Buy ‘Em or Deny ‘Em: Does A Regression Loom For These “Lucky” Pitchers? (Sean Manaea & More)

by Connor Henry

Last week we took a look into some pitchers who are suffering from inflated BABIP, so this week I wanted to dive into some pitchers who are benefitting greatly from low BABIP. Like I said last week, determining whether pitchers have regression coming to their BABIP comes down to the Batted Ball data that they tend to have control over. We will specifically look at:

  1. Inducing Soft Contact > League Average 18%
  2. Limiting Hard Contact < League Average 35.5%
  3. Generating Infield Fly Balls (IFFBs) > League Average 10.4%

The ability to accomplish those three batted ball tendencies would lead me to believe that a pitcher can sustain a below league average BABIP (.293).

 

Sean Manaea – Oakland Athletics
Still only 26, Manaea has long been accused of not living up to his potential. However, through 117 innings in 2018 he is carrying a 3.44 ERA to go along with an incredible 0.99 WHIP, the latter being tied for 8th best in baseball out of qualified pitchers. So what has changed? One of the first things you see when you look into his stats is that he is currently sporting a .223 BABIP, lowest in f baseball. This comes a year he had a .318 BABIP, a monumental 100 batting average points higher! Let’s break down his batted ball data in comparison to last year:

  1. Soft Contact % (2017/2018): 15 / 14
  2. Hard Contact % (2017/2018): 33 / 39
  3. IFFB % (2017/2018): 7 / 9

What becomes painstakingly clear after looking at those numbers is that he has actually regressed in two of the three categories from last year. His hard hit rate has increased to above league average and his soft contact rate drags a good deal below league average. The one marginal improvement in his batted ball data is the ability to generate automatic outs with infield pop-ups, but even that continues to sit below league average. For reference, let’s take a look at how all of his batted ball data compares to Carlos Carrasco.

Player
LD%
GB%
FB%
IFFB%
Soft%
Hard%
BABIP
Sean Manaea22443591439.223
Carlos Carrasco22433681436.311

Incredibly almost all of the batted ball data shows that they are inducing similar contact. Even the category with a slight discrepancy shows that Carrasco is limiting hard contact more effectively than Manaea, yet their BABIP sit about 90 points apart. The only reasoning that can be made to justify this could be their home ballpark. Oakland Coliseum is known as a pitchers’ park while Progressive Field (the Indians home park) is considered a hitter’s park. Nevertheless ballparks, even Coors Field, do not account for a 100-point difference in BABIP.

Verdict: Manaea, by all accounts, is having a breakout year. His ERA and WHIP tell the story of a pitcher who has made vast improvements and is fooling hitters consistently. However, after looking closely into the data it is very clear that his .223 BABIP is unsustainable and a regression is coming. While the ratios may look stellar halfway through the season, Manaea has experienced great fortune and selling while you can may be a move worth looking into.

 

Kyle Freeland – Colorado Rockies
Like any other Rockies pitcher, Freeland has been hard to trust and prone to rough outings throughout his young career. What we’ve seen out of him this year has led to some optimism. He currently owns a 3.18 ERA to go along with a 1.21 WHIP, both improved from last season. The other statistic that is lower this year happens to be his BABIP. Last season he suffered from a .308 BABIP, which is about 10 points above the league average, while this year his BABIP sits at a fantastic 0.265. Can we trust it?

  1. Soft Contact % (2017/2018): 24 / 22
  2. Hard Contact % (2017/2018): 32 / 29
  3. IFFB % (2017/2018): 11 / 8

Freeland has an extremely useful ability to induce soft contact. He has always been known as a groundball pitcher, so when you pair that with the ability to create soft contact, easy groundball outs can come in bunches. He also has a knack for limiting hard contact, which is especially helpful in Coors Field. Unfortunately this year he has regressed a bit when it comes to generating pop-ups, but the other data is encouraging enough to overlook that. Just like last week, let’s reference Aaron Nola’s batted ball data so that a comparison can be drawn.

Player
LD%
GB%
FB%
IFFB%
Soft%
Hard%
BABIP
Kyle Freeland18483482229.265
Aaron Nola2050301521426.262

The similarities are quite interesting. Freeland is producing groundballs and flyballs at a rate similar to Nola while limiting hard contact and inducing soft contact just as well. Certainly his IFFB rate does not compare as harmoniously, but all things considered these two pitchers are inducing similar contact and have therefore matched each other with equally low BABIP. I do not mean to say that Freeland is as good as Nola, I am simply stating that their batted ball data leads me to believe that they can both sustain similarly low BABIP.

Verdict: Freeland is by no means an ace. His 3.18 ERA is a bit lower than his 4.12 FIP and his 82% Left on Base rate is due for some regression because he lacks the strikeout upside of high-end pitchers. However, I do believe he is a pitcher who can regularly out perform his peripherals. Due to his, dare I say, Nola-like batted ball data it is very easy to picture a world where Freeland can sustain a BABIP below league average. While I do believe that some regression could be coming to his BABIP (maybe .275 range) because of Coors Field, I also believe in his ability to limit hard contact and induce weak contact and therefore believe that he can consistently out perform his peripherals.

Sources: Fangraphs, Brooks Baseball

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