On last Monday’s episode of the Rates and Barrels podcast, Derek VanRiper raised a curious contradiction. “[Riley Greene is] first percentile in squared-up percentage, but 97th percentile in barrel rate, which — I’m sure there’s an explanation, I don’t know what it is just yet.” In response, Eno Sarris asked, “How can he barrel it without squaring it up?” It was a great question. In colloquial use, a squared-up ball is synonymous with a barreled ball. So what’s going on here, exactly?

The first thing to know: A squared-up ball is not necessarily a well-hit ball, as Davy Andrews highlighted when these stats were first made public last June. To understand why, one must first become acquainted with the Statcast definition of squared up. The MLB glossary entry for squared-up rate defines it thusly: “A swing’s squared-up rate tells us how much of the highest possible exit velocity available (based on the physics related to the swing speed and pitch speed) a batter was able to obtain – it is, at its simplest, how much exit velocity did you get as a share of how much exit velocity was possible based on your swing speed and the speed of the pitch.” If a hitter generates 80% of their possible exit velocity on a given swing and the ball is put in play, the batted ball is considered squared up.

We might quibble over the simplicity of that definition. In any case, as Davy showed, squared-up balls can be hit at super low speeds — if all it means is that a hitter channelled 80% of the potential exit velocity, then 80% of a half-swing is not very much exit velocity.

It’s also possible to do damage without making frequent flush contact; Greene shows us how. As Ben Clemens wrote just a couple of weeks ago, Greene is posting yet another excellent offensive campaign despite one of the higher strikeout rates among qualified hitters. He’s doing it unconventionally, swinging a ton in early counts to maximize damage. He’s also unconventional in another sense: He barrels the ball a ton while hardly ever squaring it up.

Part of the explanation for how this works is tied to the nature of swinging hard. When the bat speed statistics first dropped, it immediately became clear that there is a strong negative relationship between bat speed and the ability to square the ball up, at least by the Statcast definition. Click over to the bat tracking leaderboard, and the first thing you’ll see is this image, which shows the negative correlation between these two variables:

That’s no surprise. By the Statcast definition of a squared-up ball, slow swingers will always come out on top, because swinging slower allows for greater barrel accuracy. But it’s not all bad news for hard swingers. They also tend to produce the most valuable type of batted ball: a barrel.

Naturally, bat speed is correlated — positively — with barrel rate. A barrel, by the Statcast definition, is any type of batted ball where the expected batting average is at least .500 and the expected slugging percentage is at least 1.500. Barrels tend to be clustered in a pretty narrow exit velocity/launch angle range, somewhere north of 100 mph in terms of exit velocity and between 15 and 40 degrees or so of launch angle:

As the scatterplot below shows, the relationship between bat speed and barrel rate is extremely tight:

Greene’s average bat speed — 75.2 mph — is in the 91st percentile, so on some level, a high barrel rate and a low squared-up rate is to be expected. Even so, the spread between these two metrics is striking. His barrel rate is higher than his squared-up rate! Only one other hitter has a lower squared-up-minus-barrel rate — Aaron Judge. And that gives a hint into how, exactly, Greene is pulling this off.

Judge racks up an obscene number of barrels. Already, he’s mashed 60 this year, good for a 25.9% barrel rate. Like Greene, his squared-up rate is low — not as low, but comfortably a standard deviation below the mean. But also like Greene, Judge is amazing at converting his squared-up balls into barrels.

Nobody comes particularly close to Judge in this metric. Nearly 40% of his squared-up balls are converted into barrels, by far the highest rate in the league. (The league average is 13.6%.) As you might have guessed, Greene also excels here, ranking fifth among all hitters with at least 150 plate appearances:

So that’s the first part of this equation. Greene might not square the ball up that often, but when he does, it’s frequently crushed. The other part of the equation? Greene hits a ton of foul balls.

Greene’s 315 foul balls rank fifth among all hitters. When Greene makes contact with the ball, it goes foul 56% of the time. That mark ranks 11th out of all hitters with at least 150 plate appearances; besides Cal Raleigh, nobody else in Greene’s squared-up-to-barrel cohort fouls off nearly as many balls:

All of those foul balls — in addition to his seventh percentile whiff rate — contribute to the squared-up percentage denominator, sinking Greene’s squared-up rate to the very bottom of qualified hitters. Importantly, foul balls are not part of the barrel rate denominator. The barrel rate that shows up on the Savant player page popsicles is a measure of barrels per batted ball event. A bunch of foul balls do nothing to affect a hitter’s barrel rate, but they’ll go a long way toward tanking a squared-up rate.

It isn’t necessarily intuitive to think that a hitter could be so good at barreling the ball and so bad at squaring it up. But breaking it down in this fashion, I think it starts to clarify this ostensible conundrum. Barrels are hard to come by. Even Judge, the barrel GOAT, hits one just over a quarter of the time he puts a ball in play. To be a barrel king like Judge or Greene, you don’t need to crush that many baseballs, at least on an absolute basis. But you better make sure that when the ball is in play, it gets smushed.

More than anything, I think these two data points paint a compelling picture of the modern hitter. Greene, perhaps more than any other hitter, goes for broke, almost like the anti-Luis Arraez. His swing tilt is the steepest in the sport. He mishits a bunch of pitches. He whiffs a ton. But when he connects, he does damage. And even though those damage events are relatively infrequent, they’re valuable enough to make him one of the better hitters in baseball.

Below is an analysis of the prospects in the farm system of the Washington Nationals. Scouting reports were compiled with information provided by industry sources as well as my own observations. This is the fifth year we’re delineating between two anticipated relief roles, the abbreviations for which you’ll see in the “position” column below: MIRP for multi-inning relief pitchers, and SIRP for single-inning relief pitchers. The ETAs listed generally correspond to the year a player has to be added to the 40-man roster to avoid being made eligible for the Rule 5 draft. Manual adjustments are made where they seem appropriate, but we use that as a rule of thumb.

A quick overview of what FV (Future Value) means can be found here. A much deeper overview can be found here.

All of the ranked prospects below also appear on The Board, a resource the site offers featuring sortable scouting information for every organization. It has more details (and updated TrackMan data from various sources) than this article and integrates every team’s list so readers can compare prospects across farm systems. It can be found here. Read the rest of this entry »

Since 2021, Ke’Bryan Hayes is the leader in OAA among all infielders. As one of the best defenders in the sport, his floor is very high. Even with his career 87 wRC+, he has still been worth about 3 WAR per 162 games. If he could be a consistently average offensive player, he’d be one of the most valuable players at his position. This is a story we all know. With his name swirling in trade rumors, you have to imagine other teams are thinking about the possibility more so now than in the past. His issues stem from his suboptimal swing path, and if he’s traded, that will be what his new hitting coach tries to fix.

In the last calendar year (459 plate appearances), Hayes has a 60 wRC+. That is bad! But despite those struggles, it’s not like he is completely lacking offensive ability. His bat speed is only a little below average. His strikeout and whiff rates are better than league average over the past three seasons. He hits the ball hard more often than not, and he chases at about an average rate. Those are all things you could work with if you’re trying to manufacture a league average hitter. But if you’re doing all this and your path is rarely working in an ideal direction, you’ll always have limitations on what you do when you actually make contact. Read the rest of this entry »

A piece that ran here at FanGraphs just over a week ago elicited a good suggestion. Commenting on A Conversation With Max Scherzer on the Importance of Conviction, reader muenstertruck wrote the following:

“If you’re taking follow up questions, I’d like to hear how he differentiates intention and conviction from physical effort. How difficult is it to mentally commit to the pitch but only give it 90% so you keep some gas in the tank? Is it even possible to do so?”

Fortuitously, an opportunity to circle back with the future Hall of Famer came just a few days later when the Blue Jays visited Fenway Park for a weekend series. As expected — Scherzer likes talking ball — he was amenable to addressing said followup.

“Effort level and conviction are different,” Scherzer answered. “You can throw a pitch at 100% effort and still be mentally indecisive about it. You can also put out less than 100% effort and be mentally convicted in what you’re doing. Can things go hand-in-hand? Yes, but it’s not ‘more effort means more conviction.’ You can just be more mentally convicted.”

Scherzer had opined in our earlier conversation that you’re more likely to miss your spot when not fully convicted. What about throwing with full conviction at a 90% effort level? Does that make it easier to pinpoint your command? Read the rest of this entry »

Hello FanGraphs Members and readers. I hope all of you here in the U.S. are enjoying your holiday weekend. I’ve spent much of this week on vacation, so I didn’t get to watch as many games as I usually do. Still, I followed some of the action from afar, enough to see Clayton Kershaw record his 3,000th strikeout, the Yankees fall out of first place, and the All-Star Game’s starters be named.

This week’s mailbag is a bit more evergreen than our previous ones, when we’ve answered your questions about the Rafael Devers trade and the impact of his contract, Jacob Misiorowski and perceived velocity, and the weirdness of the Twins. Instead, today we’ll discuss how we watch baseball, players of the past who could still mash in the modern game, and so much more.

Before we get to all that, I’d like to remind all of you that while anyone can submit a question, this mailbag is exclusive to FanGraphs Members. If you aren’t yet a Member and would like to keep reading, you can sign up for a Membership here. It’s the best way to both experience the site and support our staff, and it comes with a bunch of other great benefits. Also, if you’d like to ask a question for next week’s mailbag, send me an email at mailbag@fangraphs.com. Read the rest of this entry »

We’ve now passed the mathematical halfway point of the 2025 season, which serves as a good time to check in on the ZiPS projected standings and analyze the ways in which reality has torn the preseason prognostications to shreds. While our depth charts utilize the ZiPS projections in the daily standings, this full ZiPS run utilizes the most robust methodology that I can assemble without pulling out what’s left of my increasingly dwindling supply of hair.

The ZiPS projected standings are the product of a million seasonal simulations. In order to get a better estimate of the upside and downside of the team, ZiPS takes an important additional step in simulating the roster itself before it ever considers a single game on the schedule. For example, in most of the New York Yankees’ simulations, Aaron Judge continues destroying pitchers on his merry way to what ZiPS projects will be an 11-WAR season, playing somewhere between 80% and 95% of the remaining games. Sometimes he regresses less from his current 13-WAR pace; other times, he drops off the pace a little bit more. Sometimes he’s dinged up a bit and misses time, and once in a while, he misses the rest of the season due to a serious injury. After an injury simulation, ZiPS fills in the depth charts in each sim based on who is available. When Judge is injured, the Yankees roster strength is typically made with more Jasson Domínguez, sometimes more Everson Pereira or Bryan De La Cruz, maybe some Spencer Jones, or as in simulation no. 111,535, a whole lot of Brennen Davis and Duke Ellis somehow. There’s a lot of PC power (I made an upgrade in May!) and a distressing amount of linear algebra involved.

Once ZiPS has a simulated distribution of a team’s roster strength, it then simulates the results of the rest of the season a million times. (Here I’ll note that a million simulations was not enough to get the Rockies into the playoffs.)

Below are the updated ZiPS projected standings through the games played on July 2. We’ll start our look with the AL East:

The Yankees offense slowed down considerably in June, which if you believe parts of Reddit, is somehow due to too much analytics. The more likely cause is that the Yankees are extremely reliant on Judge playing like a demigod, and when he has an ordinary month — a 157 wRC+ qualifies by his standards — the lineup has trouble absorbing what were down stretches for other key parts of the offense. ZiPS still sees the Yankees as the AL East team with the fewest potential problems over the next three months, even if it doesn’t think that Max Fried and Carlos Rodón will keep up their blistering pace.

The Blue Jays’ improvements this year should serve as a reminder (though they probably won’t), that people are too wedded to recent terrible/great performances. Coming off a 74-88 season in 2024, the Jays didn’t do a whole lot to really change the nature of their team, and the biggest thing they did do — signing Anthony Santander — hasn’t worked out yet. Sometimes gravity takes care of things!

The Rays have done their usual excellent patchwork job, but ZiPS isn’t really sold on the lineup maintaining wRC+ of 109 over the rest of the season. The computer is optimistic about Boston’s pitching staff, but the divisional math is getting difficult, and this is a team that didn’t really aggressively chase the playoffs when similarly situated in the race the last few years. ZiPS still thinks the O’s are a good team, albeit one with serious rotation issues, but they’ve banked so many losses that it’s getting hard to say that their current long shot odds are enough to keep 2025 a going concern.

Turning to the AL Central:

The Tigers have pretty much ended this race, and with an excellent rotation headed by the best pitcher in baseball right now, Tarik Skubal, this is an extremely dangerous playoff team. Detroit’s projected final win total has increased more than any other team in the baseball, jumping from 81 wins to 93.

ZiPS still sees the Guardians and Twins as legitimate playoff contenders, though it doesn’t have a great deal of enthusiasm for their rosters. I don’t expect either team to be particularly aggressive at the trade deadline.

Jac Caglianone has struggled in the majors so far, and while I fully expect him to overcome his growing pains, it also means that he hasn’t done much to resuscitate an abysmal offense. Kansas City’s pitching has been excellent, but it’s simply not enough. The White Sox are projected to finish with a 12-win improvement compared to 2024! That’s… something, I guess. Somehow, the pitching has been approximately league average, and if they can actually finish the season that way, maybe pitching coach Ethan Katz deserves the Cy Young award.

Looking to the AL West:

The Astros’ penchant for middling starts showed itself again this year, but as has been the case in the past, no other AL West team took the opportunity to build up a big cushion in the division. A seven-game lead at this point of the season isn’t an insurmountable one, but most teams with that kind of lead end up finishing with it. That’s especially the case when the team holding the comfortable lead is also likely the “true” best team in the division. The Astros are no juggernaut, but they can ride Hunter Brown and Framber Valdez, and the offense has been better than it had any right to be given the de facto loss of Yordan Alvarez and the de jure one of Kyle Tucker.

The Mariners have been surprising in that their offense has been a lot better than their pitching, and while ZiPS sees that flipping to a degree, they have enough holes that they still look like a .530-.540 team; that won’t be enough in most situations unless the Astros collapse. ZiPS is projecting a lot more Jacob deGrom innings these days than it was in March, but the holes in the lineup and at the back end of the rotation and bullpen leave Texas projected as merely a second-tier Wild Card contender.

Despite a near .500 record, ZiPS is still bearish on the Los Angeles Angels. Elsewhere, ZiPS thought the A’s had a pitching problem, and that’s basically what has transpired; the team’s early contention was a mirage.

Shifting to the National League, staring with the East:

The Phillies have been tested by Aaron Nola’s poor start and subsequent injury, but this was always a compelling unit and they’ve carried on without serious trouble. They do need to score more runs to keep holding off the Mets, and Bryce Harper’s injury highlighted the fact that he, Kyle Schwarber, and Trea Turner have been holding up the lineup.

The Mets have cobbled together an impressive rotation seemingly from spare parts, and ZiPS is actually fairly confident they’ll be fine after a rather gloomy June. ZiPS sees the Mets as being as strong as the Phillies, but the Phillies get a projected edge by virtue of an easier schedule (ZiPS says .497 vs. .505 for the Mets) and the two-game “head start” on the second half.

ZiPS still thinks Atlanta is a very competent team, but even if you assume that there aren’t more nasty pitching injury surprises waiting and that there’s nothing fundamentally broken about Ozzie Albies or Michael Harris II, the team has a 39-46 record, and is at the point where they have to consider short-term retooling.

The computer thinks the Nationals are better than the Marlins, but are now too far behind to be a factor in the playoff race.

Moving to the NL Central:

ZiPS was a massive believer in the Cubs in the preseason, being head-over-transistors in love with the team’s offense and defense, and not absolutely hating the pitching staff. That’s about how the team has played, so the projections naturally haven’t changed too much. ZiPS also saw the Brewers as the biggest danger to the Cubs, and again, it hasn’t moved off that position.

St. Louis and Cincinnati are both above .500, but the computer still sees the Cards as too broadly mediocre and the Reds as having too many positions that have been chasms for either to be a divisional threat without some things going their way. Both are plausible Wild Card teams.

The projections are actually bullish on the Pirates scoring more runs in the second half, with much of the lineup underperforming their peripheral numbers, but it’s largely in the category of “too little, too late.”

Lastly, let’s look at the NL West:

ZiPS was always skeptical of the notion that the Dodgers ought to be projected for a crazy number of wins, with the preseason projections thinking that the biggest benefit to come from the team’s offseason was protecting itself from injury downside. I don’t always agree with my creation, but I did in this case. That’s sort of how things have played out; the injuries hit the pitching as hard as they usually have, but the high-end offensive talent has compensated, and team is on a 102-win pace. I’ll note that this ZiPS run was a late-night one, and does give a pretty big hit to Max Muncy’s playing time after the grisly injury he sustained in yesterday’s game. In reality, the Dodgers have a large enough lead that his exact timetable shouldn’t change the projections significantly.

The Padres have been solid and are a first-tier Wild Card candidate, but they’ve probably fallen too far behind to scare the Dodgers. It doesn’t help that they’ve gotten basically no offense out of left field and designated hitter this year. The Giants are hitting their projections after falling short the last few years, but they have a similar problem to the Padres and have gotten sub-.700 OPS performances at prime offensive positions (first base, right field, and DH).

The Diamondbacks have disappointed, in large part due to a number of serious injuries, and the team, seeing the writing on the wall, has been hinting about being short-term sellers this summer. If they aren’t, however, ZiPS still thinks that they’re good enough to end up with a Wild Card spot without anything ridiculous happening.

For their part, the Rockies can be content with the fact that they’re one of the 30 best teams in the majors.

It was ugly, it was labor-intensive, it was sobering — and probably humbling. Clayton Kershaw entered Wednesday night’s start in Los Angeles needing just three strikeouts to reach 3,000 for his career. Facing the White Sox, a team with the American League’s worst record (28-57) and the majors’ second-highest strikeout rate against lefties (26.6%), the 37-year-old southpaw repeatedly struggled to get from strike two to strike three, and only reached the milestone on his 100th and final pitch of the night. By the time he caught Vinny Capra looking at a slider on the outside edge of the plate, the Dodgers trailed 4-2, and Max Muncy had just departed with a serious knee injury while applying the tag on an attempted steal of third base. It took a textbook ninth-inning rally for the Dodgers to salvage a victory.

Here’s the big moment:

Read the rest of this entry »

Last week, I began a series of pieces about team win-loss totals as estimated by BaseRuns, first by taking a broad look at the methodology and its limitations, then by zooming in on the offenses that deviate most notably from their BaseRuns assessment in the run scoring department. Let’s wrap up with a look at the defenses that sit furthest from their runs allowed approximation.

In the offense edition, I used a game show format to evaluate whether the perspective offered by BaseRuns has a point, or if there’s something its methodology is overlooking. We’ll keep that framework going for the defenses as well. Here’s a reminder of how it works:

To determine whether or not BaseRuns knows what it’s talking about with respect to each team, imagine yourself sitting in the audience on a game show set. The person on your left is dressed as Little Bo Peep, while the person on your right has gone to great lengths to look like Beetlejuice. That or Michael Keaton is really hard up for money. On stage there are a series of doors, each labeled with a team name. Behind each door is a flashing neon sign that reads either “Skill Issue!” or “Built Different!” Both can be either complimentary or derogatory depending on whether BaseRuns is more or less optimistic about a team relative to its actual record. For teams that BaseRuns suggests are better than the numbers indicate, the skill issue identified is a good thing — a latent ability not yet apparent in the on-field results. But if BaseRuns thinks a team is worse than the numbers currently imply, then skill issue is used more colloquially to suggest a lack thereof. The teams that are built different buck the norms laid out by BaseRuns and find a way that BaseRuns doesn’t consider to either excel or struggle.

Read the rest of this entry »

Love ’em or hate ’em, the class of “expected” stats has utility when we’re talking about predicting the future. The data certainly inspire mixed feelings among fans, but they perform an important task of linking the things that Statcast and similar non-traditional metrics say to performance on the field. A hard-hit rate of X% or a launch angle of Y degrees doesn’t really mean anything by itself, without the context of what’s happens in baseball games.

I’ve been doing projections now for nearly half (!) my life, so outside of my normal curiosity, I have a vested interest in using this kind of information productively in projections. Like the Statcast estimates (preceded with an “x,” as in xBA, xSLG, etc.), ZiPS has its own version, very creatively using a “z” instead.

It’s important to remember these aren’t predictions in themselves. ZiPS certainly doesn’t just look at a pitcher’s zSO from the last year and say, “Cool, brah, we’ll just go with that.” But the data contextualize how events come to pass, and are more stable than the actual stats are for individual players. That allows the model to shade the projections in one direction or the other. Sometimes that’s extremely important, as in the case of home runs allowed for pitchers. Of the fielding-neutral stats, home runs are easily the most volatile, and home run estimators for pitchers are much more predictive of future home runs allowed than are actual home runs allowed are. Also, the longer a pitcher “underachieves” or “overachieves” in a specific stat, the more ZiPS believes in the actual performance rather than the expected one. More information on accuracy and construction can be found here. Read the rest of this entry »

Coming into 2025, you might not have expected Alejandro Kirk and Ernie Clement to play central roles on a playoff contender. Neither player was an above-average hitter last season; in fact, each hit for a 93 wRC+ while playing regularly for a team that won just 74 games. Yet the pair rank first and second in position player WAR on the Blue Jays, thanks not only to improved offense but exceptional glovework, with Kirk battling the Giants’ Patrick Bailey for the top spot in two catching metrics, and Clement ranking among the best third basemen while also posting strong metrics in limited duty at the three other infield positions. The pair have not only helped the Blue Jays to a 47-38 record and the top AL Wild Card position, but also the top ranking in my annual midseason defensive breakdown.

Kirk and Clement aren’t Toronto’s only defensive stalwarts. Second baseman Andrés Giménez and center fielder Myles Straw, a pair of light-hitting glove whizzes acquired from the Guardians in separate trades this past winter, have been strong at their respective positions, with the latter helping to cover for the absences of Daulton Varsho. A Gold Glove winner last year, Varsho missed the first month of this season recovering from right rotator cuff surgery, and returned to the injured list on June 1 due to a strained left hamstring. Even in limited duty, Straw, Varsho, and Giménez — who missed about four weeks due to a quad strain, with Clement filling in at second for most of that time — have all rated as three to five runs above average according to Statcast’s Fielding Runs Value (FRV), and five to eight above average according to Defensive Runs Saved (DRS). Clement has totaled 12 DRS and 10 FRV at the four infield spots; in 359.2 innings at third, he’s second in the majors in both DRS (7) and FRV (5).

This is the third year in a row I’ve taken a midseason dip into the alphabet soup of defensive metrics, including Defensive Runs Saved (DRS), Statcast’s Fielding Run Value (FRV), and our own catcher framing metric (hereafter abbreviated as FRM, as it is on our stat pages). One longtime standby, Ultimate Zone Rating (UZR), has been retired, which required me to adjust my methodology. Read the rest of this entry »