Trevor Bauer’s (Deserved) Down Year

Trevor Bauer, the National Fantasy Baseball Championship’s No.-9 starting pitcher and No.-31 player overall, has pitched to the tune of a 4.12 ERA this year. All things considered (“things” being, primarily, the juiced ball), Bauer hasn’t been awful. But after compiling a pristine 2.21 ERA in last year’s breakout with equally pristine ERA estimators to boot (3.14 xFIP, 3.21 SIERA), this year’s peripherals (4.35 xFIP, 4.21 SIERA) are far less inspiring, even when adjusted for context.

The easiest way to write off Bauer’s 2018 season as an aberration is, well, to look at everything else he has ever done. He sports a career 3.97 ERA, with just one season (2018) with an ERA under 4.00. The blind squirrel who took an approach as simplistic as this in 2019 would have invariably found a nut.

Such an approach, however, would grossly undersell Bauer’s gains in 2018, which were quite legitimate. Using the most basic of peripherals, Bauer’s swinging strike rate (SwStr%) took the best 3rd-biggest step forward in nominal terms, behind only Patrick Corbin (and his slider) and Gerrit Cole (and his fastball).

Yet 2018 gains do not necessarily beget sustained excellence. Bauer’s narrative is a fairly complex one, so let’s give it proper attention.

For all intents and purposes, Bauer’s breakout technically occurred in 2017. Despite a 4.19 ERA, Bauer, for the first time in his career, sported ERA estimators better than 4.00 (3.60 xFIP and 3.80 SIERA). For those using xFIP and SIERA as leading indicators (or, conversely, for those who thought his .337 BABIP and 16.1% HR/FB screamed of bad luck), 2017 was the first forecast of success on the horizon.

Ironically, such faith in a breakout may have been misplaced, at least given the information available to us. Bauer’s 9.2% swinging strike rate, surely nothing to write home about, is one shorthand way of highlighting his good fortune in 2017. Using the methodology outlined here, in which I used pitcher plate discipline to find regressed strikeout rates, Bauer was 2017’s 2nd-luckiest qualified pitcher by “deserved” strikeout rate:

  1. +6.6% — Jose Quintana
  2. +5.4% — Trevor Bauer
  3. +3.9% — Justin Verlander
  4. +3.8% — Chris Sale
  5. +2.4% — Gio Gonzalez

Given a couple of the marquee names there (Verlander and Sale, namely), it begs the question: are some pitchers capable of outperforming their deserved strikeout rates? In short, yes. Bauer finds himself among this group, having outperformed his actual strikeout rate by roughly 2.5 percentage points since 2014, when he first began pitching first time.

Still, that means Bauer outperformed his strikeout rate by roughly 3 percentage points in 2017. The difference between strikeout rates of 23% and 26% for a budding ace is sizable, if not massive, especially when paired with a relatively high walk rate (8.0%). If you correct for his deserved strikeout rate, Bauer’s 2017 ERA estimators creep back above 4.00. I stand by this hindsight-is-20/20 hot take: betting on a Bauer breakout in 2018 was a fool’s errand. That he rewarded those who trusted his surface-level improvements is merely coincidence (which I’ll explain in a second).

At this point, I can abandon discussion of deserved strikeout rates. In 2018 and 2019, my regression model suggests Bauer had (and has) outperformed his 2018 and 2019 strikeout rates by almost identical margins of roughly 2.5 percentage points, aka his usual. There’s no reason, from where I’m sitting, to believe Bauer has been particularly lucky or unlucky this year or last. That means, however, that the model validates Bauer’s down year, at least by virtue of his strikeout rate (something also to be explained shortly).

Fast forward to 2018. Bauer ditched his two-seam fastball (a truly terrible pitch) and displaced it with a vicious slider and highly improved cutter. The cutter, with an .313 expected weighted on-base average (xwOBA) in 2017, arguably represented Bauer’s best opportunity to optimize his arsenal given existing tools. The slider, thrown only 36 times in 2017, was a wild card, one that proved to be potentially career-saving: it was baseball’s best pitch by wOBA (and 3rd-best by xwOBA) among almost 700 — seven hundred — pitches thrown at least 350 times last year. In other words, Bauer added an elite weapon basically out of nowhere (which, alas, is why I maintain that bets on a 2018 breakout were blind-squirrelesque).

So, what happened in 2019? It’s not as if Bauer lost his slider or cutter. In fact, he’s using both more often, increasing their aggregate usage from 24% to 30%. It is, however, as if they have both declined fairly dramatically in effectiveness. Both pitches boasted whiff rates north of 20% last year but have since fallen off:

Trevor Bauer’s SwStr%
2018 2019
Pitch Type # Thrown SwStr% # Thrown SwStr%
Four-Seamer 1,051 7.5% 1,068 9.5%
Knuckle Curve 762 15.4% 585 13.0%
Slider 391 21.5% 435 17.8%
Cutter 298 21.1% 432 12.9%

Having successfully buried the lede, this table looks a whole lot worse when you incorporate his average pitch velocities:

Trevor Bauer’s SwStr% and Velo
2018 2019
Pitch Type # Thrown Velo SwStr% # Thrown Velo SwStr%
Four-Seamer 1,051 94.6 7.5% 1,068 94.7 9.5%
Knuckle Curve 762 79.2 15.4% 585 79.2 13.0%
Slider 391 82.0 21.5% 435 79.6 17.8%
Cutter 298 86.8 21.1% 432 84.5 12.9%

Bauer has lost multiple ticks on his slider and cutter, whether intentionally or unintentionally. By no small coincidence, both of those pitches have declined in effectiveness by measure of not only whiffs but also quality of contact allowed: from 2018 to 2019, the xwOBA on contact declined by 35 points for his cutter (.301 to .336) and 40 points for his slider (.283 to .323). The combination of more contact and harder contact have made Bauer far more vulnerable than he was last season. Here’s that table, one last time, with the addition of overall xwOBA (not just on contact) and a nifty subtotals row at the bottom:

Trevor Bauer’s Everything
2018 2019
Pitch Type # Thrown Velo SwStr% xwOBA # Thrown Velo SwStr% xwOBA
Four-Seamer 1,051 94.6 7.5% .369 1,068 94.7 9.5% .384
Knuckle Curve 762 79.2 15.4% .245 585 79.2 13.0% .247
Slider 391 82.0 21.5% .136 435 79.6 17.8% .214
Cutter 298 86.8 21.1% .283 432 84.5 12.9% .358
Overall 13.2% .259 12.1% .306

It’s too easy to call Bauer’s 2018 season an outlier on the basis of ERA alone. While obviously a 2.21 is insane, his ERA estimators (not to mention his 5.8 wins above replacement) painted the portrait of a bona fide ace. Bauer’s 2019 season hasn’t been quite as kind of him, and his proponents might hold out hope on a return to his 2018 form, either later this year or in 2020.

It seems unwise, however, to hope for a full rebound given evidence of declining velocity not only between the 2018 and 2019 seasons but also within the 2019 season itself (average cutter velocity by month: 85.0, 85.1, 84.0, 84.3, 83.3). If the success of his secondary offerings are tied strongly to their velocity, it then becomes a waiting game of when, or even if, those pitches will rebound to their 2018 potential.

There’s also a pessimistic argument to be made that Bauer, despite his ERA estimators describing a pitcher who elevated himself to ace status, benefited from good luck even on the basis of contact quality (that is, “deserved” outcomes per Statcast’s measurements). A player’s true talent level is an always-moving target, which is why we resort to a player’s peripherals to help us cut through the noise. But peripherals (such as plate discipline and contact quality allowed) are also moving targets in and of themselves. On all fronts, baseball is a game of peaks and valleys, ebbs and flows.

Whether or not you subscribe to the pessimistic view of Bauer’s 2018 success, one thing is for certain: two of his better offerings have backpedaled immensely at the same time each has ceded 2+ mph in average velocity. There are always other factors at play, but velocity seems to me to be the primary culprit.

Most interestingly (and, perhaps, most crucially), Bauer’s fastball velocity remains intact. This suggests to me Bauer’s dips in velocity on his secondaries are deliberate — or, if not deliberate, then at least controllable, fixable. It gives me hope for the possibility of another sub-4.00 ERA season from Bauer in the future, even in the juiced-ball era.

As for the remainder of the 2019 season, I wouldn’t count on it — not until I see tangible changes to the complexion of his breaking and off-speed assets.

We hoped you liked reading Trevor Bauer’s (Deserved) Down Year by Alex Chamberlain!

Please support FanGraphs by becoming a member. We publish thousands of articles a year, host multiple podcasts, and have an ever growing database of baseball stats.

FanGraphs does not have a paywall. With your membership, we can continue to offer the content you've come to rely on and add to our unique baseball coverage.

Support FanGraphs




Currently investigating the relationship between pitcher effectiveness and beard density. Biased toward a nicely rolled baseball pant. Reigning FSWA Baseball Writer of the Year and 5-time award finalist. Featured in Lindy's Sports' Fantasy Baseball magazine (2018, 2019). Now a Tout Wars competitor.

newest oldest most voted
soddingjunkmail
Member
soddingjunkmail

” it begs the question: are some pitchers capable of outperforming their deserved strikeout rates? In short, yes.”

Hard to say this without sounding snarky (but I’m making an honest attempt):

Doesn’t this really say that the “deserved” metric isn’t doing a very good job of calculating what they deserved?

EDIT: And I should add – articles like this are exactly why I come to fangraphs. Real analysis of an interesting question (Which is the real Trevor Bauer?) with a plausible and data supported reason found. Bravo.

carter
Member
carter

Maybe I do not understand this correctly, but doesn’t it stand to reason that pitchers change their arsenal in strike out situations?

Mike Podhorzer
Editor
Member

I’m not Alex, but as a developer of another xK% metric, and other expected metrics as well, every metric in the “expected results” family is going to miss on outliers. I’m not sure it’s possible to hit on every single player accurately. Typically, it will work for like 95% of players, while the remaining 5% are going to be at the extremes that “break” the metric. It’s likely because they are doing something else we aren’t accounting for, and to this date, haven’t figured out what that is and/or how to quantify it to incorporate it into our equations.