Zach Britton Has Actually Been Unlucky

Hopefully there aren’t too many of you out there suffering from Zach Britton fatigue. Last month, our own Corinne Landrey wrote about his potential for an all-time great season, and then shortly thereafter the baseball-writing community collectively began taking turns crafting the individual arguments for his Cy Young — and even MVP — candidacy, before the pushback began. We had our Zach Britton week, and all was good and fun. In reality, however, the chances of him winning — or even making a serious run at — the Cy Young Award seems highly unlikely.

But the first inaugural Zach Britton Cy Young Discussion Week still provided the framework for a few days of thought-provoking arguments and gave us something interesting to ponder. Now, here’s something else to think about: what if, in Zach Britton’s already potentially all-time great season, he’s actually been unlucky?

We know the typical indicators of good fortune:

  • A lower ERA than FIP. Britton’s ERA is 1.44 runs lower than his FIP, the 11th-largest negative difference of any qualified reliever.
  • An abnormally high strand rate. Britton’s 88.2 LOB% is the highest of his career, and the fifth-highest of any qualified reliever.
  • An abnormally low batting average on balls in play. Britton’s .214 BABIP is the lowest of his career, and the fourth-lowest of any qualified reliever.

On first glance, one might glance at Britton’s player page, observe those three facts, and figure Britton’s been the recipient of good fortune. But by taking things a step further, we can entertain the idea that not only has Britton earned those numbers above, but that he’s actually deserved better.

Over on BaseballSavant, there’s a relatively recent feature that creates an expected batting average for any given ball in play, based on the batting averages of batted balls with a similar combination of exit velocities and launch angles. Using this, one can search for all the balls in play within the given parameters of an expected batting average. So, for example, if one were interested in finding what one might deem as “unlucky” hits, one could search for all balls in play, with an expected batting average of .270 (one standard deviation below league average) or worse, which led to hits. And then, one could take the results of that search and divide each number of “unlucky” hits by that pitcher’s total number of hits allowed, to create a leaderboard sort of displaying which pitchers have had the highest percentage of their hits be of the “unlucky” variety.

That hypothetical is all very real, and the very real leaderboard looks like this:

Unlucky Hit Leaders
Name Total Hits “Unlucky” Hits Unlucky Hit%
Jerry Blevins 38 10 26.3%
Zach Britton 35 8 22.9%
Eric O’Flaherty 43 9 20.9%
Clayton Richard 73 15 20.5%
Andrew Miller 44 9 20.5%
Kenley Jansen 31 6 19.4%
Blaine Boyer 83 16 19.3%
Dylan Floro 26 5 19.2%
Dan Otero 58 11 19.0%
Zach Duke 49 9 18.4%
SOURCE: BaseballSavant
“Unlucky” Hits: Hits on balls in play with an expected batting average less than or equal to .270, based on exit velocity and launch angle
-Minimum 25 total hits allowed

Sure, this post could’ve been about Jerry Blevins, but who really wants to read about Jerry Blevins? Britton, obviously, makes for the more compelling story, and Britton is the first name behind Blevins. So Britton it is.

So, we see Britton’s name, and we understand that his mark of 35 hits allowed is already pretty ridiculous as is, but then we also see that eight of those 35 hits came on balls in play with an expected batting average one standard deviation or more below league average.

Hits which came off the bat at 85 mph on the ground and were the happenstance result of perfect placement:

Or hits which came off the bat at 74 on the ground and were the result of the first baseman playing in front of the runner instead of behind him, giving him an insufficient amount of time to make a play on the weakly hit ball:

Or glorified bloops off the end of the bat at 76 which turn into doubles thanks to a combination of fortunate placement and what I’ll generously refer to as a “suboptimal” route by right fielder Joey Rickard, who accumulated -5 DRS and -5 UZR in fewer than 300 innings in right field this season:

Of course, batted ball angle isn’t included in any of this, making it an admittedly rough way to measure “unlucky” hits, a subjective term to begin with. But we can still attempt draw a couple different conclusions from this. One is that Britton has, in fact, been an unlucky pitcher this season, despite what the more surface-level “luck” indicators suggest, and that Britton’s numbers ought to be better. Turn all eight of Britton’s unlucky hits into outs and that .214 BABIP turns into a laughable .159. Even half makes it .187. The 0.83 WHIP becomes an even more absurd 0.69 (shut up). Only one of the eight “unlucky” hits turned into an earned run, but then again he’s only allowed four all year, so the ERA drops from 0.61 to 0.46. That one run might be the difference between Britton setting the all-time ERA record or not.

The other conclusion we can draw is that this is actually a feature, and not a bug. You might recall a post I wrote over the winter detailing the circumstances surrounding Britton’s four blown saves in 2015. Essentially, each blown save was the direct result of multiple defensive miscues and/or soft contacts which led to hits, similar to what we saw above. Britton is still yet to blow a single save this season.

Maybe what we’re seeing here isn’t so much a byproduct of poor fortune so much as it is a byproduct of the way Britton pitches. A testament to the extreme nature of his weak ground-balling tendencies. An implication that the only way to beat this year’s version of Zach Britton is to get lucky, and even then, you probably won’t win.

We hoped you liked reading Zach Britton Has Actually Been Unlucky by August Fagerstrom!

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August used to cover the Indians for MLB and, but now he's here and thinks writing these in the third person is weird. So you can reach me on Twitter @AugustFG_ or e-mail at

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Interesting that the first 5 names on that unlucky hits leaderboard are lefties


They’re also (mostly, not Kenley) predominantly groundball types. Get more groundballs, get more variance. Not a shocking leaderboard, I just don’t know if it really says all that much, but I think it’s an interesting use of the data.