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Let’s play an old game of Rob Neyer’s. Compare these two anonymous people:

  • Player A: 96.2 IP, 6.0 K/9, 2.3 BB/9, 4.13 DRA, 101 cFIP
  • Player B: a reader trying not to fall into a disinterest-based coma

Last spring, Jesse Hahn was treated as a bit of a sleeper, if only in the fantasy circles, thanks to his mild upside and the limitless opportunity of the Athletics rotation. He grasped that low bar and held it firmly, starting 16 games for a last-place team and slowly improving before getting shut down with a forearm strain in early July. With 1.0 WARP in half a season’s work, Hahn was as close as it gets to a league-average starter; his cFIPs of 102 and 101 in his two seasons of work confirm the suspicion going forward.

PECOTA, on the whole, is somewhat critical:

Given the finite nature of life and the weight of opportunity cost, we would ordinarily scan these numbers, nod, and move on. But then we come to the last line: Breakout 35%, Improve 65%, Collapse 17% – Comparables: Alex Cobb, Manny Parra, Dana Eveland. The statistically uninteresting Hahn is most similar to one of the best pitchers in the American League (at least, he was before his Tommy John surgery), and two famously bad pitchers with ERAs in the mid-to-high sixes.

This is where the average projection system lets us down, and where PECOTA’s percentiles offer a glimmer of insight. Hahn’s baseline is mediocre not because he’s boring, but in fact the opposite—his mean is dull, but his variance is incredibly high. His 10th and 90th percentile projections offer nearly a five-WARP gap. He could be anything.

To put in perspective: Hahn’s worst-case scenario is worse than the worst conceivable Ubaldo Jimenez, and his best-case outcome is better than the best-case Taijuan Walker. His complete list of comparables teems with breakout success stories (2014 Garrett Richards! 2012 Homer Bailey! 2011 Justin Masterson!) and generational disappointments (2006 Lenny DiNardo! 2015 Matt Moore! Any Daniel Cabrera!) Eight of Hahn’s 100 comps had ERAs of zero, which would be fantastic if they didn’t also have inning counts of zero; all eight fell under the knife, a fate that Hahn himself is at no small risk of sharing.

It makes sense, really, because Hahn is an amalgam of so many tiny pieces of pitcher, a photomosaic of tools and flaws. Despite his size, Hahn rarely graced prospect lists in his youth, partially because of a post-draft Tommy John but mostly because of his inability to master a third pitch; without a dominant fastball, he appeared doomed to long relief. He escaped his destiny by wielding a platoon-defying hard curve as an out pitch, using it to strike out a batter an inning with his 2014 stint with the Padres.

Then, in 2015, he became a completely different pitcher. Batters stopped chasing the curve out of the zone, lowering their swing rate from 48.5 percent to 35.8 percent, and thus making contact with it 10 percentage points more often. And when they did, they were often satisfied with the results, raking a 35 percent line drive rate against it. Hahn basically outperformed his peripherals by two-thirds of a run while displaying a batted ball profile that ordinarily goes the opposite way. And yet for all the line drives, only three amounted to extra bases, all doubles. Which part was the luck?

Hahn’s success leading up to the end of his season correlated with his curtailing of the curve and leaning on his fastball, which he threw with sudden, unexpected pinpoint control. Despite the massive drop in strikeouts, he also saw a similar decline in walks, and became reliant (successfully so) on democratic baseball, letting the fielders behind him do their jobs, and also Marcus Semien. It’s good to see such bravery rewarded.

Given this strange profile, it’s easy to see both the pieces, both good and bad, of his short major-league tenure interlocking. Imagine 2015 Jesse Hahn with 2014 Jesse Hahn’s curveball! Imagine 2014 Jesse Hahn getting killed by 2015 Jesse Hahn’s batted ball profile! Imagine 2016 Jesse Hahn coming down with 2015 Jesse Hahn’s mystery forearm strain! The latter, sadly, is all too easy to imagine.

Pitchers are fun because they’re so often required, by batters and by their own sinew, to reinvent themselves. Hahn has already seen his share of adversity and, despite it all, still gets to work. It’s an encouraging profile from a personal standpoint, if not a statistical one, but if nothing else it makes Hahn far more interesting than your average average pitcher.

Thank you for reading

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brentdaily
2/22
Why are the breakout/collapse scores so much higher for pitchers than hitters? Hitters top out in the mid-teens, pitchers in the forties. Mix of volatility and confidence level? Or something else? Thanks.
euqubudhp
2/22
Volatility, mostly. Hitters are fairly predictable; pitchers can master a new pitch (Jake Arrieta) or lose one (Tom Wilhelmsen a couple years back), and their injuries tend to be more unpredictable and more damaging.
fbraconi
2/22
I agree- the best feature of PECOTA relative to other projection systems is its percentile breakdowns.
apaterson
2/22
Does PECOTA know that Hahn announced he was going to stop throwing his slider completely due to ongoing arm problems? It will be hard for him to break out without his best offspeed pitch.

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RotoWire News: Hahn will scrap the slider from his pitch arsenal this season, John Hickey of the Bay Area News Group reports. "We tried some things and I think it was the slider causing problems. At the very least, I know it wasn't helping my arm, so I'm going to go without it and incorporate the changeup more," said Hahn on Sunday. (2/21/2016)
Slinkey1998
2/22
He threw the slider 4.7% of the time last season. I don't think it'll be too great a loss, especially if it helps him stay healthy.
Kinanik
2/22
What are the historical results of the top breakout % player?
euqubudhp
2/22
Good question. I can only go back a couple years with the tools I have on hand:

2015: Wily Peralta/Robbie Ray (45%)
2014: Jeanmar Gomez (45%), Zach Britton / Garrett Richards (44%)

I may be wrong on the methodology (I'm probably wrong), but I believe the lower overall breakout rates across the board stem from a larger sample of comparables that PECOTA chooses from this year, flattening things out a bit.