Robert Gsellman’s Ominous Velocity and Spin Trends
Last year, Robert Gsellman came up to the big leagues and helped stabilize an injury-plagued Mets rotation. With a power sinker that had added velocity, the unheralded Gsellman missed bats and generated grounders at an elite level. And after another Steven Matz injury put the lefty’s dependability into question this past spring training, Gsellman was given a prime opportunity to grab a 2017 rotation spot and run with it. To date, however, he hasn’t returned to top form.
For one thing, the results have been ugly. By RA9-WAR, Gsellman has been one of MLB’s worst starters. That once-great sinker whiff rate has been halved. But beyond outcome-level stats, his pitch data indicates worsened stuff. Overall, Gsellman’s sinker is down 0.71 mph, and especially striking are his in-game velocity declines.
Below are LOESS-smoothed curves plotting the difference between the given two-seam fastball velocity and its initial “baseline” in that game — represented, in this case, by the average velocity of the pitcher’s first five two-seamers. By restating velocities like this, each start becomes its own “universe” and we mitigate pitch-tracking biases on the game and park level.

Out of the gate of his 2017 starts, Gsellman’s velocity is dropping. By the 40-pitch mark, he has typically lost 1 mph from his starting speed. As he approaches 80 pitches, his two-seamers are nearly 1.75 mph slower. The orange curve does rebound near its end, but a widened 95% confidence interval reflects a smaller sample of pitches and less certainty that he’ll continue to gain velocity back. Regardless, Gsellman is ending his starts at 1.5 mph off his opening speed. Compared to the dark gray curve for the league — which indicates starts this April in which pitchers threw 20-plus two-seamers/sinkers and 90-plus total pitches — Gsellman’s velocity has tumbled much more steeply.
In-game velocity drops were not such an issue last year. Gsellman’s velocity would actually rise slightly in the first few innings before falling under the baseline once he eclipsed the 30-pitch mark. Whereas Gsellman is spending the bulk of his 2017 starts below his initial baselines, his 2016 velocity descents were gentler and closely aligned with the MLB norm. We do see a steeper downward dive towards the end of the blue curve, but again, smaller pitch totals near the century mark widen the confidence band and limit our certainty.
Notably, Gsellman attributed last Wednesday’s in-game speed drop to tightness. But even if that start is removed, the persistent distance between the 2016 and 2017 confidence intervals shows a significant, worsened trend.
By way of illustration, here’s the same chart as above, but without the April 26 start:

A velocity dip is troubling, of course, for two big reasons. Not only would it portend a fall from his previously rosy outlook, but it may foreshadow an arm injury. Diminished pitch spin is also a major injury predictor, and the news for Gsellman isn’t good on that front, either.
| Pitch Type | 2016 RPM | 2016 Percentile | 2017 RPM | 2017 Percentile |
|---|---|---|---|---|
| Two-Seamer | 2204 | 63rd | 2146 | 54th |
| Four-Seamer | 2170 | 29th | 2141 | 24th |
| Slider | 2376 | 73rd | 2204 | 26th |
| Curveball | 2630 | 78th | 2621 | 67th |
| Changeup | 1589 | 24th | 1565 | 20th |
Gsellman’s spin rates are down across every pitch type. His two least-used pitches — i.e. the four-seam fastball and changeup — have declined less than 30 revolutions per minute, declining by just a few percentile ranking slots. His two-seamer and curveball, however, have lost enough RPM to drop down by some 10 percentile slots. And most glaring of all, Gsellman’s slider has plunged by 172 RPM, enough to fall halfway down the spin rankings.
These trends in velocity and spin hint at an injured pitcher. At the very least, they’re producing a less effective pitcher. It’s not good timing for the Mets, who are now down two starters and have few enticing MLB-ready pitchers in the minors. And it’s not good timing for Gsellman’s pursuit of a lasting big-league rotation job, an opportunity he may be reluctant to pass up. But right now, he looks like a different pitcher, and returning to last year’s promising form will depend on his capacity to regain last year’s stuff.
Gerald Schifman is the lead researcher at Crain's New York Business and a writer at The Hardball Times. He previously worked in the New York Mets' baseball operations department and in Major League Baseball's publishing department. Follow him on Twitter @gschifman.


I wonder what the 2016 MLB data would look like compared to the 2017 data. I only ask because of the switch in tracking systems from 2016 to 2017. If there is a comparable change in the overall league, it may explain the change in Gsellman as well.
Agreed, I’m really curious to see end of season results for spin and velocity because right now I have no idea whether to trust year to year comparisons.
Especially when looking at Four-Seamer and Curve — his numbers are very close to last year, yet he is in a lower 2017 percentile.
Poor Mets fans, way to kick them when they’re down. Usually I would guess that a string of injuries is just bad luck, but to have it happen to the Mets after a couple years of pitchers maxing out innings and velo and experimenting with warthen sliders, this does have the feel of the other shoe dropping
Eh, I mean I think we’ve all known Gsellman isn’t right pretty much since the beginning of the season…
Poor Mets Fans?! We have one of the most exciting organizations in baseball! Every day, we watch a thrilling young starter take the mound, and we wonder, “What injury is he about to have? Could he already be injured? How long will he be out? Will he ever be the same? How good might he have been?”
Watching the Mets is like watching Olympic figure skaters that wipe out every time.
I like these types of graphs. I’m a fan. Thanks!
Did you mean to make that joke or was it punintentional?
That was punny!
I’m a big fan too – I don’t think I’ve seen game-level data presented this way, and I’m fascinated by them. Keep it up!
I didn’t expect to see a LOESS curve anywhere, but it’s a good use of it here. Love it.
Couple things I see looking at his numbers…His BABIP is .377 and his K% & BB% aren’t all that different (a little worse than last year). The LD% is worse than last year, but his Soft/Medium/Hard contact numbers are about the same, too. His LOB% is only 52.5% which is bout to get better.
All in all it looks like he’s a little worse than last year and more unlucky than last year. Also it’s only 21.2 IP so far this year so the sample is pretty dang small.
The above doesn’t mean that the velo numbers aren’t concerning. I’m still relatively optimistic about him this year.
I agree that those indicators are encouraging, but on the other hand he’s giving up a lot of contact and his swinging strike rate is way down. I’m not sure which numbers to trust.
Who knows at this point. It’s only 21 IP. I think there is enough positive to not think he’s gonna stink all year, and he could possibly be much better.
This whole article is excellent. Just excellent. Mr. Schifman, I look forward to seeing more of your work here.
Hey, I know it’s free content, but I hope we can soon get past “this hints at injury” with a completely unknown size of hint.
In 2016, what % of pitchers who showed at least this signal in April ended up injured? What % of pitchers without this signal ended up injured?