Who Makes the Best Swing Decisions in Baseball?

Juan Soto
Scott Taetsch-USA TODAY Sports

Last week, when I was waxing poetic about Jeff McNeil’s ability to wait for a good pitch and then drop it into left for a single, I made an offhand mention to the player with the best swing decisions of 2021: Mike Tauchman, who doesn’t even play in the major leagues anymore. Then I moved on.

That wasn’t an accident. It’s what we in “the business” (no one calls it this) like to think of as a preview. I got multiple texts (another pro writer tip: “multiple” sounds better than “two”) from friends this weekend asking where the whole list of hitters was. That list is right here!

As a quick refresher, the idea here is to take every swing decision a hitter makes and compress them into one number. Every hitter who saw at least 50 pitches in each of the four attack zones (heart, shadow, chase, waste) is on the list. I took each of those rates and gave them league-average production for those decisions. The result looks like this, stated in terms of run value per 100 of the relevant zone/decision combination (take a waste pitch, say, or swing at a pitch in the shadow zone):

Run Value/100 by Swing/Zone, 2021-22
Zone Swing Take
Heart 0.42 -5.92
Shadow -3.62 -0.06
Chase -8.09 6.07
Waste -12.29 5.63

From there, I assumed a league-average percentage of pitches in each zone. Combined with each hitter’s swing rates, that let me produce an overall run value assuming an average rate of pitches in each zone.

Here’s a quick guide on how to interpret these numbers. For each hitter, there are three numbers. The first two are just the same statistic said different ways. The first metric, “RV/100,” is how many runs above or below average each hitter on the list would be, per 100 pitches, if they got exactly average results on every zone/decision combination. The higher the number, the better positioned a hitter is to succeed, by taking tough pitches and swinging at good ones.

The second number turns those inscrutable run value numbers into something you can work with. Seriously: a scale where the best number is 0.62 and the worst number is -1.33 is awful. “Did you see Juan Soto? The man can’t be stopped; he picks up nearly 0.6 runs per hundred pitches he sees from his eye alone!” Yeah, that’s not gonna work.

So I did some math — ew, math — to turn those numbers into something we can work with. First, I went from 100 pitches to one pitch, then converted pitches to plate appearances based on the league-wide average of 3.92 pitches per plate appearance. That gave me runs per plate appearance, and multiplying runs per plate appearance by the wOBA scale factor (1.209 in 2021) turns runs into wOBA. Just rolls right off the tongue, doesn’t it?

In any case, that’s a much easier way to think about this. “Juan Soto raises his wOBA by 30 points by spitting on bad pitches” sounds excellent (or OBP if you’d prefer, since wOBA is on an OBP scale and we’re hardly being scientific here, so call it what you want). That doesn’t even get into what Soto does when he swings; we’re assuming everyone is average when they swing, which isn’t the case. But as a single number, it’s a nice way to think about how where you swing can affect your production.

The last number on there is NOC+, a pet statistic of mine that I roll out every so often to give context to strikeout and walk rates. It’s a plus statistic, where higher is better, and it measures how much a batter’s non-contact results (strikeouts, HBPs, and unintentional walks) help or hurt them. More specifically, it’s a measure of how far above or below average a hitter’s production on contact would need to be to make them an exactly average hitter. Have a NOC+ of 113? That means you could be 13% below average on balls in play and still be an average hitter. NOC+ of 87? You’ll need to be 13% better than average when you put the ball in play just to break even.

You can read about the finer details of that number here, but it’s basically just there as a sanity check. NOC+ looks at strikeout and walk numbers, which means contact rates are very important there. It’s not exactly the same — you can make good swing decisions and just come up empty too often — but generally speaking, if you’re hunting good pitches to hit, you should do well by all three metrics. The other side isn’t as clean of a relationship — you can achieve a solid NOC+ by rarely striking out, so contact hitters do well by that number almost regardless of how often they chase — but if you combine low contact rates and poor swing decisions, you’re in for a world of hurt.

I find this way of looking at swing decisions to be elegant, if not necessarily perfect. Let’s put it this way: if I asked you to come up with a one-number plate discipline metric, and you couldn’t use strikeouts or walks (or contact rate), do you think you’d have Soto second and Javier Báez second-to-last? I’m pretty happy that merely looking at swing rates by zone can do a good job of putting numbers to what our eyes see on the field every day.

There are some interesting names on there, too. Brandon Nimmo’s at-bats are as grindy as you think. Salvador Perez must be doing a lot right when he makes contact, because hoo boy has his judgment been bad. Maybe we should be more willing to believe that Zack Collins can figure it out at the big league level given his propensity for taking bad pitches. And oh yeah: this is just another thing at which Ronald Acuña Jr. is good.

Taylor Walls can pick it, and he’s no slouch when it comes from telling balls from strikes either. David Fletcher, on the other hand, needs to rekindle his strike zone judgment if he’s going to return to form. He’s still doing alright at actual strikeouts and walks thanks to his phenomenal contact rate, but without drawing walks and getting the occasional pitch to drive, hitting will likely continue to be tough sledding for him. The insights go on and on.

Boy, wasn’t that page of statistics fun? I don’t even mean that sarcastically; I find this quite interesting. Even if you don’t want to dive through a Google Sheet full of names and long, context-less numbers, I think it’s worth knowing that you can take the rawest imaginable building blocks of a player’s approach — when they swing and when they don’t — and add useful nuance to them using Baseball Savant’s four-zone approach. I like the four-zone demarcation of the strike zone far more than the old in/out dichotomy, and the kind of slicing and dicing I did here is a major reason for that.

Before I finish up, here are the top ten hitters by wOBA added with swing decisions:

Best Hitters by Swing Decision, 2021-22
Player Run Value/100 wOBA From Swing Decision NOC+
Mike Tauchman 0.619 0.029 92.5
John Nogowski 0.593 0.028 110.2
Juan Soto 0.593 0.028 126.7
Brandon Nimmo 0.544 0.026 113.4
Clint Frazier 0.528 0.025 100.0
Trent Grisham 0.519 0.025 102.7
Max Muncy 0.479 0.023 113.3
Robbie Grossman 0.453 0.021 108.2
Curt Casali 0.448 0.021 89.4
Alex Bregman 0.443 0.021 115.9

And the bottom ten:

Worst Hitters by Swing Decision, 2021-22
Player Run Value/100 wOBA From Swing Decision NOC+
Victor Reyes -0.998 -0.047 92.5
Harold Ramirez -1.053 -0.050 105.7
Jorge Alfaro -1.094 -0.052 77.1
Hanser Alberto -1.098 -0.052 109.1
Salvador Perez -1.103 -0.052 91.4
Tomás Nido -1.106 -0.052 81.8
José Iglesias -1.149 -0.054 107.8
Lewin Díaz -1.173 -0.056 89.4
Javier Báez -1.220 -0.058 80.6
Francisco Mejía -1.330 -0.063 105.0

Lastly, a few odds and ends. If you’re looking for the individual swing rates by zone so that you can marvel at the fact that Báez swings more at pitches in the chase zone than Soto does at pitches on the edges, here they are. Don’t see your favorite (or least favorite) hitter on there? That means they haven’t seen many pitches lately, but not to fret. You can do this at home if you have far too much free time and a spreadsheet. Just plug in their swing rates in each zone, multiply them by those run values in the chart up above, add in the fact that the average zone distribution by hitter is 26.4% heart, 42.4% shadow, 22.3% chase, and 8.9% waste, multiply by 100 pitches, and bam, you’ve just painstakingly reconstructed my method.

So thanks for playing along as I describe some statistical shenanigans. Whether or not a hitter swings is a tough part of baseball to get excited about. It’s a particularly tough part of baseball to visualize; a hitter who chases 12% of the time doesn’t look very different from a hitter who chases 17% of the time to the eye test. It’s extremely important, though, and I hope that these attempts at simplifying swing and take behavior into single numbers are useful.

Ben is a writer at FanGraphs. He can be found on Twitter @_Ben_Clemens.

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1 year ago


Is there a way to sort through the noise that assigning league average production for swings and league average percentage of balls in each zone might produce? You allude to it with Soto swings – not getting to what happens when he does swing – so wondering if there is more to come. Very interesting exercise..