There is no baseball topic that gets me more excited than swing diversity. A player’s swing is like a fingerprint: No two are the same. But even similar swings can yield extremely different results. There are many ways to compare swings, but because Vertical Bat Angle (VBA), the angle of the bat at contact relative to the ground, is the most accessible (thanks, SwingGraphs), it’s been my go-to proxy for the last year or so. Of course, you can always use your eyes to visually analyze swings, but having the data to confirm it helps inform the evaluation.

Lately, my video evaluations have focused on hitters with steep VBAs, and even among this group there is a ton of swing diversity. Some take golf-like swings to get to their steep planes and others employ one of my favorite styles: the chicken-wing swing.

Intuitively, it makes sense that hitters with steeps paths are more prone to whiffs than those who have flatter swings. Even so, some of the game’s best contact hitters have swings as steep as some of those who are the most whiff prone. Luis Arraez, for example, has a swing that is just as steep as J.D. Martinez’s, at least according to VBA. Without the data to confirm, it’s hard to know if the same holds true for Attack Angle (AA), the angle of the bat’s path at impact.

To show you exactly what I mean, I’ll compare pairs of hitters with nearly identical average VBAs, but different offensive profiles. A few weeks ago, Davy Andrews wrote about Edouard Julien and the bizarre nature of his platoon splits (and a tune to go along with it). His entire offensive profile drastically changes depending on if he’s facing a lefty or righty. It’s fascinating. After I read the piece, I was immediately curious as to how those trends might relate to Julien’s swing path. At 40 degrees, Julien has one of the steepest VBAs in the majors. It’s almost a perfect diagonal. Here are a few slow motion swings that showcase that:

No matter how high or low the pitch is, Julien manages to get his bat on a diagonal, which last year helped him run an xwOBACON of .443, well above average. His diagonal angle also allows him to crush fastballs. He had a .408 wOBA against heaters but struggled mightily (.287 wOBA) vs. breaking balls. Production against different pitch types is where you tend to see some deviation between hitters with similar VBAs. Like Julien, Freddie Freeman is also a lefty batter with a steep VBA (41.7 degrees), yet despite their similar angles, Julien ran a 44.3% whiff rate against breaking pitches, while Freeman’s whiff rate vs. breaking balls was 27.7%. There are swing components other than VBA that contribute to how such divergence can happen. But before getting to that, let’s check out some of Freeman’s swings from 2023:

Man, Freeman is smooth. Because both he and Julien set up with high hands, they can create a steep path at different pitch heights. This setup allows them to drop their barrel easily and rely on changing posture to adjust to locations. How they do it, though, is where their swings differ. Julien uses more aggressive movements to get to different pitch heights, while Freeman shifts his shoulder plane and avoids more drastic body adjustments. His chicken-wing style is a bit more handsy and less reliant on changing his eye level, and as a result, he has excellent plate coverage. His contact rates on pitches at the top, bottom, and outer thirds of the zone outpace Julien by about eight percentage points in each location.

Two other factors, which are not publicly available, also likely contribute to Freeman’s superior plate coverage: Horizontal Bat Angle (HBA), the horizontal angle of the bat at impact, and bat speed. Freeman, who we’ve already established has a steep VBA on average, appears to be better at altering his swing speeds when necessary, which lets him manipulate his bat angle to cover pitches throughout the zone. You can see this in the third video above, on the changeup breaking down and away from him.

Freeman’s approach also helps him produce against lefties (career 120 wRC+), which is something he has improved upon as he has gotten older (139 wRC+ over the last three seasons). Meanwhile, Julien’s daddy-hack approach sometimes limits his ability to alter his swing speeds and angles, which can often lead to poorly timed swings or mishits and explains why he is prone to hitting groundballs (50.2% last year) despite his steep swing. These issues are more apparent when he faces lefties (22 wRC+, 80% groundball rate), though as Davy pointed out in his Julien piece, he has made only 48 plate appearances against lefties in the big leagues — an incredibly small sample size.

That brings us to the next hitter, Tim Anderson. Even with his steep 39.5-degree VBA, Anderson had a groundball rate above 60% last year. A batter’s contact point has to be extremely deep to pull that off. Here are some swings from him to illustrate that:

Most hitters would struggle to put the ball in play after letting it travel this deep, but TA’s steep barrel and feel for contact in the zone allowed him to pound the ball into the ground over and over and over again last season. The sweeping breaking ball from Rich Hill is the exact type of pitch Anderson would have elevated in years past. Typically, having a steep bat path against an opposite-handed breaking ball is a perfect recipe for an ideal launch angle distribution, but if you’re making deep contact, this is all you can get out of the swing.

Chas McCormick was the anti-Anderson last season, when he mostly refused to hit the ball on the ground against opposite-handed pitching. He can do this because of how he marries his steep, 38.2-degree VBA with ideal contact points. In 2023, he had a 25.6 GB% against left-handed pitchers. That was the third lowest in baseball behind Jorge Soler and Mookie Betts. Unsurprisingly, by wRC+, they were three of the six most productive right-handed hitters against lefties last year. Here are a few swings from McCormick vs. lefties that show his ability to elevate no matter the zone or pitch:

Even on the well-executed curveball from MacKenzie Gore, McCormick’s barrel was on an upward slope at contact because he connected with the pitch out in front of the zone. This is the type of pitch that Anderson would have pounded into the ground despite the similar steepness at contact, because he would’ve let the pitch get deeper before swinging.

McCormick’s closed stride puts him in a great position to elevate any pitch in the middle of the plate, even if it makes it more difficult for him to square up inside pitches in the top half of the zone. That said, as you can see in the video of his swing against Cole Ragans, he can still get to up-and-in pitches when he holds his posture. The main takeaway is that no matter the zone, his barrel is working on an upward slope through contact, which allows him to do more damage.

Although their swings are similarly steep, these four hitters have different swing types that generate different results. VBA is a great tool to use, but it only tells one part of the story.

I imagine that everybody here at FanGraphs generates ideas for articles in different ways. Looking at leaderboards is certainly a common method. You click around, sorting by different stats until someone looks out of place. “How did you get all the way up here?” is what the start of a FanGraphs article sounds like. Sometimes ideas take longer to germinate, and sometimes there are twists and turns along the way.

For a while now, I’ve been noticing that Freddie Freeman always seems to pop up near the top of Baseball Savant’s foul ball leaderboard. He finished second to Ozzie Albies in 2023 and second to Bo Bichette in 2022. In 2021, he finished third behind both Bichette and Albies. He finished third again in 2020 and first in 2019, 2018, and 2016. Freeman is one of the best hitters in the game, and since 2016, he has 4,225 foul balls, over 400 more than Francisco Lindor in second place. The names below them are good too: José Abreu, José Ramírez, Marcus Semien, Paul Goldschmidt. You get the picture. That brought me to my first question:

Are foul balls the mark of a good hitter?

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A few articles ago, I was engaging in one of my favorite pastimes: making up the names of non-existent statistics. What can I say? I got into writing because I like lining words up in funny ways. I got into baseball writing because I love baseball. But when the two things I like line up, then we’re really cooking with gas.

The fake statistic in question? Whomps per whiff. You can grasp what it is right away: how often you absolutely whomp the ball, as compared to how often your swing results in nothing but a tiny gust of air and perhaps an emphatic umpire reaction. Is this a predictive statistic? I have no idea whatsoever, but I thought I’d try to see who’s good at it.

The good news: The good players are good. I defined a whomp as a barrel, a whiff as a whiff, and then limited it to players who saw at least 500 pitches in 2023. The best in baseball at it? Ronald Acuña Jr., who just put up an all-time offensive season. Neat! Second best? Mookie Betts, who finished second in MVP voting behind Acuña. Maybe we’re on to something here. Here’s the top 10 by that metric:

One thing that I love about this statistic is that it isn’t secretly ranking players based on their plate discipline. Betts doesn’t swing much, so he doesn’t whiff much. Seager is aggressive but selectively so. Luis Arraez is 12th. Lars Nootbaar is 13th. Those two are polar opposites who nonetheless are both good hitters.
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I thought that today’s article was going to be an easy one to write. Reading Alex Chamberlain’s post on the pulled fly ball revolution made me imagine the worst pitch a pitcher could throw: a sinker that ended up high and inside, an easy-to-contact fastball in the area of the plate that leads to the most damaging types of opposing batted balls. Then I extrapolated my idea out a little bit. Maybe I could look up the pitchers who throw their sinkers high in the zone most often. We could all laugh about how they’re called “sinkers” — so that’s clearly a bad place to throw them. Maybe we would gawk at a table of a few pitchers who do this bad thing, and then we could move on with life.

Well, I can do at least one thing. Here’s a table of the pitchers who threw elevated sinkers in or around the strike zone most frequently in 2023:

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I’ll lead with this: I’m not certain the Launch Angle Revolution^TM was ever really a thing — or at least, it wasn’t a thing in the way we thought it was. In 2019, we were faced with an onslaught of home runs that needed an explanation, a genesis. It made sense to turn to launch angles: all else equal, if you hit balls higher, they tend to travel farther. As we’d later learn, juiced balls were much more a culprit than anything else. I wish I could find the sound byte for it – my squishy memory may have manufactured it – but I swear I recall Christian Yelich, perhaps the juiced ball’s most prominent (though, to be clear, not necessarily its biggest) beneficiary, scoffing at the concept of a “launch angle swing.” (Edit: It’s here! Thanks, Mike Petriello!) Although Yelich’s fly ball rate jumped 13.4 percentage points in 2019, he (arguably rightly) denounced the very idea of what everyone assumed had fueled his success.

There is, however, unquestionably another revolution afoot: the Pulled Fly Ball Revolution^TM. Inherently, it’s its own kind of launch angle revolution. But it’s also a spray angle revolution, and a pitch selection revolution, and a swing decision revolution. It is multifaceted and sprawling, and it is much more clearly defined than its predecessor. Here’s the percentage of batted ball events (BBE) that were pulled fly balls (PFBs, for short) by year:

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I don’t think I’m alone in my fascination with pulled fly balls. In fact, I know I’m not, because Alex Chamberlain wrote about them today too. These days, we’re practically drowning in data: exit velocities, launch angles, chase rates, aggression rates — the list goes on and on. There are so many different ways of thinking about exit velocity that you can read an entire great article about what they all mean. If you want to translate how hard someone hits the ball into how they’re likely to perform, there’s no shortage of instructive articles. But in that deluge of data, horizontal angle has been left out, for reasons both purposeful and accidental, and the unavailable is always interesting.

Earlier this month, I did some idle digging into what pull rate means for production on contact. The takeaway was, to be generous, middling. It seems like pulling your aerial contact results in better overall production on that contact, but the effect isn’t huge. Perhaps the more interesting takeaway was that xwOBA on these batted balls had a bias: the more pull-happy the hitter, the lower their xwOBA was on the balls they hit in the air. That was the case despite greater overall production on those balls.

That’s a weird little artifact, though I didn’t think too much of it because I kind of knew what it would say in advance. Every time I look at a dead pull fly ball hitter, they’re getting home runs out of batted balls that xwOBA hates. But that doesn’t mean the statistic is working incorrectly; it’s doing exactly what it says on the label by bucketing batted balls based on exit velocity and launch angle. Read the rest of this entry »

For a while now, I’ve been having fun analyzing how accurate umpires are when calling balls and strikes according to the Statcast strike zone. Honestly, I might be having too much fun. It’s just that there are so many variables that might affect the way the umpire sees a pitch. Today we’re looking into the most literal one: the ballpark. Every stadium is different, and that can affect how easy it is to track the baseball. This is a well-established issue, which is why every ballpark has a batter’s eye, a dark background that’s supposed to ensure that the batter is able to see the ball out of the pitcher’s hand. Those backdrops vary quite a bit, from evergreen trees and ivy in Colorado, to a painted wall in Texas, to tinted glass in the Bronx.

When Drew Smyly nearly threw a perfect game last April, it helped that it was a day game at Wrigley Field, and his left-handed release point was so wide that the ball appeared to be coming not from the batters eye, but from the bleachers in right-center. Last September, in response to multiple public complaints from players, the Astros effectively extended Minute Maid Park’s batter’s eye several feet farther into right field, awkwardly repainting part of a formerly red section of brick and signage green. “It’s like night and day,” one player told The Athletic after the paint job:

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As I write this, I’m in a fair amount of discomfort. I went to the dentist’s office for a routine filling and next thing you know, bam, root canal. I’m a little out of it, is the point, and in my dental chair daze, I did what everyone probably does when they’re upside down with blood rushing to their head for a long time: I started musing about Isaac Paredes.

Oh, I hear you. This isn’t what normal people do when they’re discombobulated, not even a little bit. To that I say, you’re not wrong. Also, though, I’m not a normal person. This is my job, and daydreaming about work is inevitable, not weird. In any case, I came up with an incredible idea, a way to work out the next Paredes before teams did. I was a genius. Here’s the bad news, though: I don’t really remember it now that I’m lucid again.

That’s a bummer, but it’s OK, because in trying to reconstruct my thoughts, I think I came up with a pretty cool way of contextualizing how much it pays to sell out for pulled contact. As an added bonus, I got to pore over a ton of data and play with it to my heart’s content. That’s the dream, coming up with some silly junk stat in a haze and then spending hours manipulating data to show that it’s worthwhile.
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About a year ago, I wrote about how umpires have improved at calling balls and strikes throughout the pitch tracking era. They have gotten a whole lot better, especially at identifying strikes. While everyone appreciates a more consistent and accurate zone, that has made things a bit harder for hitters overall. More importantly, their progress didn’t seem like it was showing any signs of slowing down. With the 2023 season in the books, it’s time to check in on whether that’s still the case. The methodology here is simple: check to see if Statcast agrees with the umpire’s decision for each called ball and strike. This isn’t a perfect method, as a pitch right over the heart of the plate is a much easier call than one right on the edge, but the enormous sample sizes (there were 376,635 takes in 2023) mean that things even out over time.

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The other day, my friend asked me a simple baseball question with no easy answer: What does a four-seam fastball look like? Not what is a four-seam fastball, or what does a four-seam fastball accomplish, or any number of fastball-related questions with more straightforward answers. He wanted me to conjure up an image of the most common pitch in baseball. I didn’t quite know what to tell him; strangely enough, the more ordinary something is, the harder it can be to describe.

My friend is merely a rhetorical device, but I’ve already grown attached to him, so let’s call him Tony. Tony is a casual observer of baseball. He hears terms like “fastball” and “curveball” and “the Dodgers are ruining the game” every now and then, but he doesn’t have the requisite context to understand what any of it really means. How do I show Tony what a four-seam fastball looks like in 2023? After all, every pitcher works differently. The velocity gap between Jhoan Duran’s and Rich Hill’s four-seam fastballs is the difference between a speeding ticket and losing your license. Explaining to Tony that those two offerings are technically the same pitch would be like trying to convince an alien that a Bergamasco Shepherd and a Xoloitzcuintli are the same species. It’s factually correct, yet without hyper-specific evidence – and the background knowledge necessary to interpret that evidence – it’s all but impossible to believe.

I could show Tony some video of Félix Bautista to illustrate the ideal four-seam fastball. Alternatively, I could show him Andrew Heaney as an example of a perfectly average four-seamer instead:

Yet Tony didn’t ask about results, be they average or exceptional. He wants a visual point of reference, and simply put, neither of those two throws a visually conventional heater. Reaching triple-digits on the radar gun remains a rarity, and Bautista does it more often than most. Meanwhile, Heaney throws his fastball with over 15 inches of arm-side run; that’s 70% more horizontal movement than the average four-seamer of a similar speed and release point. On the graph below, Heaney sits way over on the right, and only two dots (min. 500 pitches) can be found farther in that direction:

What Tony really wants to see is the prototypical four-seam fastball, the pitch that most closely resembles the norm in as many material ways as possible. Identifying the man who throws such a pitch won’t serve a practical purpose; it won’t help teams win ballgames, fans win their roto league, or Harold Ramírez lay off all those four-seamers outside the zone. Still, it’s nice to have a baseline for the most important pitch in baseball – or any pitch for that matter. Thus, I set out to find the pitchers who throw the pitches that best exemplify what each pitch looks like in the game today.

A project like this requires a good deal of subjective decision making. No one throws a pitch perfectly identical to league average in every measurable way. Heck, even if someone did, who’s to say that average is the same as normal. The league average four-seam fastball last year clocked in at 94.2 mph, but the average reliever threw nearly a full mile per hour faster than the average starter. With that in mind, would it be incorrect to say that a starter who boasts a 94.2 mph heater is throwing with typical velocity? On top of that, pitchers who throw harder fastballs tend to throw better fastballs, which means they get to throw more fastballs. Therefore, they influence the league average to a greater extent than their less prolific peers. The average velocity of the 43 starters who threw at least 1,000 four-seam fastballs last season was 1.2 mph faster than the average velocity of the 216 starters who threw between 50 and 999 of the same pitch. Should those fewer, faster pitchers have such an outsized influence on the overall numbers? With all that said, I’m sticking with league average as my baseline (for lack of a perfect alternative, if nothing else), and I hope you’ll stick with me as I explain the rest of my decisions.

Next, I had to figure out how to narrow down the list of possible candidates. Seven-hundred and thirty-one players threw a four-seam fastball in the major leagues last year, and I wasn’t going to get anywhere if I gave each of them a close look. (Sorry Tony, even I have my limits.) Thus, I set 100 four-seam fastballs as my arbitrary minimum requirement, and I chose to prioritize one attribute above all else: velocity. It’s called a fastball, after all.

Seven pitchers (min. 100 pitches) averaged exactly 94.2 mph on their four-seam fastball. Another 18 sat at 94.1 or 94.3 mph, and I included those arms in my search to allow for candidates who might be a rounding error away from league average. That gave me 25 pitchers to work with, 19 right-handers and 6 southpaws. I hemmed and hawed over whether to include lefties at all, and ultimately I put off making a decision in hopes I wouldn’t have to. Thankfully, that proved to be the case, as none of the top candidates were left-handed.

Armed with 25 contenders and a Google spreadsheet, I hopped on Baseball Savant, looking for as many physical pitch characteristics as I could find and manipulate. I settled on nine: vertical release point, horizontal release point, extension, perceived velocity, vertical movement, horizontal movement, spin rate, total movement, and active spin. After calculating the standard deviation of each metric, I returned to my 25 candidates. Did anyone fall within one standard deviation of league average in every category?

Well Tony, today is your lucky day. One pitcher, and only one pitcher, fit the bill. One pitcher was within a single standard deviation of league average in all nine of the aforementioned metrics. That same pitcher came within half a standard deviation in seven categories, within a quarter of a standard deviation in five categories, and within an eighth of a standard deviation in four. No one else came closer at any step along the way. The owner of the most ordinary four-seam fastball in baseball is José Berríos.

Wow… Let’s take a minute to marvel at the regularity. Here’s how Berríos threw his four-seamer in 2023:

And here is how he stacks up to Alec Marsh, the next closest competitor and, as I discovered, a player for the Royals, not the title of a Phillies day care fan fiction. I’ve also included league average numbers in the table for additional context:

I considered making a case for Marsh on the basis of speed alone. At the beginning of my search, I said I would prioritize velocity, and his 94.2 mph average was right on the money. However, Berríos’s 94.3 mph average velocity was actually rounded up from 94.25 mph. In other words, if he had thrown just one additional fastball at 92.3 mph or slower (he threw 27 such pitches last year), his season average would have fallen to 94.2. It’s simply too close to take the title away from him.

Interestingly, Berríos’s four-seam fastball wasn’t quite so ordinary until this past season. For most of his career, he threw the pitch with less rise and more run than the typical four-seamer. However, in 2023, his four-seamer had more vertical movement and less horizontal movement than it had since his breakout campaign in 2018:

My quest for the platonic ideal of a four-seam fastball was so fruitful that I decided to perform a similar search for sinkers and cutters. I still prioritized velocity, but for this investigation, I also took movement into account to narrow down the contenders. Call me a literalist, but I say the typical sinker needs to sink, and the typical cutter needs to cut.

Starting with sinkers, I picked out the 12 pitchers who came within one-quarter of a standard deviation of league average in velocity and within half a standard deviation in both vertical and horizontal movement. Next, I compared them all to league average in each of the additional categories I previously identified. Unfortunately, there wasn’t quite as clear of a winner this time around.

Only one pitcher, Colin Rea, finished within one standard deviation of league average in every metric (including mph). However, eight others finished within one standard deviation in nine out of 10. When I narrowed the criteria to half a standard deviation, Rea remained in the lead, meeting the criteria in nine of the 10 metrics, but he was tied with three other pitchers: Mitch Keller, Miles Mikolas, and Bryse Wilson. Meanwhile, at a quarter of a standard deviation, Rea reclaimed sole position of first place (eight out of 10), but three more arms were right on his tail with seven: Mikolas, Pedro Avila, and Brandon Pfaadt. What’s more, one of the metrics in which Rea wasn’t particularly close to league average was vertical movement, and that seems pretty important for a sinker. Among the quartet of Rea, Mikolas, Avila, and Pfaadt, only Avila came within a quarter of a standard deviation of league average in vertical movement. Finally, when I went down to an eighth of a standard deviation away from league average, Rea lost his crown to Avila, who came that close to league average in six different metrics. Rea and Noah Davis finished right behind him with five each.

The names that came up most often in the previous paragraph were Rea, Avila, and Mikolas. However, only one of those three threw his sinker with precisely league-average velocity. Indeed, only one of those three came within half a mile per hour of average. What’s more, that same pitcher was the only candidate out of 12 who came within an eighth of a standard deviation of league average in both vertical and horizontal movement, and one of only two who came within a quarter: Pedro Avila.

Likewise with the cutter, there were no exact matches. I picked out the 14 contenders who came within half a standard deviation of league average in velocity and both planes of movement, but none of those 14 came within one standard deviation of league average in every other metric. Nonetheless, there was still a clear winner. Only one pitcher came within half a standard deviation of average in nine categories, within a quarter in six categories, and within an eighth in five. He was one of only four pitchers within half a standard deviation of league average in both vertical and horizontal movement and within a rounding error of league average in velocity. And out of those four, he was easily the closest to league average in release point and extension. It’s Javier Assad.

Here at FanGraphs, we pay a ton of attention to average performance. The concept of “league average” informs some of our most foundational stats. We even have a tab on the leaderboards page (+ Stats) dedicated to precisely that. It’s not hard to see why; a good sense of average performance, whether for a team, a player, or an individual skill, has all sorts of practical applications. Sometimes, however, it’s just as interesting to take a step back from results and focus on the process instead. We talk a whole lot about four-seamers, sinkers, and cutters, and it’s helpful to visualize those concepts as best we can. In 2023, it was Berríos, Avila, and Assad who made that possible.

So, there you have it, Tony. It’s been fun! Let’s grab a coffee sometime soon.