I continue to find Statcast’s bat tracking data fascinating. I also continue to find it overwhelming. Hitting is so complex that I can’t quite imagine boiling it down to just a few numbers. Even when I look at some of the more complex presentations of bat tracking, like squared-up rate, I sometimes can’t quite understand what it means.

I’ll give you an example: when I looked into Manny Machado’s early-season struggles last week, I found that he was squaring the ball up more frequently when he hit grounders than when he put the ball in the air. That sounds bad to me – hard grounders don’t really pay the bills. But I didn’t have much to compare it to, aside from league averages for those rates. And I didn’t have context for what shapes of squared-up rate work for various different successful batters.

What’s an analyst to do? If you’re like me in 2024, there’s one preferred option: ask my friendly neighborhood large language model to help me create a visual. I had an idea of what I wanted to do. Essentially, I wanted to create a chart that showed how a given hitter’s squared-up rate varied by launch angle. There’s a difference between squaring the ball up like Luis Arraez – line drives into the gap all day – and doing it like Machado. I hoped that a visual representation would make that a little clearer. Read the rest of this entry »

Like many other nerds, I have devoted a lot of time to slicing and dicing Baseball Savant’s new bat tracking data over the last few weeks. And like many other nerds, I’m not entirely sure how we’ll end up using this wealth of new information. More time, more data, and more brain power is needed to wring out whatever sweeping new truths it may hold. I’m going to write about bat tracking data in a more focused way next week. There are a couple things I think are really interesting; not necessarily new information, but ways that bat tracking data can give us hard numbers for things that we’ve already learned. In this article, I’ll be a bit more scattershot. I’d just like to take you through how I’ve processed all the information that has come out over the last few weeks.

First off, bat tracking will give us new stats that stabilize more quickly than existing ones, as that’s how granular metrics that separate underlying skills from results tend to work. In smaller samples, exit velocity turned out to be a better predictor of overall batting performance than wRC+ or wOBA. Now we have swing speed, which in smaller samples turns out to be a better predictor of exit velocity. To wit, I pulled data from the first week of bat tracking, April 3 to April 9, and compared it to each player’s overall numbers this season. I eliminated any player with fewer than five plate appearances during the first week or fewer than 100 PA during the entire season, which left me with a sample of 295 players. It was no contest. Full-season exit velocity had a much stronger correlation to first-week swing speed (R = .60) than it did to first-week exit velocity (R = .40). It also predicted full-season hard-hit rate better than first-week hard-hit rate (R = .66 for swing speed, compared to R = .46 for hard-hit rate). If, after the first week, you want to know who’s going to hit the ball hard for the rest of the season, don’t look at exit velocity. Look at swing speed:

Read the rest of this entry »

Season one of One Tree Hill is a perfect season of television, and I will not be entertaining arguments to the contrary. In it we meet Nathan and Lucas Scott, the sons of hometown basketball hero, Dan Scott, who runs a local car dealership. Nathan was raised in the traditional nuclear family structure by Dan and his college sweetheart and wife. Lucas was raised in a single-parent household by his mother, Dan’s high school sweetheart. Despite sourcing their foundational genetic material from the same DNA pool, Nathan and Lucas are depicted at odds with one another in several key ways. Nathan is his father’s golden child and characterized as hyper competitive, entitled, and emotionally stunted; Lucas receives no acknowledgement from Dan and skews more intellectual, reserved, and empathetic. Both are super good at basketball and both crave the approval of their father. Nathan seemingly has it all, but presents as lonely and ill at ease in his environment. Lucas drew the short straw, but is mostly content and supported by several meaningful relationships.

The whole concept is a pretty straightforward exercise in nature vs. nurture, and if you haven’t seen One Tree Hill, don’t worry, I haven’t spoiled anything; this is all part of the show’s initial setup in the pilot episode. What the viewer is intended to puzzle out as the season unfolds is how much of Nathan’s arrogance and aggression is a reaction to his surroundings and how much is an inherent part of his character. And on the other hand, can Lucas, against his father’s wishes, learn to thrive in new surroundings as he steps into the spotlight of varsity basketball? Or is he more naturally suited to exist in the shadows?

I recently read almost six years of scouting reports, statistical breakdowns, and interviews covering two prospects from the 2018 MLB draft in an attempt to to understand the how and why of each player’s career arc. More on that later, but for now, I want to emphasize how much easier it is to analyze a teen soap opera. And it’s not that the scouting reports were unclear, or that the statistical analysis was misleading, or that the players misrepresented themselves in interviews. It’s that taking 18- to 22-year-olds and turning them into big leaguers is a hard thing to do under the best of circumstances. Read the rest of this entry »

The fastball is dead. Or is it?

Every season has its share of articles detailing the league-wide decline in fastball usage, and 2024 is no exception. This time around, the spotlight has been on the Red Sox, who have seemingly crafted an elite rotation based on a delightfully succinct philosophy: Spin go brrrr. Indeed, they trail the league in four-seam fastball usage by a wide margin. But they’re also ninth in sinker usage and first in cutter usage as of this writing. This is incredibly interesting to me, especially after you consider the graph below:

In early counts (0-0, 0-1, and 1-0), when batters are more eager to swing and hunt for fastballs, we’ve reached a new minimum for four-seam fastballs. That checks out. But look at the combined rate of sinkers and cutters: It’s back up to levels last seen in 2018. So really, the Red Sox aren’t being hipsters. If anything, they represent what the league is thinking as a whole. The uptick is there, even if you exclude Boston. Read the rest of this entry »

For the last few years, I’ve been checking the accuracy rate of the ball-strike calls made by umpires, dividing the number of correct calls by the total number of takes. It’s a blunt approach, but because umpires make so many thousands of calls each year, it yields solid results. On Tuesday, I pulled the numbers for the 2024 season, and I found something I didn’t expect: Accuracy is going down rather than up. In every single season since the beginning of the pitch tracking era in 2008, umpires have gotten better at calling balls and strikes according to the Statcast strike zone. This is the first time I’ve ever pulled the numbers and seen a lower accuracy rate. However, this is also the first time I’ve checked the numbers this early in the season, and it turns out umpires tend to make better calls as the season goes on. Since 2017, accuracy in March, April, and May has been 0.19 percentage points lower than accuracy over the full season (though the difference in 2023 was just 0.03 percentage points). Here’s what that looks like in a graph.

You know how at the beginning of every season, there are a couple blown calls during a nationally televised game (or at least, calls that appeared to be wrong according to the on-screen strike zone), and certain people start complaining that umpires are terrible and they’re getting worse? Those people always catch me off guard. I usually forget about the missed calls when the season ends, but those people somehow manage to keep their umpire anger at a high idle through the entirety of the offseason so that the instant baseball returns, they’re ready to shout about the umpires again without any need to ramp up. I don’t know how they do it without pulling an oblique, but in a sense, those angry people are right. Even though the umpires are always getting better year after year, they’re nearly always more accurate toward the end of the season than at the beginning — so much so that when the season starts, they’re worse than they were at the end of the previous season. For a month or two, the umpires really have gotten worse. We often say early in the season that pitchers are ahead of hitters. It turns out they’re ahead of umpires too.

For each season, I broke down the overall accuracy in two-month increments, essentially dividing the season into thirds. I also broke down the accuracy during spring training and the playoffs, although there are plenty of factors that make those numbers suspect. During spring training, the umpiring pool is much wider. Perhaps more importantly, there are far, far fewer tracked pitches during spring training, both because the number of games is so small and because not every stadium is set up for Statcast. That results in a much smaller, much less reliable sample. The playoffs are also a much smaller sample, but they’re also, at least in theory, selecting for better umpires. Working the playoffs is seen as an honor and a reward for performing well in the regular season. We should expect accuracy to be at its lowest during spring training and highest during the playoffs.

Generally speaking, the results fit our preconceptions. Spring training accuracy is very low and it features the volatility that we’d expect from a small dataset. Umpires are also more accurate in the playoffs. The red line is March, April and May, and as you can see, it’s nearly always below everything but the spring training line. Not only do umpires start getting better in June, but they keep getting better right through the end of the season, which is why the light blue line for August, September, and October is usually above the yellow line for June and July. The trend is a little bit easier to see if we focus just on pitches in the shadow zone, the area that’s one baseball’s width from the edge of the zone on either side.

In the graph above, the dotted line represents that season’s overall accuracy on calls in the shadow zone. Each data point represents the number of percentage points above or below that year’s average. Not only do the calls get better as the season goes on, there’s a definite gap between the first two months and the rest of the season. Umpires are decidedly worse in those first two months. However, 2023 was a real outlier. It was first time since 2008 that umpires were more accurate in the beginning of the season than the end.

With that, I want to bring you back to 2024. So far this season, umpires have gotten 92.46% of calls right, down from 92.81% in 2023 and just two thousandths of a percentage point higher than in 2022. Based on everything I’ve shown you, we should expect umpires to get better over the rest of the season. However, the drop-off from last year is noticeable. Accuracy over the first two months of the season has only fallen once before, from 2009 to 2010, when it dropped by 0.16 percentage points. So far this season, accuracy has fallen by twice that amount: 0.32 percentage points. That’s a tiny change, on the order of one call per game, but that doesn’t make it any less real. We’ll have to wait and see how the rest of the season goes, but perhaps this year really could end up being different. Or, if it follows the pattern of the past decade and a half, accuracy will soon be in its way up.

Hi! It has been made to clear to me that my use of f = m * a as a narrative device herein was quite distracting, chiefly because in this context it’s incorrect. I apologize in advance to renowned baseball physicist Prof. Alan Nathan, should he ever read this; to all other physics enthusiasts who have remarked on the mistake; and to me, for embarrassing me. Ideally you will see past it and appreciate the meat and potatoes of the post for what they are: that there is possibly declining marginal utility to bat acceleration in a way we don’t seem to witness for bat speed. Thanks, and sorry again!

I can’t possibly begin to cover all the excellent work concerning Statcast’s new bat tracking data. Now as much as ever, it’s important to support your local Baseball Prospectuses, PitcherLists, Baseball Americas, FanGraphses and freelance Substack writers. We move quickly in these parts. There’s so much analysis to consume, all of it superb.

When confronted with this new data, one of my first instincts was to see which metrics from other areas of sabermetric analysis could be replicated within the bat tracking framework. Enter 90th-percentile exit velocity (90EV); it’s a powerful shorthand metric that distills a lot of information about the top end of a hitter’s exit velocity distribution into a single number. It’s not perfect, and other metrics outperform it, but it’s easy to see how it has become popular in contemporary analysis, especially in prospecting and scouting circles. Read the rest of this entry »

Statcast’s new public repository of bat tracking data has been out for a few weeks now. Like every number manipulator with a sense of curiosity and middling technical skills, I’ve been messing around with the data in my spare time, and also in my working time, because messing around with data is both my job and hobby.

Mostly, I’ve been reaching some conclusions that mirror what others have already shown, only with less technical sophistication on my part. This article by Sky Kalkman does a great job summing up the biggest conclusion: Pitch location and spray angle (pull/oppo) influence swing length so much that you probably shouldn’t quote raw swing length. But I thought I’d look for something slightly different, and I think I found something.

Here’s the high level conclusion of my search: When pitchers throw harder fastballs, hitters slow down their swings to compensate. It sounds counterintuitive. Shouldn’t hitters speed up their bats to try to get to the faster pitch? But I had a hunch that this wasn’t the case. If you listen to hitters describe their approach against flamethrowers, they focus on shortening up and putting the ball in play. “Shortening up” might sound like it describes swing length, but it also surely describes swing speed. A hitter who is just punching at the ball likely won’t swing as hard as one trying to launch one. If you’re prioritizing having your bat on plane with the ball as long as possible, you probably aren’t focusing as much on raw speed. Read the rest of this entry »

For years now, a simple message has been gaining traction in major league bullpens and pitching labs: Just throw it down the middle. As big league pitches have gotten speedier and bendier, the people who throw them have been increasingly advised to trust their stuff, stop nibbling around the edges, and attack the heart of the zone. Adam Berry wrote about the Rays adopting this approach in 2021. In 2022, Bryan Adams superfan Justin Choi looked into the numbers and noted, “In each season since 2015, when Statcast data became public, hitters have accumulated a negative run value against down-the-middle fastballs.” Last year, Stephanie Apstein documented the phenomenon in Baltimore, while Hannah Keyser and Zach Crizer did the same on a league-wide basis, describing the Rays model thusly:

Step 1: Develop unhittable stuff
Step 2: Let it rip down the middle
Step 3: Win

Just last week, Jeff Fletcher wrote that after trying and failing to get their pitchers to attack the zone more often, the Angels started putting their pitchers in the box to face their own arsenal, courtesy of a Trajekt pitching machine. “I knew my pitches were good,” said José Soriano through an interpreter, “but when I faced myself, I find out they’re really good. So I have more trust in my stuff now.” Pitches right down the middle are called meatballs for a reason, but if you’ve ever watched peak Max Scherzer demolish the heart of the other team’s lineup by simply pumping 97-mph fastballs across the heart of the plate, none of this comes as a galloping shock.

Still, I wondered whether I could find data to back up this shift in mindset. Are pitchers really attacking the zone more often? And are better pitching staffs (or staffs with better stuff) really attacking the middle of the plate more often? After all, the Angels rank 22nd in Stuff+ and 14th in PitchingBot Stuff, not to mention near the bottom in ERA, FIP, and xFIP. If they feel this good about their stuff, I’d imagine that every team does. Read the rest of this entry »

On the first knuckleball thrown at Coors Field in 16 years, Matt Waldron hit home plate umpire Bill Miller right in the nuts.

Nobody — not Waldron, not his catcher Kyle Higashioka, not Miller — appeared to know where the ball was going. Despite Higashioka frequently (and understandably) struggling to track the flight of the ball throughout the rest of the night, Waldron delivered a career-best performance, allowing just one run over six innings.

Perhaps the most surprising part of his performance was the setting. Since 2008, knuckleballers have dodged outings at Coors Field, which sits 5,200 feet above sea level. Conventional wisdom dictates that knuckleballs at altitude are a bad idea, as Cy Young-winning knuckleballer R.A. Dickey told Dave Krieger back in 2012. Read the rest of this entry »

The catcher pickoff is one of my favorite plays in baseball. It’s impressive almost every single time. Not only do backpicks call for remarkable agility and arm strength on the catcher’s part, but they also require a Holmesian ability to read the diamond. Are any runners getting cocky? Is the defense ready for a pickoff throw? Can the team risk a throwing error? The catcher needs to make those decisions rapidly, all while still performing his regular duties behind the plate. It’s not easy.

To that point, I like catcher pickoffs so much because they’re a nice reminder of the level of talent on display in professional baseball. In all my years of childhood rec league play, I never saw a catcher pull off a backpick. I don’t think I ever saw anyone try. The chances of success were too low, and the risk of a catastrophic error was too high. Catcher pickoffs are better left to the professionals. Yet this year, even the professionals are leaving them to someone else.

Here is a supercut of every catcher pickoff so far in the 2024 season. You might notice there aren’t many:

According to the records at Baseball Reference, there have been a total of seven catcher pickoffs this year. Just past the quarter mark of the season, that puts the league on pace for 26 backpicks in 2024. Last year, there were 49. In each of the previous two seasons, we saw 51. Over the last two decades, there has never been a full season with fewer than 41 catcher pickoffs. The numbers are, perhaps, even more dramatic if you remove cross-listed pickoff/caught stealing plays. There have only been five pure catcher pickoffs this year, putting the league on pace for just 19 by season’s end:

In 2023, the league leaders in catcher pickoffs were Keibert Ruiz (6), Patrick Bailey (4), and Francisco Alvarez (4). In 2022 and ’23 combined, the leaders were Ruiz (10), Jose Trevino (7), and Elias Díaz (6). While three of those five catchers have spent time on the IL this season, that group has still combined to catch 933.1 innings over 115 games. That’s nearly equivalent to a full season of work behind the dish. They have yet to pick off a single runner.

Here’s another fun way to think about how few catcher pickoffs we’ve seen in 2024. So far this year, there have been more successful steals of home plate (9) than successful catcher pickoffs (7). That’s partly because steals at home are up, but still, this simply doesn’t happen. Like, ever:

Entering the 2023 season, I thought we might see an uptick in backpicks. I was hardly alone. Willson Contreras, one of the greatest backpick artists of his generation, took note of the fact that the new disengagement rules did not limit catcher pickoff attempts. He said the Cardinals would have to be “smart” regarding “when our catchers backpick runners.” Manager Oliver Marmol sang a similar tune, praising his new catcher’s pickoff abilities. He said Contreras would “play a big part” in preventing runners from “stretching out” their primary and secondary leads. More catchers, such as Sean Murphy (“Yeah, that means we’ll throw more”), and managers, including Gabe Kapler (“We’re emphasizing backpicks”), made similar remarks.

A few months into the 2023 season, Kiri Oler looked at the data and concluded that “the numbers suggest catchers could be throwing behind runners significantly more in the name of keeping runners on edge.” She found that backpicks were a much more effective tool for discouraging stolen bases than traditional pitcher pickoff throws. Yet, if catchers were throwing behind runners any more often, they weren’t earning any more pickoffs. League-wide catcher pickoff totals were remarkably consistent from 2021 to ’23. Now, in the second season under the new disengagement rules, catcher pickoffs are disappearing.

This disappearing act is especially noteworthy considering average catcher pop times have gotten quicker in recent years (at least as of Ben Clemens’s piece on the stolen base rate from last month). What’s more, it’s not as if runners have been extra cautious on the bases this season; if anything, it’s the opposite. The stolen base attempt rate is slightly up, while the stolen base success rate is slightly down. Similarly, runners are making outs on base (OOB) and taking extra bases (XBT%) at similar rates to last season, according to Baseball Reference.

Most interestingly, the decline in catcher pickoffs has not resulted in fewer pickoffs overall. Ninety-nine runners have been picked off this season, putting the league on pace for 368 pickoffs by the time the calendar flips to October. That would be the highest total in a single season since 2012. Needless to say, this means pitcher pickoffs are on the rise. If current trends hold, pitchers alone will finish the season with more pickoffs (342) than pitchers and catchers combined in 2023 (341). Pitchers have not surpassed the 300-pickoff mark since 2012; they’re on pace to smash past that threshold in 2024.

On the one hand, it makes sense that pitchers would improve their pickoff throws with a full season of new disengagement rule experience under their belts. That said, it stands to reason that runners, too, would get better at making the most of the new rules. A recent article from The Athletic noted that “stolen-base percentages actually went down with each pickoff attempt last season, perhaps because baserunners were not yet attuned to exploiting the new rules. This season, runners are taking fuller advantage. According to STATS Perform, the stolen-base percentage after zero pickoff [attempts] is .77 percent. After one, it’s .81. After two, .87.”

Thus, while pitchers are getting better at picking off runners, the penalty of a failed pitcher pickoff attempt has increased. That being so, you might think catcher pickoffs would rise as a result. Runners’ taking more aggressive leads provides the opportunity, while the disengagement limit for pitchers provides the motive. The case is solid. Nevertheless, things certainly haven’t played out that way. What’s up with that?

Perhaps it isn’t really about the pickoffs, at least not directly. Instead, catchers might simply be placing greater emphasis on a different aspect of their game: framing. Teams knew pitch framing was important long before they had any metrics to quantify it. Now that we have the numbers, framing is more in vogue than ever. As a result, it’s likely teams are prioritizing framing over other strategies (i.e. pickoffs) in spring training, game plans, and the moment. I’ve already described how difficult a backpick can be. Now imagine trying to pull one off while simultaneously attempting to steal a strike. It’s all but impossible. If anything, I’d think backpicks have the opposite effect; pitches in the strike zone are probably more likely to be called balls on catcher pickoff attempts. Indeed, Noah Woodward found just that in a piece for his Substack, The Advance Scout. Woodward also suggests that the one-knee-down catching stance, known to help with pitch framing, makes it harder for catchers to pull off backpicks. As this catching setup rises in popularity, it makes sense that we would see fewer catcher pickoffs.

Good pitch framing isn’t nearly as exciting as a successful backpick, nor is an extra called strike nearly as beneficial as a pickoff. Ultimately, however, there’s more value to be gained from framing than backpicks over the course of the season. If a catcher can only do one or the other, it’s not hard to see why framing wins out. Even Willson Contreras seems to agree. Contreras recorded 28 pickoffs from 2016-22 with the Cubs. Throwing behind runners was his signature skill. Yet, ever since he signed with the Cardinals – who encouraged him to work on his framing and switch to a one-knee-down position – he has not picked off a single runner. The evidence may be circumstantial, but it’s still compelling.

If catchers are really letting pickoffs fall by the wayside in an effort to steal more strikes, it’s worth remembering that pitchers are picking up the slack. In other words, it might be a win-win. Since the disengagement limits were introduced, pitchers have been picking runners off with greater efficiency than before. That means pitcher pickoff attempts are less detrimental than we might have thought. Meanwhile, catcher pickoff throws still come with significant risk attached; as Kiri explained in her piece last year, the probability of an error is significantly higher on a catcher pickoff throw than a pitcher pickoff throw. Furthermore, while each pitcher disengagement marginally increases the chances of a successful steal, a throwing error all but guarantees the runner an extra base. Therefore, if pitchers can successfully pick runners off at a high enough rate, pitcher pickoff throws might be a safer option for the defense than backpick attempts. Hence the win on both fronts; catchers can be more efficient when they focus on framing over pickoffs, and pickoffs might still be more efficient coming from pitchers rather than catchers.

It will take a lot more data before we can say with any certainty that catchers are truly moving away from backpicks. After all, we’re only seven weeks into the season. Moreover, catcher pickoffs are always so low in number that the league-wide backpick pace could skyrocket quickly. But hey, if we always waited to write about trends until they were undeniable, we wouldn’t be doing a very good job telling the story of the season as it plays out. Pickoffs, both the catcher and pitcher variety, are something to keep a close eye on for the rest of the year. That shouldn’t be hard to do — pickoffs are pretty fun to watch.

All stats and rankings through May 16.