Review: Motus Global’s mThrow

When Motus Global’s sleeve was announced last spring, it was supposed to save baseball, stemming the flood of Tommy John surgeries plaguing the majors. Now, the device that teams have been using to study their pitchers’ mechanics since last fall is available to the public. The mThrow has been on sale through the Motus website since March, and began shipping in early May. Eager to see what the device had to offer, I plunked down the $150 (plus $20 for an additional compression sleeve) and waited anxiously.

The box that the mThrow comes in is taken up mostly by the compression sleeve. The actual IMU — the sensor that actually tracks the arm’s motion — is a tiny blue thing, about the size and shape of a circus peanut*. The IMU charges by induction, so all the user has to do is plug in the charging station, place the sensor on top of the station, and wait about an hour.

* – But slightly better-tasting.

Pairing the sensor is simple, too, taking just a few taps of the smartphone app. The hardest part of setting the thing up is probably wedging the sensor into its little pocket in the compression sleeve, and then pulling the sleeve on so that the sensor rests over the infamous ulnar collateral ligament. In fact, the design might be overly simplified. In an effort to make the sensor more water-resistant, there are no lights on the sensor to tell the user of the charge level. The only way to check is to pair the sensor with the smartphone app; if the app doesn’t recognize the sensor, it probably needs to be re-charged.

The app is currently available only for the iPhone; an updated version was approved this week. The software now computes five metrics from the sensor data: pitch count; maximum arm speed, a rotational velocity measured in revolutions per minute; arm slot at release; maximum shoulder rotation relative to initial position; and, of course, torque on the UCL. These are then combined into three headline numbers: performance, a measure of mechanical consistency; workload, currently an additive function of elbow torque; and a “throw meter,” an energy bar that drains from blue to orange as the workload increases and consistency decreases.

I ran some preliminary testing of the mThrow, connecting it to an iPhone 4S and throwing 17 fastballs, 17 changeups, and 17 curveballs to the best of my extremely limited ability; all but six throws were recorded. Even if there’s no difference between their speeds and movement, you can still see a difference between my initial warmup tosses (the first dozen, with much lower arm speeds), fastballs (about 13-25), curveballs (26-43, with much lower torque values), and changeups (44 onward, with decreased arm speeds).

This simple relationship was confirmed with a second test using a HitTrax system, which can track speed and late break of pitches as they cross the plate. My subject was a 45-year-old with some collegiate pitching experience who threw ten fastballs and ten curveballs. By comparing the HitTrax velocity report (right) to the mThrow statistics (left), we can see the correlation between the decrease in arm speed and the decrease in velocity as the subject switched from fastball to curves.

Lastly, I brought the sleeve to a local high school (Blackstone Valley Tech, Upton, MA) to get some insights from active players. Assistant coach John Burke, pitcher Nick Laren, shortstop Joe Corsi, and catcher Jack Lynch took turns throwing an assortment of pitches from a number of release points, seeing how their throwing motions stacked up. The session supported some beliefs — for instance, that the quick motion Lynch uses to throw out would-be base stealers puts more torque on the elbow than a standard pitching delivery. But others were surprisingly contradicted: despite everyone’s belief that sidearm throws put less stress on the elbow than an over-the-top delivery, the app didn’t seem to report a relationship between arm slot and torque.

Chief technology officer Ben Hansen says the mThrow is still in its infancy, and says that the device’s official consumer launch is not scheduled until later this summer. The app currently relies on data compiled from Motus Global’s work with MLB prospects at last fall’s instructional league to generate its workload number, but Hansen and his team are working to produce more meaningful metrics from a more complete data set.

“We’re just capturing as much data as we can to see what’s normal,” Hansen said. “We also have controlled studies going on at every level. We have [NCAA] D1, D3, high school, and Little League players wearing it religiously.”

At this early stage, the app seems to be designed more for Motus’s professional clients than for public users. Maybe the best example of this is the tagging feature, which allows users to tag individual throws as belonging to bullpen sessions, long toss, or game action, and to further break throws down by pitch type. But at the moment, the tags are unavailable to the user after selection, getting passed on to Motus Global with the sensor data but not visible on any of the trend screens. Hansen confirmed that the tags were being used in the company’s research for their MLB clients, however.

“Every week we send reports broken down by tags where we compared each pitcher to the league averages for that pitch type,” Hansen said. “The teams love using the tags and breaking things down into the different pitch types.”

It’s a tantalizing view of an exciting feature that could still be a couple years away. And it’s not just super dorks like me who would find those analytics useful. The key to a good changeup is matching the same arm speed used to throw a fastball, so it’s easy to see coaches like Burke using the arm speed metric to give feedback to young pitchers just learning to throw the pitch. But without any way to divide pitches into different categories, this sort of feedback isn’t possible yet.

“We are looking into a web portal to give users more in-depth analytics,” Hansen said. “But right now we’re focused on getting the analytics right before we move on to other platforms.”

It’s probably still too early to judge the mThrow fairly, and I’m almost definitely not the right person to do it (sabermetrically-inclined tech geeks who can’t pitch are not Motus’s target market). And it’s true that more research could produce findings that actually help young pitchers stay on the field and off the operating table. But as currently constructed, the mThrow raises more questions than it answers, and left me wanting more. Like a top pitching prospect, the technology needs some time to mature before it can make a meaningful contribution.