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Open-source motion capture data of elite-level baseball pitchers on GitHub (github.com/drivelineresearch)
69 points by icelancer on Dec 15, 2022 | hide | past | favorite | 16 comments



This is from Driveline Baseball. My understanding is that they've really revolutionized the ability of pitchers to put spin on the ball. (Sticky stuff aside)


The MVP Machine [0] has a lot of interviews and background with Driveline folks, including their now-disgraced-turns-out-hes-a-terrible-person headline player (Trevor Bauer).

What's unclear is how long-lasting the performance improvements are (can the pitcher maintain spin rates without constantly going back to the data and coaching staff?).

One very positive thing I've seen is applying the analytics to young athletes as a future injury prevention tool. We now can, with high probability, identify kids who are on the path to permanently ruining their arm long before they cause lasting damage and give them an intervention - "You can dominate in Little League, but you'll never be a pro if you keep doing it this way. You must either change the way you throw or stop trying to be a baseball pitcher"

[0] https://www.basicbooks.com/titles/ben-lindbergh/the-mvp-mach...


Good book! I think the Driveline blog is a better source for folks working with youth athletes. The MVP Machine was a little bit more Moneyball than player development oriented . . .

Bauer. I had a bit of a meltdown about him - I was momentarily worried that his name alone would bring a huge negative reaction to people associated with Driveline training methods. That seems to have not come to pass.

I very much like the Driveline "Skills that Scale" training approach. I took several brand-new-to-softball middle schoolers into 50+ MPH bat speeds with overload/underload training and bat sensors. One great athlete hit 60+ in training in her very first year of playing the game. Course, she looks like a D1 athlete as well, so she may have gotten there just by putting a bat in her hand . . .


Driveline is the cutting edge of baseball/softball hitting and baseball pitching. As a tech person involved in coaching youth through middle school athletes, their blog (and youth coaching certification, which I completed) really gives a solid foundation in how to use bat speed sensors, radar guns, and more advanced tech in training. It's fun stuff for a data geek.

Mocap is a step beyond what I want to do with young athletes but having a data-driven approach is a coaches dream. Measure things that matter, build a constraint-based training environment, and let exterior outcomes shape players.


Only tangentially relevant but there is a great comedy drama show on Amazon Prime at the minute about the forming of a professional women's baseball team during WW2 called A League Of Their Own.


Everything gets a remake I guess…

https://m.imdb.com/title/tt0104694/


RTIB/LTIB and RTHI/LTHI are not symmetrical - any idea why?


I can answer this. Each of these markers comes into the software as part of an unconnected point cloud, which then needs to be identified and 'solved' to a constraint skeleton to get the true angles of rotation and the 'stick person' representation that you typically see.

Because of this, if you placed markers with bi-lateral symmetry, it would be much more difficult to solve joint rotation angles, as the overall facing of the point cloud would be undetermined. So, you have additional markers placed on none moving (not a joint) locations that ruin symmetry and allow facing to be easily solved. Typical locations are outside of the thighs, upper arms, and occasionally the back.

I built mocap studios for games companies.


I was mostly wrong.

But I like this answer better. It's a simple and clever solution to a real problem that you might not readily see as you're developing the solution.


I read your answer before commenting and didn't think you were so much wrong, but dangerously close to right, just off slightly. Interesting enough, each studio and sometimes even each operator, will have their own preferred marker placements. We will also vary these markers when doing multi actor scenes, so to help determine the tracking of the individual actors as well.


that's amazing! Do you have an email address where I can shoot you a message? I'd love to pick your brain on this tech (paid of course).


I am no longer in the game industry in this fashion. But sure, would be happy to talk.


Marker placement in motion capture is often intentionally bilaterally asymmetric because it makes automatic labeling of markers easier (with respect to side/orientation of the subject).

Source: Am a biomechanist with several years of mocap experience.


Just spitballing and guessing here: easier math.

Look lower down at the pictures or pitchers (heh). The legs themselves aren't symmetrical.

So they probably tweaked the points so that the most common range of angles to make the math easier to do.

Like I said, just a guess. But with one leg bent and the other stretched out, they probably form a line close to parallel with the ground for right-handed pitchers at the point in time when the pitcher is transitioning from wind up to release.


All this effort going into the most boring sport imaginable.


I thought we were talking about baseball not soccer.




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