Daddy Hacks or: The Lone Peril of Swinging Too Onerous

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Jay Biggerstaff-USA TODAY Sports activities

I can’t presumably start to cowl all the wonderful work regarding Statcast’s new bat monitoring knowledge. Now as a lot as ever, it’s necessary to help your native Baseball Prospectuses, PitcherLists, Baseball Americas, FanGraphses and freelance Substack writers. We transfer rapidly in these components. There’s a lot evaluation to eat, all of it excellent.

When confronted with this new knowledge, considered one of my first instincts was to see which metrics from different areas of sabermetric evaluation might be replicated throughout the bat monitoring framework. Enter Ninetieth-percentile exit velocity (90EV); it’s a strong shorthand metric that distills loads of details about the highest finish of a hitter’s exit velocity distribution right into a single quantity. It’s not good, and different metrics outperform it, nevertheless it’s simple to see the way it has grow to be well-liked in up to date evaluation, particularly in prospecting and scouting circles.

So I regarded to 90EV for inspiration with respect to bat pace. I assumed bat pace, being a major enter to exit velocity, would exhibit comparable strengths in characterizing a hitter’s distribution of bat speeds by consolidating probably the most essential speeds right into a single worth. Certainly, parsing bat speeds into deciles seems to work very well:

Bat Pace Percentiles

Bat Pace Decile Avg EV Contact% Barrel% Sq. Up% Blast% xwOBAcon
0th as much as Tenth 71.2 65.4% 0.1% 36.3% 4.3% .130
Tenth as much as Twentieth 77.2 78.2% 1.3% 39.5% 8.5% .191
Twentieth as much as Thirtieth 78.9 78.9% 2.9% 36.9% 11.5% .232
Thirtieth as much as Fortieth 80.5 79.2% 3.5% 36.5% 13.4% .256
Fortieth as much as Fiftieth 82.1 78.8% 5.5% 37.2% 16.0% .284
Fiftieth as much as Sixtieth 83.3 79.3% 7.2% 37.4% 18.5% .307
Sixtieth as much as Seventieth 84.6 78.1% 8.3% 38.6% 20.1% .322
Seventieth as much as Eightieth 86.2 78.0% 12.1% 39.6% 23.3% .369
Eightieth as much as Ninetieth 87.7 77.6% 11.9% 40.9% 25.3% .377
Ninetieth by A hundredth 88.5 82.3% 13.8% 40.4% 29.2% .404

Common exit velocity will increase linearly with bat pace. So does contact high quality (xwOBA on contact, or xwOBAcon) and barrel fee (Barrel%). All of those developments meet expectations. What defies expectations, nonetheless, is that contact fee (Contact%) spikes for a hitter’s high 10% of bat speeds. Whereas bat pace correlates positively with whiffs (that’s, extra bat pace usually means extra whiffs), the common hitter’s quickest swings evidently produce extra contact, not much less, and by a considerable margin besides. That’s an incredible collective feat. It’s just like the numeric equal of “seeing seaside balls.”

There’s extra to this than meets the attention. Why is that this doable? Let’s view the predicament by the lens of physics. Do you bear in mind physics? One factor I bear in mind — along with spending an inordinate period of time throughout a number of days with my buddy Kevin attempting to bounce an empty plastic apple juice bottle on its facet to get it to land upside-down on its cap — is that pressure equals mass instances acceleration. Not velocity, however acceleration. The everyday swing begins at an preliminary velocity of zero and makes contact at a ultimate instantaneous velocity of X (on this case, “Bat Pace”). To achieve X mph from 0 mph, the bat should speed up. How a lot the bat accelerates determines how a lot pressure the hitter imparts upon the ball. And what’s a hitter’s major job if to not impart pressure upon an unsuspecting, unassuming baseball?

The bat monitoring knowledge from Statcast doesn’t embrace mass (i.e., the load of the bat), and we barely have acceleration. At finest, we should make a flawed assumption that bat acceleration is fixed all through a hitter’s swing. (We make the identical assumption for a pitch’s motion by house — how dangerous might it’s? Perhaps don’t reply that query.) I cobbled collectively some crude acceleration estimates primarily based on bat pace and swing size utilizing my extraordinarily time-withered recounting of Eleventh-grade physics as a Martinelli’s bottle tumbled by my mind. Villain origin story apart, what relevance is acceleration if we’ve ultimate pace? Particularly, we are able to use acceleration to diagnose variations in seemingly equivalent bat speeds. Think about two swings with bat speeds of precisely 75 mph, but one swing is just seven ft lengthy, the opposite eight ft. We are able to assume the previous swing needed to speed up extra rapidly throughout a smaller distance to achieve the identical instantaneous velocity on contact because the latter.

So as a substitute, how do a hitter’s bat acceleration deciles correspond with varied measures of manufacturing? A lot otherwise:

Bat Acceleration Percentiles

Bat Acceleration Decile Avg EV Contact% Barrel% Sq. Up% Blast% xwOBAcon
0th as much as Tenth 68.8 52.9% 0.3% 25.5% 3.5% .112
Tenth as much as Twentieth 76.2 67.0% 1.7% 31.8% 7.6% .177
Twentieth as much as Thirtieth 79.2 76.2% 3.3% 37.3% 12.1% .232
Thirtieth as much as Fortieth 81.1 81.2% 5.2% 40.5% 15.7% .277
Fortieth as much as Fiftieth 82.8 84.3% 6.8% 42.8% 19.3% .311
Fiftieth as much as Sixtieth 83.9 84.3% 8.9% 42.7% 20.5% .333
Sixtieth as much as Seventieth 85.1 85.3% 9.3% 44.8% 23.2% .351
Seventieth as much as Eightieth 85.7 84.5% 10.2% 43.4% 23.3% .363
Eightieth as much as Ninetieth 86.4 80.9% 11.0% 40.2% 23.0% .368
Ninetieth by A hundredth 86.4 79.6% 10.3% 34.9% 22.2% .350

In transferring from the penultimate decile to the highest decile, the league-average exit velocity plateaus at 86.4 mph (reasonably than persevering with to extend linearly). Contact charges peak nearer to someplace between the Sixtieth and Seventieth percentiles, as does Statcast’s new square-up proportion (Sq.-Up%). Barrels peak under the Ninetieth percentile, as does Statcast’s new Blast fee metric (Blast%), in addition to our tried-and-true xwOBAcon. The feel of assessing swing efficacy (by the perspective of a single bat monitoring measurement) has modified solely.

All of which is to say that daddy hacks — true swing-out-of-your-shoes daddy hacks — maybe aren’t one of the simplest ways for a hitter to optimize his offensive manufacturing. Which isn’t to say that daddy hacks aren’t good, productive swings — they’re nonetheless among the many most efficient swings a hitter could make, and a hitter must err on the facet of an excessive amount of acceleration reasonably than not sufficient — however it is a query of optimization, not magnitude.

What, then, is one of the simplest ways to optimize? What’s the best mixture of bat pace and bat acceleration, utilizing this unsophisticated percentile framework? It’s someplace within the red-highlighted space under, which is usually not the place a hitter maximizes his acceleration:

Bat Pace x Bat Acceleration: xwOBAcon

Acceleration →
↓ Pace
0th-Tenth Tenth-Twentieth Twentieth-Thirtieth Thirtieth-Fortieth Fortieth-Fiftieth Fiftieth-Sixtieth Sixtieth-Seventieth Seventieth-Eightieth Eightieth-Ninetieth Ninetieth-A hundredth
0th as much as Tenth .113 .187 .166 .160 .143 .129 .083 .076 .000 .123
Tenth as much as Twentieth .121 .223 .239 .233 .202 .188 .172 .131 .083 .051
Twentieth as much as Thirtieth .095 .184 .283 .298 .288 .238 .261 .224 .158 .071
Thirtieth as much as Fortieth .060 .150 .264 .312 .336 .286 .286 .263 .207 .113
Fortieth as much as Fiftieth .004 .119 .246 .320 .341 .352 .348 .297 .255 .144
Fiftieth as much as Sixtieth .012 .099 .216 .324 .355 .347 .363 .333 .285 .242
Sixtieth as much as Seventieth .000 .057 .134 .272 .364 .382 .358 .354 .347 .234
Seventieth as much as Eightieth .000 .119 .116 .233 .323 .401 .413 .436 .397 .336
Eightieth as much as Ninetieth .000 .210 .105 .108 .234 .382 .386 .435 .436 .360
Ninetieth by A hundredth .426 .000 .247 .145 .216 .253 .379 .402 .455 .410

It is the place he maximizes bat pace, however by an extended swing that permits extra time to speed up (at a barely decrease fee of acceleration) to its most pace. That’s not one thing you may glean from bat pace alone. As such, top-10% bat pace as a 90EV-equivalent metric merely doesn’t seize the knowledge we would like it to seize, at the very least not in its entirety.

The answer to the issue of optimization vis-à-vis contact high quality for any hitter, no matter measurement and energy, is to attenuate swing size for any given bat pace (pink = excessive common exit velocity, blue = low).

To be clear, lengthy swings aren’t dangerous; actually, an extended swing (in distance, not time) tends to indicate extra distance throughout which to speed up, which naturally creates extra bat pace. You possibly can truly see that longer swings are related to greater bat speeds and better exit velocities. But when a hitter can obtain the identical bat pace with a shorter swing, he’ll inherently generate extra acceleration.

Presumably not all hitters take daddy hacks on the similar frequency. On the similar time, I can’t with any confidence attest to which hitters take extra daddy hacks than others. Understanding what we learn about them, I doubt Steven Kwan takes anyplace close to as many daddy hacks as Javier Báez. This is the reason I’ve taken care to discuss with league averages and “the everyday hitter.” At what threshold above a hitter’s common bat pace do contact fee and high quality begin to degrade? Does that threshold change from hitter to hitter?

As for daddy hacks themselves, each bat pace and acceleration correlate instantly with ball-strike depend. Bat pace and acceleration peak when the depend is most of their favor (3-0), and reduce steadily because the depend turns into much less favorable, with hitters’ slowest swings occurring in 0-2 counts. It’s in these advantageous counts that hitters presumably do themselves a disservice (simply barely a disservice, however a disservice nonetheless) by taking daddy hacks reasonably than taking a bit off it to make sure they sq. it up a bit higher — to make sure the chaos is actually managed:

xwOBAcon by Bat Acceleration and Rely

Bat Acceleration Decile Forward Even Behind Two Strikes
0th as much as Tenth .225 .221 .245 .081
Tenth as much as Twentieth .275 .257 .287 .135
Twentieth as much as Thirtieth .311 .305 .295 .179
Thirtieth as much as Fortieth .343 .344 .320 .216
Fortieth as much as Fiftieth .373 .359 .355 .252
Fiftieth as much as Sixtieth .390 .395 .363 .263
Sixtieth as much as Seventieth .428 .393 .398 .277
Seventieth as much as Eightieth .441 .407 .393 .285
Eightieth as much as Ninetieth .467 .433 .407 .265
Ninetieth by A hundredth .455 .408 .348 .255

The perfect swings, then, seem like those who enhance bat pace by acceleration reasonably than swing size, impartial of pitch location. I say “impartial of swing location” as a result of swing size correlates with lateral (east-west) pitch location, with inner-half pull-side approaches yielding longer swings. The red-and-blue jelly bean above reveals that swing size is positively correlated with exit velocity, so it is sensible that pull-side swings yield excellent outcomes. They not solely benefit from a shorter outfield wall distance but additionally allow the hitter to generate extra bat pace throughout an extended swing distance. Two swings with equivalent charges of acceleration will produce completely different swing lengths and ultimate bat speeds primarily based solely on the pitch’s location. This complete factor has been in regards to the swing — it’s primarily in regards to the swing — nevertheless it’s about swing choices, too, and the augmentative powers of these choices.

Bat pace turns into dependable far more rapidly than exit velocity, which by itself ought to rapidly cement it into the analytical toolbox. Like some other metric, although, it nonetheless requires an immense quantity of context, lest we danger evaluating apples to oranges. Acceleration is a few of that crucial context, and I anticipate that after we’ve year-over-year knowledge, we are going to use it to diagnose accidents or spot indicators of decline higher than bat pace by itself.

All stats are by Might 19.



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