There’s a problem here. I say the word Pitch F/X and there’s a decent amount of you that stop reading there. That makes sense. Pitch F/X is something unfamiliar, something that seems too complicated to understand. But the reality is that Pitch F/X can give us more information on pitchers than stats ever can. So in this post, I’m going to attempt to explain the concept of Pitch F/X and how it’s pragmatically applied in my new Pitch F/X graphs.

When we hear about a player on our favorite team having “too straight a fastball” we know that’s a sign for alarm because major league hitters can handle straight pitches. That’s just one example of how critical movement is for a pitcher to achieve success, especially as the pitcher starts losing velocity from his fastball or if the pitcher never had good velocity to begin with. Even when a pitcher throws hard, some movement on his fastball just makes him better. We here all about cutters, sinker, and splitters, all derivatives of a fastball with more movement. We all know about **Mariano Rivera** and his one pitch, his legendary cutter. Rivera has been able to achieve consistent success as the closer for the Yankees season after season even as he’s gotten older and lost velocity because his pitch has such dynamic movement that no one in the major leagues has been able to hit it steadily. On the flip-side we hear about hanging breaking balls. What we notice is that when a pitcher leaves a slider or curveball up in the strike zone, bad things tend to happen, usually in the form of an extra-base hit going the other way. What is a hanging breaking pitch? A breaking ball without sufficient movement to get down in the zone or at least farther down. No pitcher has perfect control and no pitcher ever will. Even **Roy Halladay** and **Justin Verlander** misplace pitches and occasionally get hit hard because of it. But sometimes we’re watching on TV and we see a pitcher throw a pitch that ended up right down the middle, waist-high, and the hitter, sometimes even a superstar, takes it for a strike or swings through it. We wonder why they didn’t hit the errant pitch many rows into the stands like it would seem they could have. Often the TV broadcaster says that the hitter simply wasn’t ready for the pitch and couldn’t square it up. But other times, despite the poor location, the pitch had such good movement that the hitter was fooled by it. Movement can compensate for deficiencies in velocity and sometimes control. We also see pitchers with poor control but dominant stuff. Sometimes that could because the pitcher can’t repeat his delivery and his pitches go all over the place. But other times it’s because the hurler’s pitches have such great movement that he can’t always control where they go. Pitchers need to generate enough movement and be in control of where their pitches move in order to be successful.

We see that movement is so important to a pitcher’s success. That’s why we measure it. When you’re at the stadium, the pitcher deals a pitch and the board tells us the velocity and pitch type. Those are generated by an algorithm called Pitch F/X. For every pitch, Pitch F/X accurately records its velocity and identifies what type of pitch it was. How does it identify pitches? By also utilizing the pitch’s movement. In addition to what we see on the scoreboard, Pitch F/X also records many other things, most importantly for us, the pitch’s vertical and horizontal movement. This Pitch F/X data is provided on sites like Brooks Baseball, Texas Leaguers, and Fangraphs, and we can utilize it to paint the full picture on pitchers. Every fan knows that it’s important for pitchers to change speeds. But just as important is for pitchers to differentiate their pitches’ movement. Think of it this way: let’s say that in his previous at-bat, a hitter swung over the top of the opposing pitcher’s nice 85 MPH slider for strike three and now the hitter is facing a 1-2 count. He’s looking for the slider, hoping to track it with his eyes out of the zone or drive it out if the pitcher hangs it. But instead he sees out of the pitcher’s hand that he’s throwing a fastball in the low-90′s. The hitter lost his timing, but he can see the pitch is going to be a strike so he swings, aiming to at least foul it off. But lo and behold, the pitch was actually an 85 MPH changeup with the exact same movement as his fastball, and since the hitter was expecting 85 MPH and he got 85 MPH, instead of fouling the pitch off, he gets the barrel on the pitch and drills it into the seats for a home run. But now say the changeup had additional downward movement, and despite the different pitch, it would likely be the same result: the hitter would swing over the top of it.

In this day and age, hitters nearly always have at least rough idea of how the opposing pitchers’ pitches will move. The way a pitcher remains successful is through velocity and changing speeds, dynamic movement that makes a pitch difficult to hit even if you know it’s coming, and changes in movement, like between a fastball and sinker. How do we figure out whether a pitcher will be able to achieve sustained success in the big leagues? By looking at the velocity and frequency that he used his pitches, but also by looking at how his pitches move. That what makes Pitch F/X data so important. It helps us understand why a pitcher was successful in the past and attempt to explain whether he will be able to continue to succeed in the future.

All the sites I linked to have different ways of displaying and explaining the data. Let me explain the way I exhibit the data and what we can learn from it. Here’s an example of one my graphs and I’ll explain it below.

Without understanding anything, we can see in the key that the colored lines are different pitches that **Matt Moore** threw in 2011. The key also tells us how often Moore threw each of his pitches and what each pitch’s average velocity was. But what is going on with those lines?

Picture yourself as a hitter in the batter’s box versus Moore. You would have a front row seat (standing room only) to the movement on Moore’s pitches. Moore throws so hard that with your average vision and hand-eye coordination, it’s hard to even see his pitches. But you do notice just before you strike out on three pitches without lifting your bat off your shoulder that Moore’s first-pitch fastball wasn’t just straight 96 MPH, as a right-handed batter (like most of you are), the pitch moved down and in towards you. His changeup, which was almost slow enough for you to consider swinging, had sharper movement also down and in. And then Moore finishes you with a curveball that looks like it’s going to miss well above the strike zone before free-falling perfectly and moving away from you right onto the outside corner for strike three. Despite how quickly you went down, getting a close look at Moore’s pitches really makes you appreciate him a lot more. It’s not just that he throws 96 MPH and blows by hitters, but also he features the finesse to beat hitters with his movement as well.

I like to say that this graph is from the standpoint of a batter in the batter’s box. You have to picture it in three dimensions- the lines aren’t really moving towards the bottom of your screen, but towards you. Picture all the lines as coming from a pitcher standing on a 10-inch mound 60 feet, 6 inches away from you. All the lines start in the pitcher’s hand, the origin of the lines, and finish by being caught by the catcher just after passing through the gray rectangle. But each of the pitches moves differently before being caught.

The end points of each line show the average vertical and horizontal net movement from the ball’s origin in the pitcher’s glove until it’s caught by the catcher. Gravity causes every pitch to move at least slightly downward, therefore the length of the rectangle, which depicts the vertical net movement, starts at 0. The more negative the endpoint of a pitch, the more downward movement the pitch featured. For the horizontal movement, negative marks are pitches that move in towards right-handed batters, and positive marks are pitches that move away from righty batters and towards lefty batters. That is reversed from the Pitch F/X data from most websites, primarily because this graph is from the hitter’s perspective instead of the pitcher’s. In general in graphs that we see, values get more positive as we move to the right, so switching the horizontal movement and having the right side of zero be negative and the left side be positive would be too confusing. Another thing you may have noticed in that the lines for Moore’s pitches on this graph do not all start at the horizontal zero mark, and even the lines themselves don’t start in exactly the same place. Moore’s pitches don’t start at zero because Moore doesn’t start from zero. He stands on the mound just to the left of the midpoint of the strike zone horizontally from the batter’s perspective. In order to locate their pitches all over the the strike zone, pitchers release their pitches at slightly different heights and horizontal distances from the batter. But all pitchers should be able to locate their pitches all over the zone, so the average release point should be about the same. Looking very carefully, we can get a feel for where Moore tended to throw each pitch. If you pull out your magnifying glass (or have a lot better vision than me), you can see that Moore started his changeup slightly lower vertically than his other pitches, indicating that he tended to throw it more down in the zone. His other pitches though, he was good about placing all over the place both vertically and horizontally.

The lines themselves show how each of the pitches would move in the air. This isn’t taking location into account- no matter how great Moore’s curveball is, if he left it mid-out to a right-handed batter, it would get hit hard. Moore would occasionally drop in a pitch like that (at least some of the time, by accident), but he would try to get a good downward angle on his curveball in have it finish farther down in the zone, and he would also often try to have the pitch come back to hit the outside corner of the strike zone. Basically these lines are how the pitches would move from wherever Moore throws them to where they’re caught, disregarding the angle with which Moore would throw his pitches along with the horizontal location from which he would throw them. Changing the angle would basically give any of these lines the same movement but with a different origin and end. This graph averages the velocity, movement, and even the release point of Moore’s pitches so we can see the average way his pitches would move. There will always be variation, but this graph gives us an idea of what to expect from Moore’s pitches.

Pitch F/X graphs are so important because they take out a lot of the luck factor. A pitcher’s pitches don’t suddenly change and if he tries to add a new pitch, it becomes a headline. Pitchers live and die in the major leagues and at all levels of organized baseball based on their pitches. The Pitch F/X data gives us an idea of how good pitchers really are. People may disagree, but I trust Pitch F/X data more than stats for that reason: your pitches are your pitches, you can’t change them. The data isn’t perfect, but it’s gotten a lot better in recent years. And I’m going to keep using it for pitcher after pitcher. Don’t be scared of Pitch F/X. It’s just another resource to seek out what we all want to know: how good our favorite players really are, and how good they will be in the future.

If you didn’t understand the points I was making over the past few days in my previews with Pitch F/X graphs, please try reading them again and if you still don’t understand, feel free to contact me at @RobbieKnopf on Twitter or by emailing me at [email protected]

The preview for Moore is here, for **Wade Davis** is here, and for **Jeff Niemann** is here, and they’ll be more previews and Pitch F/X graphs coming soon.

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