Too Much Math About an Old Adage

Joe Camporeale-Imagn Images

I never pitched in Little League, but I remember many of the lessons our coach imparted to this day. Most specifically, I remember him harping on “hard in and soft away.” This was silly. Nobody on my team could throw a curveball, and even from my youthful perspective, no one could throw anything hard either. We all mostly struck out or walked; pitchers with command were pretty much untouchable in my small-town East Tennessee league. But we’re losing the plot here – as it turns out, that advice is omnipresent in baseball, from little leagues to the majors.

I’ve always been enamored with this simple and yet fascinating rule of thumb. Why does it work? Does it work, even? What’s so special about “in” and “away” relative to pitch speed? I’ve never quite found a satisfactory way to classify it. But while I was taking a look at contact point data last week, I came up with an idea for how to measure this. When you look at the data, the evidence has been there all along.

I focused on the “hard in” aspect of the adage, because major leaguers throw so many different secondaries that honing in on what “soft” meant seemed impossible. To that end, I devised a quick test to see how conventional wisdom behaves in practice. I defined “inside” and “outside” pitches by removing the middle third of the plate, then extending out nine inches past the edge of the strike zone in both directions. I looked at sinkers and four-seamers thrown in these areas to define “hard in” and “hard away.”

With that data in hand, I set out to measure how hitters deal with those pitches. For every hitter, I took all of their contact points against inside fastballs and found the median depth of contact. I did the same for outside fastballs. For the purposes of this study, I took only balls in play. I tagged every swing as either early (farthest forward third of the subset of swings), on time (middle third), or late (last third). I also calculated each hitter’s average wOBA, exit velocity, and launch angle for both inside and outside fastballs.

By indexing everything to itself this way, I was able to measure production relative to a hitter’s own baseline. Without this step, I was at the mercy of sampling; if Aaron Judge swung more often in a particular bucket, that bucket would look really good. The opposite would be true of some weaker hitters. By comparing everyone to themselves, we get a more honest accounting of what’s going on.

What’s going on, incidentally, is that being late on an inside fastball is devastating for the hitter:

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Relative wOBA, Fastballs by Location and Timing
Timing/Location Inside Outside
Early 0.036 -0.030
On Time 0.012 0.004
Late -0.048 0.026

In plain English, when a hitter makes late contact with an inside fastball, their results on contact are notably worse, by nearly 50 points of wOBA. That’s an enormous effect, the equivalent of the gap between otherworldly power like Cal Raleigh and merely great power like Rafael Devers or Pete Alonso; or the gap between Alonso and Trea Turner. Fifty points of wOBA on contact is a big finding, and guess what? It’s happening for a clear reason:

Relative Exit Velocity (mph), Fastballs by Location and Timing
Timing/Location Inside Outside
Early 6.6 -4.4
On Time 1.9 1.6
Late -8.5 2.8

In other words, when pitchers venture inside, hitters really do need to get the bat out to do damage. Making contact too late, too deep in the zone, leads to incredibly poor outcomes. On the outer half of the plate, there’s far less signal, and it’s in the opposite direction. Making contact deeper in the zone leads to better results; more advanced contact points are associated with lower wOBA and exit velocity.

This makes good mechanical sense. Imagine making contact with a fastball over the outer half. Catch one of those fastballs late, and you’re liable to hit it the other way square. Get out in front of it, and there’s a decent chance that you’ll be rolling over the ball, what with trying to hit it late in your swing and far away from you. In fact, early/outside fastballs have a launch angle 3.3 degrees lower than outside fastballs as a whole, using the same relative-to-self methodology. The opposite is true for inside fastballs; to hit those hard, you have to have your bat all the way through the zone by the time you make contact.

The difference between early and late swings at fastballs is stronger for four-seamers. Here’s how it looks broken out by pitch type:

Relative wOBA, Four-Seamers by Location and Timing
Timing/Location Inside Outside
Early 0.047 -0.030
On Time 0.007 0.011
Late -0.054 0.020

Relative wOBA, Sinkers by Location and Timing
Timing/Location Inside Outside
Early 0.032 -0.022
On Time 0.006 0.001
Late -0.039 0.020

I think I’ve pretty conclusively proven that the reason inside fastballs are effective is that they punish late swings. Fastballs, after all, are fast. There’s even more juice if they’re both fast and rising. Again, I’m not saying anything new. We all knew this without needing to see the data. But seeing the data is still enlightening, to me at least, and goes a long way toward explaining why pitchers still try to pump inside fastballs past hitters. If swings are slow, the results will be disastrous; that’s why.

On the other hand, look at the tremendous damage that hitters are capable of when they get off an on time or early swing against an inside fastball. “Hard in and soft away” only works if your hard pitch knocks hitters off of their “A” swing.

To that end, I decided to measure which pitchers were effectively pitching inside. With all the per-pitch data already handy, I had an easy way of doing this. I took every pitch where a hitter swung at an inside fastball and used that to calculate an “average contact depth” value for every single pitch that matched my criteria. Then I compared that to the actual contact depth. The difference is how much a pitcher enticed the batter to be either early or late. Here are the 10 pitchers whose opponents made contact with inside fastballs farthest behind their average inside fastball contact point:

Timing Disruptors (Latest Contact Points vs. Inside Fastballs)
Pitcher Avg. Contact Point Deviation Velo (mph) Swings
Justin Steele -7.47 90.7 46
Roki Sasaki -4.26 96.2 41
Yuki Matsui -3.95 92.0 67
Ryan Feltner -3.83 93.6 45
Reed Garrett -3.54 96.9 65
Matt Bowman -3.44 90.9 45
Richard Fitts -3.42 95.5 74
Tyler Gilbert -3.42 90.1 61
Clay Holmes -3.36 93.7 198
Jason Adam -3.24 94.6 43

Honestly, I expected this list to be full of guys who throw 100, but Steele is a fascinating name at the top. He’s a fastball-dominant righty who sits around 90 mph and does well anyway. There’s clearly something deceptive about his cutter-y fastball. (I used Statcast definitions to determine which pitches fit here, and Statcast calls his offering a four-seamer.) Sasaki pumps laser beams past people, no doubt, but a lot of the pitchers on this list use deception to succeed.

For every list of leaders, there has to be one of laggards. Amusingly, many of the pitchers who are letting their opponents get extended throw the ball hard:

Trackable Fastballs (Earliest Contact Points vs. Inside Fastballs)
Pitcher Avg. Contact Point Deviation Velo (mph) Swings
Javier Assad 1.08 92.31 52
Parker Messick 1.06 92.51 48
Tyler Mahle 0.89 92.27 75
George Soriano 0.73 95.82 43
Daniel Palencia 0.72 99.73 121
Drew Pomeranz 0.65 92.78 116
José Alvarado 0.65 99.24 56
Nick Mears 0.64 95.69 47
Mason Englert 0.58 93.54 48
Kaleb Ort 0.53 96.52 63

One way to think about this list: It’s a mix of guys with so-so fastballs and relievers whose fastballs are so good that hitters sell out to beat them. It’s not every high-leverage reliever, obviously – the best guys are, well, the best – but it’s a good reminder that pure velocity is no guarantee of disrupting a hitter’s timing enough to keep them behind on an inside fastball.

I’m a little less sure of what the other side of the plate means, but I calculated it anyway, because hey, I have the data. Here’s a list of pitchers who get their opponents out in front, even of their fastball, on the outer reaches of the plate:

Good Outside (Earliest Contact Points vs. Outside Fastballs)
Pitcher Avg. Contact Point Deviation Velo (mph) Swings
Huascar Brazobán 1.84 96.5 53
Seranthony Domínguez 1.81 97.8 94
Tristan Beck 1.80 94.7 44
Carlos Vargas 1.58 97.5 80
Jacob Lopez 1.46 90.9 142
Brent Headrick 1.40 94.3 64
Orlando Ribalta 1.30 96.6 40
Matt Svanson 1.29 97.1 55
Caleb Thielbar 1.27 93.1 61
David Morgan 1.23 98.0 56

And to come full circle, one that greatly amuses me. Thought Sasaki’s fastball looked good on the inner part of the plate? Well, it’s an absolute disaster when he throws it outside. Batters are late on it, which is great inside and leads to a pile of opposite-field line drives outside. It’s tough to tease out game plans from raw measurables here, but whether it’s hitters who are able to stay back against these pitchers or just fastballs that slow down opposing bats, they’re getting hit around because opponents are capable of staying back:

Tagged Oppo (Latest Contact Points vs. Outside Fastballs)
Pitcher Avg. Contact Point Deviation Velo (mph) Swings
Roki Sasaki -4.17 96.3 59
Max Kranick -3.53 95.8 44
Tony Gonsolin -3.28 93.5 42
Aaron Bummer -3.23 91.2 41
Jason Alexander -3.19 91.2 77
Parker Messick -2.94 92.4 43
Andre Pallante -2.88 94.5 131
Hogan Harris -2.84 93.7 78
Kolby Allard -2.80 90.1 74
Clayton Kershaw -2.72 89.4 60

I don’t feel confident in the size of this effect, certainly not in a vacuum; the other pitches and other fastball locations a pitcher selects have a huge impact on how hitters behave against these cherry-picked samples. But even with that said, I think it’s really cool that you can see how fastball shape and location interact from the raw data. That stuff you always thought about the sport when you were a kid, the stuff your parents and coaches and teammates repeated ad nauseam through endless practices and games? It’s real. It’s measurably real. It works even in the majors. If you can jam someone with an inside fastball, the value is undeniable. Just don’t get caught with your hand in the cookie jar; if the batter is on time or early, there might be fireworks.





Ben is a writer at FanGraphs. He can be found on Bluesky @benclemens.

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zekepMember since 2025
30 seconds ago

This is just a big duhhhhh, and the sample sizes are too small