Sabermetrics, the Sound off the Bat, and a Bit of Phenomenology

Baseball as a sport, like most activities of daily life, is one which we consume primarily through our eyes. While I’m certain some people still enjoy it by listening to the radio (a mode I’m still partial to), I think you would be hard-pressed to that argue baseball is not visual. That’s not to say we don’t listen to the sounds (personally I find baseball on mute to be close to a kind of torture). However, our judgments of the game, and more importantly our judgments of the players in it, are based on what we see visually. We don’t know Mike Trout is good just because the announcer tells us he is good, we know he is good because we can see how good he is. We can see the balls he snatches away as they clear the fence, as well as the balls he smashes over them.

There are other methods we can use to see that Trout is good as well. Sabermetrics and Trout have seemingly been tied together in their emergence into the public baseball consciousness. As he blossomed into a star, so did Sabermetrics as it rose to the forefront and into the view of the average fan. Like Trout, the way we digest sabermetrics is in a sense almost purely visual. We come to FanGraphs, and we read a stat line off the screen. When we look at exit velocity or launch angle, we’re looking at metrics we’re aware of because a computer system visualized them for us.

To a large extent, what I’ve said above is simply a result of us privileging sight more than our other senses. Baseball utilizes the other senses as well. We all likely have memories tied to the smell of the stadium or a leather glove. Maybe every time you go to a game you get a hot dog, and that taste is as connected to baseball as the sound of a cheering crowd. Baseball at its best is a palimpsest of all of these senses working together to create our experience.

Phenomenology, in the most basic way I can explain, is the study of our consciousness and how we experience the world through consciousness. All experience, and consciousness as a result, is deeply rooted in our senses. We experience life because we experience or sense the physical world around us. As mentioned before, sight is the “primary” sense with which we navigate the world. This privileging of sight over the other senses shapes our perception and experience in the world. I don’t think anyone would argue that a blind person doesn’t experience the world very differently compared to someone who can see.

Bringing this back to baseball, we can start to think about the ways in which baseball as a game of sight also affects the way we experience it. However, as mentioned at the beginning, baseball has a secondary means of consumption outside of the visual (TV/stadium) and that is auditory (radio). If we could only watch baseball, without the use of any other senses, we would likely be able to follow the game without any loss of understanding as to what is happening on the field. The umpire makes gestures so I can tell balls and strikes and plays at the bag. I can see a home run clear the fence, or a batter swiping second base. But if we could only hear baseball, and we didn’t have the announcers to guide us (through their sight), we would lose some important information. We could hear strikes and balls from the umpire, but we couldn’t see how close or how far away they were from the zone. Maybe we can hear safe or out, but at which bag and which runner? Perhaps we can hear the home crowd cheer suggesting a run has scored, but how many and by who?

But there is one sound which immediately stands out from everything else we hear in the game, and that is the crack of the bat. Every crack of the bat doesn’t result in a home run, but you immediately know what has happened, you know that the ball has been hit and it has been hit hard. Personally, I think it is one of the most satisfying sensory experiences in all of baseball. I’m sure I’m not the only one who has had to rewind a video a few times, not to see the home run fly again, but to hear that snap.

We sometimes hear an expression like “his bat makes a special sound.” The idea is that even though the batter is hitting the same leather ball with the same wood bat as everyone else, something about the sound is unique. One night as I lied in bed trying to sleep, I asked myself why we don’t analyze bat sound? The idea that sound is an indicator of skill or talent in some way isn’t new. People have been talking about bat sound for I imagine a very long time. What we haven’t done, however, is attempt to quantify it. Sabermetrics has and continues to scour every bit of information it possibly can about how good a player is or how good they could be. Perhaps because we have privileged and experienced baseball (in particular baseball talent) through almost exclusively sight for so long, we’ve forgotten to look at quantifying other senses.

All of that gibberish is just a fancy way of saying maybe it’s time we looked closer at bat sound. I’m certainly no audio engineer, but luckily I am computer savvy and Google knowledgeable enough to give a little push. Using data from the 2019 MLB season, I looked at the waveform of sound off the bat of six home runs (three by Anthony Rendon and three by Juan Soto). I selected only home games at Nationals park, applied the same basic noise reduction to them all (though this seemed to have little effect, as the noise off the bat is noticeably louder than anything in the background), and was able to get two homers from different players on the same day twice. I trimmed down the hit sounds to start right when the waveform destabilized, and I ended when the waveform stabilized (to be fair, these are probably the wrong technical terms). There are variables that could affect the capture of sound, the most obvious of which to me seems the fact I didn’t choose two same-handed batters. Regardless, here are some quick sound recording results.

Rendon, June 16th: Pulled/Center

Rendon, August 31st: Pulled

Rendon, September 1st: Center

Soto, July 30: Center

Soto, August 31st: Opposite

Soto, September 1st: Pulled

As noted, I’m not a professional audio engineer, so I can’t “interoperate” these results for you. Just like you, all I can do is look at them (sight again!) and see if there are any immediate basic patterns. Right off the bat, I would certainly think there are.

For example, Rendon’s June 16th and August 31st home runs look very similar sound-wise, particularly at their start. Soto’s July 30th and Sep 1st homers also look similar in that they don’t look anything like Rendons. We can see in his August one something much closer to the two I first mentioned by Rendon. Another noticeable aspect is how much shorter the sound waves are for Soto’s, which seem to dissipate much faster.

This little experiment isn’t meant to prove that there is something here. It is to suggest that there could be something here, and to show that there are still a myriad of ways in which we are not thinking about sabermetrics. Imagine if you could run a similarity score for sound waves from different players to asses some kind of potential. What if we could say that not only does Luis Garcia look similar to Juan Soto when he swings the bat, but that he sounds similar to when Soto swings the bat too? What if max frequency in a standardized wavelength is an excellent predictor of power? Imagine if there is some lightly touted prospect in the minors whose bat sound mirrors that of Mike Trouts.

The rise of sabermetrics was all about realizing the value of what was already there, taking what we already knew and finding new ways to look at it. It’s only a matter of time before we can measure the near-exact location of a pitch at every step it takes from the pitchers hand to the glove of the catcher. With that will come new information and new ways of dissecting it. However, there’s still plenty of data already being collected with potential we’re only just realizing. Perhaps all that’s stopping us from seeing it is that we keep looking for it when we should be listening for it.

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atadams
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atadams

You should try using spectrograms. They are what I used to help identify the Astros’ trash can bangs (http://signstealingscandal.com is my site). They will give you a much more identifiable visual pattern. I used a Python package called Librosa to create the spectrograms on the site (example: http://signstealingscandal.com/about/). If you’re not a Python guy, Sonic Visualiser is a free, open-source application that will create them. https://www.sonicvisualiser.org/

Lunch Angle
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Lunch Angle

Nice idea! Actually evaluating the “the ball sounds different coming off his bat” phrase is something I’ve thought about, but you actually did it. I’ve been skeptical that it’s actually possible to hear with the human ear any difference between a hard hit ball from any two players.. but maybe with technology!

Being a pedant here, but btw I don’t think “palimpsest” means what you think it means