Random relievers can do crazy things in small samples. Who can ever forget Nationals right-hander Justin Miller striking out 57.9% of the hitters he faced across a three-week stretch of 2018? Or Kody Funderburk’s legendary whiff explosion to close out the 2023 Twins season? Guardians reliever Hunter Gaddis is on one of these incendiary strikeout runs, and it’s driving me to madness.

Gaddis might not strike you as operating at the same level of random as Miller and Funderburk. By any set of reasonable standards, Gaddis broke out last season, appearing in nearly half of his team’s games while delivering a 1.59 ERA. But — forgive me — I didn’t really buy it. His 23.7% strikeout rate matched the league average for relievers, and his arsenal didn’t exactly justify a .205 BABIP. Given his pitch shapes and peripherals, I figured Gaddis would settle in as more of a solid middle-relief type than one of the premier backend arms in the league. And then this April happened. Read the rest of this entry »

It was June 2024, and Matt Bowman was in a tough spot. He was 33 years old and fresh off his third DFA in six weeks. In his one appearance as a Mariner, he recorded just two outs, gave up one run on one hit — a home run — and one walk. As a righty reliever on the wrong side of 30 with a 92-mph sinker, he was about as fringey as they come.

That day in Seattle could have been his last time on a big league mound. Instead, he tried something crazy. Once the owner of an unremarkable delivery, Bowman now throws from the most extreme horizontal release point in the sport. And it looks like it has saved his career. Read the rest of this entry »

First impressions are everything, the expression goes, and a poor one could have doomed Juan Soto’s 2024 season. The Yankees dealt five quality players for one year of his services; a slow start in the Bronx would have invited the wrath of tabloids and fans alike. But Soto started with a bang, gunning down a runner at home plate to preserve a ninth-inning lead in his debut and going on to hit .325/.438/.561 in his first month as a Yankee. From day one, he was undeniable.

This time around, he hasn’t been as lucky. Soto remains in New York, albeit in a different borough, and he’s fresh off signing the largest contract in professional sports history. By those standards, his start this season is underwhelming. His batting line is 25% above league average, but the shape of his production is essentially Soto at his least productive: tons of walks, a few too many groundballs, and not much extra base damage. The quasi-slow start prompted a story written by The New York Post’s Mike Puma headlined “Juan Soto opens up to The Post about pitchers’ new approach without ‘the best hitter in baseball’ behind him.” Read the rest of this entry »

Hitting a baseball is an unthinkable accomplishment of timing. In order to strike a ball traveling from the pitcher’s hand to the plate in less than half a second with a slab of wood, a hitter must execute an elaborate sequence of movements on time. When do you lift your front foot? When do you load your hands? When do you fire your hips? It’s a sophisticated choreography; a beat late at any point can doom the swing.

Picture Fernando Tatis Jr. When Tatis is at the plate, he shifts around like a predator stalking its prey, eyes peeled for the exact moment when the pitcher lifts his front foot so that he, too, can get his toe down at the right time, and then his hands up, and then finally the barrel through the zone:

If hitting is such a delicate sequence, conditional on the pitcher’s own timing, it follows that pitchers who mess with that timing can improve their performance; by extension, pitchers who groove their deliveries will underperform their stuff. In an interview with David Laurila in 2017, Jason Hammel described changing his delivery for these precise reasons. Read the rest of this entry »

I thought I had it sorted out; it took one batted ball to convince me otherwise. It was the bottom of the seventh inning during the Rays’ first game in their new George M. Steinbrenner (GMS) Field digs. Jonathan Aranda worked his way into a 2-0 count against Rockies reliever Tyler Kinley. With runners on second and third, one out, and the Rays down two runs, Kinley hung a slider. Aranda uncorked his A swing, launching the ball deep to right field. Off the bat, I thought it looked way gone. It didn’t even go 300 feet:

Read the rest of this entry »

For the Tampa Bay Rays, it was the fearsome power of nature; for the Athletics, the whims of a greedy doofus. But while the cause may vary, the outcome is the same: Both teams will play all 81 of their home games this season in minor league parks. The A’s will set up shop at Sutter Health Park, also known as the home of the Triple-A River Cats; the Rays’ address is now George M. Steinbrenner (GMS) Field, the erstwhile environs of the Single-A Tampa Tarpons. (The River Cats will share custody, while the Tarpons will move to a nearby backfield.)

This is suboptimal and sort of embarrassing for the league. But it does present a compelling research question: How will these parks play? According to the three-year rolling Statcast park factors, the Oakland Coliseum and Tropicana Field both qualified as pitcher-friendly. The Coliseum ranked as the sixth-most pitcher-friendly park, suppressing offense 3% relative to league average, while Tropicana ranked as the third most, suppressing offense around 8%. Where will Sutter Health and GMS Field settle in?

I started by looking at how each park played in their previous minor league season. Over at Baseball America, Matt Eddy calculated the run-scoring environment for each ballpark in the 11 full-season minor leagues. Eddy found that Sutter Health ranked as the most pitcher-friendly Pacific Coast League park by far in 2024, allowing 31% fewer runs than the average PCL park. GMS Field played closer to neutral compared to its Florida State League peers, but it did significantly boost home runs, particularly to left-handed hitters. Read the rest of this entry »

After wrapping up our position player rankings last week, we turn our attention to the league’s pitchers, starting with the bullpens in the bottom half of the reliever rankings.

It’s impossible to project relievers. The pitchers themselves are random enough, sprouting new pitches or gaining five ticks on their fastball with no prior warning. Pitchers also tend to get injured, especially the ones who go max effort on every pitch. And then there’s the randomness of 60-inning samples, where a fly ball sneaking just past the glove of a leaping outfielder can catapult an ERA from respectable to disastrous. This is all to say that the task of forecasting a bullpen’s performance over the course of a single year is destined to fail.

So I’ll take this introduction as an opportunity to encourage you to not take the order of these rankings too seriously. Less than one-tenth of a win separates some of these teams. There is perhaps just one truly terrible bullpen in the mix; every other team essentially has a mix of proven shutdown guys, solid middle-inning depth, and intriguing wild cards. With that said: To the rankings! Read the rest of this entry »

I’m not much of a YouTube guy or, really, a fan of videos in general. If you send me an Instagram reel, I’m sorry, I will not watch it. But Lance Brozdowski delivers his baseball thoughts in video form, so I am compelled to make an exception. Lance’s posts prodded me to start writing about baseball in the first place; I always learn something when I watch his stuff and tend to agree with all of his analysis.

So I was shocked — shocked! — to hear him express pessimism about Spencer Schwellenbach in a recent video. All through this offseason, I’ve had the opposite thought: There isn’t enough enthusiasm about Schwellenbach’s rookie campaign, during which he posted a 3.29 FIP over 123.2 innings. But Lance wasn’t the only one with a tepid appreciation for the right-hander. Eno Sarris ranked him as his 34th-best starting pitcher; Thomas Nestico had him at no. 36. If I were obliged to make such a list, I might be pushing him some 20 spots higher. I think Schwellenbach’s rookie excellence can be repeated and even improved upon for one key reason: When he delivers the baseball, nobody knows what to expect. Read the rest of this entry »

There isn’t much for a baseball writer in the dull days of late February. Someone added a new pitch? The pitching nerds are all over it. Somebody else set a new career high for exit velocity? I’m not sure that merits more than a tweet and/or skeet. Statistically responsible baseball writers have long concluded that attempting to find signal in the noise of spring training stats is a futile exercise.

Thankfully, Effectively Wild came to my rescue. On Episode 2288, Ben and Meg discussed the peculiar case of Justin Verlander, who is pitching in the Cactus League for the first time in his career. After allowing a home run off a hanging slider, he sought consolation from his new teammate, Logan Webb.

“I was told not to overconcern yourself with pitch shapes here and the movement of the ball because it’s tough,” Verlander told Maria Guardado of MLB.com after his start. “It’s my first spring training in Arizona, so everyone was like, ‘Hey man, it’s a little different out here.’ I’ve heard it from everyone. But I think you still need to be honest with yourself.” Read the rest of this entry »

Nobody wants to throw a backup slider. They are, definitionally, an accident. But announcers and analysts alike have noted that these unintentional inside sliders — perhaps due to their surprise factor — tend not to get hit. In 2021, Owen McGrattan found that backup sliders, defined as sliders thrown inside and toward the middle of the strike zone, perform surprisingly well.

I’ll add one additional reason these pitches are effective: They move more than any other slider.

I analyzed over 33,000 sweepers thrown by right-handed pitchers in the 2024 season. I found a clear linear relationship between the horizontal release angle of a sweeper and the horizontal acceleration, better understood as the break of the pitch. On average, as the horizontal release angle points further toward the pitcher’s arm side, the pitch is thrown with more horizontal movement.

Josh Hejka, a pitcher in the Philadelphia Phillies minor league system, told me these results corresponded with his anecdotal experience.

“I’ve often noticed — whether in game or in the bullpen — that the sliders I throw arm side tend to actually have the best shape,” Hejka said. “I believe it’s conventional wisdom across baseball that the backup sliders tend to actually be the nastiest.”

Check out all the movement Corbin Burnes gets on this backup slider from last season.

The relationship between horizontal release angle and movement also holds true for sinkers. When a sinker is aimed further to the glove side — for pitchers facing same-handed hitters, this would be a backdoor sinker — the pitch gets, on average, more horizontal movement, as is the case with this pitch from Anthony Bender.

The explanation for the relationship is straightforward enough. When sweepers are thrown to the arm side and sinkers are thrown to the glove side, the pitcher’s grip is such that maximum force is applied to the side of the baseball, allowing for more sidespin. In a 2015 interview with David Laurila, then-Royals pitching coach Dave Eiland described why sliders back up.

“They really get around it; they don’t get over the top and pull down,” Eiland said. “It’s unintentional, more of a misfire, so to speak. If you could do that intentionally, you’d have a decent pitch.”

It isn’t just sweepers and sinkers that show a relationship between release angles and movement. Back in August, I investigated the mystery of the invisible fastball. Why was a pitch like Shota Imanaga’s fastball, with its elite vertical movement and flat approach angle, so rare? I found that vertical release angles mediate the relationship between both variables. A fastball thrown with a flatter release angle gets less backspin, and so to achieve both requires outlier mechanical skills.

Release angles don’t just measure the nature of a grip, they also dictate the location of the pitch. I conclude that where the pitcher aims a pitch changes the way it moves. For fastballs, pulling down on the ball allows for more backspin. For sweepers and sinkers, getting around the ball allows for more sidespin. Analysts attempt to separate “stuff” from “location;” these findings complicate that conversation.

***

Before we go any further, it’s important to know what exactly is a release angle. Release angles measure — or, in this case, approximate — the angle at which the ball comes out of the pitcher’s hand. For vertical release angles, anything above zero degrees suggests the ball is pointing upward at release; most vertical release angles, particularly for four-seam fastballs, are negative, meaning that the pitcher is aiming the ball downward at release.

Horizontal angles work the same way, but in the x-dimension. Positive values mean the ball is pointed toward the pitcher’s left; negative values point toward the pitcher’s right. (This is a feature of the original Pitch F/X coordinate system, when it was determined that x-dimension pointed to the catcher’s right.) In any case, release angles, both horizontal and vertical, attempt to capture the exact position of the ball at release. Because they capture the position of the ball at release, they contain information about the pitcher’s aim and, it turns out, the force they’re applying to the ball.

My research finds that there is a relationship between horizontal release angles and horizontal acceleration. In simpler terms, the way the ball is released out of the hand, and therefore where it is aimed, impacts the movement of the pitch.

There are some confounding variables in this specific relationship. The Hawkeye cameras (and, in earlier times, the Pitch F/X technology) report accelerations in three dimensions. These accelerations are measured relative to a fixed point on the field, which happens to be right in front of home plate. Because these accelerations are fixed to one point, the reported values can be biased by the position of release in space. This is far from intuitive, so it might be helpful to consider an example.

Remember that Burnes sweeper from the introduction? It accelerated at roughly 16 feet per second squared in the x-dimension. Imagine that instead of throwing his sweeper from the mound, Burnes threw it from the third base dugout. It’s the exact same pitch as before — same velocity, same horizontal break — but the release point has completely changed. On a fixed global coordinate system of movement measurement, the acceleration in the x-dimension no longer describes the pitch’s relevant movement; all that sideways movement would instead be measured in the y-dimension.

This is an extreme example to illustrate the point, but on a smaller scale, this fixed point measurement system biases acceleration measurements. In order to fix this bias, accelerations can be recalculated to be relative to the pitch’s original trajectory, removing the influence of the release point on the acceleration value. These calculations come courtesy of Alan Nathan; Josh Hejka rewrote them as Python code, making my job easy.

A slight nuance:

The accelerations given by MLB (ax, ay, az) are biased by pitch location.

To make these values location-agnostic, we need to adjust the acceleration vector to be relative to the initial trajectory (i.e. the initial velocity vector vx0, vy0, vz0).

?: https://t.co/CVVNKtG3YM

— Josh Hejka (@hedgertronic) November 14, 2024

Even after accounting for these confounding variables, the relationship between release angles and movement is still present. As the plot shows, it isn’t a particularly strong relationship — when modeled, a two-degree change in horizontal release angle is associated with roughly a foot per second increase in transverse acceleration. But while the relationship is not as strong as that between four-seam fastballs and vertical release angle, it is nonetheless meaningful.

Alternatively, the relationship can be measured using good old-fashioned “pfx_x,” or horizontal movement, which is also measured relative to the pitch’s original trajectory. Why go through all this effort to transform the accelerations? For one thing, I had a good time. And also, isn’t it fun to imagine Burnes throwing sweepers from the dugout?

The plot of horizontal location and horizontal movement, with each pitch colored by its horizontal release angle, illuminates the ostensible lack of a relationship between pitch location — measured by “plate_x” on the plot below — and movement. Draw your attention to the patch of dark blue dots around the -2 line of the x-axis. There are two potential ways for a sweeper to end up two feet off the plate inside. It can be thrown with a horizontal release angle around zero and little sideways movement, or it can be thrown with a negative horizontal release angle and lots of sideways movement.

The same relationship holds true for horizontal release angles and two-seam fastballs after the aforementioned adjustments.

On the individual pitcher level, the relationship is slightly weaker; on average, the r-squared is roughly 0.04 for sweepers, with variation between pitchers on the strength of this relationship. Zack Wheeler’s sweeper movement, for example, appears to be particularly sensitive to release angles:

***

Ultimately, analysts attempt to separate “stuff,” defined as the inherent quality of a pitch, from “location,” defined as where the pitch ends up. But what this research suggests is that, to some degree, these two qualities are inseparable. (I wrote about this a bit on my Pitch Plots Substack last September.) Certain pitches generate their movement profiles because of where they’re aimed out of the hand.

These findings naturally lead to deeper questions about the interaction between biomechanics and pitch movement. While there are variables (arm angle, release height, etc.) that are commonly understood to influence movement, these findings suggest that there are even more granular factors to explore.

Is the angle of the elbow flexion at maximum external rotation the most influential variable? Is it hip-shoulder separation? Torso anterior tilt? Pelvis rotation at foot plant? How much do each of these components contribute to pitch shapes?

Thanks to data from Driveline’s OpenBiomechanics Project, it’s easy to model the relationship between dozens of biomechanical variables and the velocity of the pitch. There are about 400 pitches in the database; by attaching markers to a pitcher moving through space, points of interest can be calculated and then compared to the pitch’s velocity.

In this public dataset, Driveline does not provide the movement characteristics of the pitch. But if the force applied to the ball based on the direction of its aim affects the movement of the pitch, it follows that these variables could be measured in a detailed manner. On the team side, KinaTrax outputs provide the markerless version of these data, providing a sample of hundreds of thousands of pitches from a major league population. Imagine the possibilities.

Correction: A previous version of this article misstated the units of acceleration of Burnes’ backup sweeper. It is feet per second squared, not feet per second.