0% 12.6% 8.7% 0.243 86.2% 28.5% 8.4% 1.99 3.75 -1.76
Kevin Gausman 15.7% 44.2% 40.1% 5.6% 7.5% 0.212 84.7% 30.5% 6.9% 1.73 3.31 -1.58
Taijuan Walker 24.1% 39.7% 36.2% 15.5% 7.1% 0.249 77.6% 24.9% 8.4% 2.50 4.08 -1.58
John Means 21.7% 30.4% 47.8% 20.5% 14.8% 0.192 100.0% 25.7% 4.9% 2.28 3.78 -1.50
Kwang-hyun Kim 19.6% 47.5% 32.9% 15.3% 8.3% 0.280 77.1% 19.2% 8.1% 3.11 4.59 -1.48
Wade Miley 21.6% 53.0% 25.4% 8.2% 8.2% 0.279 78.4% 19.2% 6.6% 2.80 4.16 -1.36
Lance McCullers Jr. 15.8% 52.5% 31.7% 7.8% 9.4% 0.260 80.3% 26.4% 12.2% 2.94 4.29 -1.35
Walker Buehler 19.0% 41.7% 39.3% 8.8% 11.4% 0.231 83.7% 25.7% 5.9% 2.36 3.71 -1.35
Anthony DeSclafani 18.1% 45.5% 36.5% 9.5% 10.5% 0.238 81.0% 23.5% 6.9% 2.68 4.02 -1.34
Group Average 19.5% 44.5% 36.0% 11.0% 9.6% 0.245 82.4% 24.6% 7.5% 2.44 3.95 -1.52
League Average* 21.2% 43.3% 35.5% 9.6% 14.1% 0.288 72.8% 23.2% 8.0% 4.19 4.20 -0.01
*Only starters are included

Group A – The SIERA Underformers
Name LD% GB% FB% IFFB% HR/FB BABIP LOB% K% BB% ERA SIERA Diff
Matt Harvey 25.8% 41.8% 32.4% 9.0% 13.5% 0.362 54.5% 16.7% 7.1% 7.70 4.83 2.87
Eduardo Rodriguez 22.3% 43.0% 34.8% 7.9% 15.7% 0.361 64.5% 27.0% 5.5% 5.52 3.49 2.03
Andrew Heaney 24.8% 31.6% 43.7% 5.6% 15.6% 0.328 67.9% 28.5% 7.9% 5.38 3.71 1.67
Chris Paddack 21.4% 44.5% 34.1% 2.6% 15.4% 0.332 60.1% 24.2% 5.4% 5.38 3.75 1.63
Mike Minor 20.6% 38.4% 41.0% 11.0% 13.4% 0.305 63.2% 22.8% 7.3% 5.67 4.23 1.44
Jorge Lopez 24.8% 47.7% 27.5% 5.6% 19.7% 0.350 69.9% 21.0% 9.9% 5.95 4.54 1.41
Justus Sheffield 23.2% 45.5% 31.3% 5.2% 18.2% 0.347 65.3% 16.9% 10.0% 6.48 5.12 1.36
Jake Arrieta 24.5% 41.5% 34.0% 4.9% 20.7% 0.308 63.6% 19.0% 10.4% 6.30 4.99 1.31
Aaron Nola 21.5% 40.0% 38.5% 9.6% 14.4% 0.331 71.3% 29.5% 5.4% 4.53 3.26 1.27
J.A. Happ 19.9% 34.2% 45.9% 8.2% 13.9% 0.319 68.2% 18.5% 6.9% 5.90 4.81 1.09
Group Average 22.8% 40.9% 36.3% 7.3% 15.7% 0.334 64.8% 22.5% 7.5% 5.82 4.23 1.59
League Average* 21.2% 43.3% 35.5% 9.6% 14.1% 0.288 72.8% 23.2% 8.0% 4.19 4.20 -0.01
*Only starters are included

Group Averages Comparison
Group LD% GB% FB% IFFB% HR/FB BABIP LOB% K% BB% ERA SIERA Diff
A 19.5% 44.5% 36.0% 11.0% 9.6% 0.245 82.4% 24.6% 7.5% 2.44 3.95 -1.52
B 22.8% 40.9% 36.3% 7.3% 15.7% 0.334 64.8% 22.5% 7.5% 5.82 4.23 1.59
League Average* 21.2% 43.3% 35.5% 9.6% 14.1% 0.288 72.8% 23.2% 8.0% 4.19 4.20 -0.01
*Only starters are included

Surprisingly, these groups aren’t significantly different from an underlying skill metrics basis. Group A (the overperformers) has suppressed line drives and those liners have become ground balls, while Group B (the underperformers) have allowed a higher rate of liners at the expense of grounders. Obviously, you would prefer a lower LD% and higher GB% like Group A has posted, but are those sustainable skills, or mostly just randomness over a relatively small sample size?

We find a bigger difference on the IFFB% side, or pop-up rate. Group A has been significantly more adept at inducing them, while Group B has struggled to do so. There is typically more skill here than on LD%, so I’d chalk this rate gap up as being more sustainable.

Moving along to the luck metric trio, we find our first clue as to why these pitchers find themselves in each particular group. Unsurprisingly, Group A has posted a significantly lower HR/FB rate than both the league average and Group B, which has posted a higher than league average mark. How much of this is home ballpark vs pitcher skill vs luck? Moving along to BABIP, we find a massive difference between the two groups. Sure, Statcast metrics aren’t included here for simplicity sake, but just looking at the batted ball type distribution rates, do you really think the BABIP gap between these two groups deserves to be this large?! Perhaps defensive support differences play a role, which shouldn’t dramatically change, but I would argue this gap is more luck than anything else.

Finally, we round out the luck metric trio discussion with LOB%, the metric that gets the least amount of attention. There’s definitely some skill here that goes above and beyond the obvious drivers (strikeout/walk rates, HR rate, etc), like stolen base attempt and success rates, and underlying skills with runners on vs bases empty. But there’s no way that would explain the entirety of the huge disparity between these two groups.

Last, we move on to strikeout and walk rates. Group A has struck out a higher rate of batters than both the league average and Group B, while both groups have posted identical walk rates.

Combining all the underlying skill metrics, we do find that Group A is a slightly better aggregate of starting pitchers, but it’s actually pretty darn close. It’s interesting to see that Group A overperforms its SIERA by nearly the same amount as Group B underperforms its. And actually, Group B’s pitchers are essentially league average on the whole, as its SIERA is barely worse.

So which group performs better over the rest of the season? Let’s get to the poll questions. Feel free to share your poll answers and why you voted the way you did.


 

 





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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Do you have an overall ranking over where the two groups have finished historically? Which group has been the better bets?