A few weeks ago, I presented some in-depth research on the size of the 2026 strike zone. The results were clear and unambiguous: The called strike zone is smaller this year than it was last year, and most of that shrinking is coming at the top of the zone. But saying that the strike zone is smaller is different than saying that the smaller zone is causing the overall major league walk rate to increase, and walks are up by a lot this season. Last year, batters walked in 8.4% of their plate appearances. This year, through May 8, they’ve walked in 9.5% of plate appearances. Still, walk rates move around all the time for reasons unrelated to the strike zone. That meant I had another question to answer: Are the walks coming from the smaller strike zone, or are they coming from something else?

First, I decided to look for which counts have had the greatest impact on the increase in walks. To do so, I used a technique called Markov chain decomposition. Think of each plate appearance as falling through a Plinko board. Every plate appearance starts at 0-0, and then it progresses in one of four ways: ball, strike, ball in play, or hit-by-pitch. Ball in play and hit-by-pitch results end the plate appearance, of course, but ball and strike outcomes on 0-0 feed into other buckets: 1-0 and 0-1 counts. In each of those counts, the same thing happens, with the next pitch resulting in either a ball, strike, ball in play, or hit-by-pitch. That keeps happening – with foul balls behaving like do-overs in two-strike counts – until you get to three strikes, four balls, a ball in play, or a hit-by-pitch. The reason that this is helpful is because you can start with small events – balls, strikes, balls in play – and build bigger outcomes, like walks and strikeouts. In that way, you can use per-pitch results to learn things about per-plate-appearance results.

That’s a Markov chain. To figure out how much each count’s changing results are contributing to the change in walk rate, we need to do a little decomposition, which means that another example is in order. Imagine a 2-2 count. Next, imagine that the only possible results are ball and strike. Further, imagine that there’s a two-thirds chance of a ball on 2-2, and a 50% chance of a ball on 3-2. You can work out the odds of a walk – one-in-three – and the odds of a strikeout – two-in-three – from those numbers. Now, let’s imagine a world where the walk rate balloons from 33% to 40%.

How can that happen? One of two ways: batters reaching 3-2 more frequently, or batters walking more frequently when they reach 3-2 counts. If 2-2 pitches go from being balls two thirds of the time to being balls 80% of the time, the walk rate would hit 40% without anything at all changing in 3-2 counts. Likewise, if 3-2 pitches go from being balls half the time to being balls 60% of the time, the walk rate would hit 40% without anything at all changing in 2-2 counts. In both of those scenarios, the walk rate goes up by the same amount, but in each case, the change in walk rate can be directly attributed to changing behaviors in a given count. As the likelihood of each individual result in each count varies, a Markov chain can calculate how much that affects the overall results.

In real life, the decomposition is a bit more complex, because there are more intermediate states and more outcomes, and because the results in each count are all changing at once. But that’s really just a matter of more math; it doesn’t alter the core concept. That means that you can look at a change in walk rate between two years and break down which counts are contributing to it the most. I did just that. I took every pitch from the 2025 and 2026 seasons and used them to create Markov chains. Then I decomposed them by count to see what’s going on with more granularity:

There’s an easy story here. Walks aren’t increasing because hitters are recovering from disadvantageous counts more frequently. Walks are increasing because when hitters get ahead in the count, they’re turning that advantage into a walk more frequently. The biggest contributing count is 3-2, with 2-0 and 3-1 close behind. It’s interesting to see 0-0 in the mix, but I think it’s very notable that four of the five counts that are contributing most to the higher walk rate feature more balls than strikes. The only reason 3-0 isn’t on that list is because the count hits 3-0 fairly rarely; it can’t contribute much.

Digging into why results in each count are changing requires leaving our Markov chain behind. If you compare 3-2 counts from 2025 and 3-2 counts in 2026, balls are happening 1.4 percentage points more often. Strikes are happening about one percentage point less often (the reason these don’t match the per-plate appearance results is that foul balls lead to a redo). But that doesn’t tell us why we’re getting more balls. To learn more, we’ll have to start integrating pitch location and batter behavior.

I’d say we should start with zone rate, but we run into a problem right away: “Zone rate” doesn’t mean the same thing anymore. There’s a new strike zone in town. And even putting aside the fact that the zone is being called more tightly, the zones listed by Statcast on each pitch have changed. I did a quick test: I took all the batters who have appeared in both 2025 and 2026, and measured the change in the listed height of their strike zone in those two years. If you weight it by the number of pitches that they faced in 2025, the aggregate league-wide strike zone, as defined by ABS, is about three inches shorter than it was last year, with most of the decline coming at the top of the zone. Only three batters in all of baseball have taller strike zones in 2026 than in 2025.

Since zone rate is a moving target, we’ll have to measure pitch locations relative to one consistent zone. I chose to use the 2026 zone, but really, we could use either. The key here is that we have to make sure we’re comparing apples to apples, as it were. That’s because we need to distinguish between two effects: pitchers throwing to the same place but getting called balls where they used to get called strikes, and pitchers throwing to less central locations.

I broke up the strike zone into 14 regions. There are four “just inside the zone” regions, four “just outside the zone in one direction” regions, four “just outside the zone, on the corner” regions, and then the heart of the zone and far from the zone. Using a consistent zone, pitchers are throwing the ball outside the strike zone slightly more often in 3-2 counts this year:

For the record, “far outside” is defined here as far enough out of the regulation zone that a take will almost never lead to a called strike. I chose one inch as the cutoff for the size of my “just inside” and “just outside” zones, which worked fairly well to differentiate between close calls and easy ones. In 2025, only 2.3% of taken pitches in the “far outside” zone were called strikes. In 2026, only 0.8% of them have been called strikes, out of a sample of more than 3,000 pitches.

Not every one of those “far outside” pitches gets taken, of course. Here are swing rates in each region on 3-2 pitches in 2025 and 2026:

You don’t have to worry too much about the changes in swing rates on corner pitches, because pitchers have only hit the corners a combined 19 times in our 2026 sample. It’s just not a very frequent area of attack on 3-2 – and really, we’re talking about hitting one-square-inch targets, so it’s not a very frequent area of attack generally.

I performed a more complete analysis by working out how many pitches batters took in each region in 2025 and 2026, accounting for both changing pitcher behavior (where they locate the ball) and batter behavior (how often they swing). In 2025, 23.4% of 3-2 pitches resulted in hitters taking a pitch that was located outside the consistent strike zone we defined. In 2026, 24.5% of pitches have resulted in hitters taking a pitch located outside the consistent strike zone. That adds to the rate of called balls, but not by 1.1 percentage points. That’s because not every pitch outside of the strike zone is called a ball, and vice versa:

That’s right: The areas at the fringes of the strike zone are being called differently. It’s not so much that the areas where strikes are most frequently called have moved (with the exception of the area just above the top of the zone, which as previously noted, is where the zone is shrinking). The difference is that balls outside the zone are being called strikes less frequently than before, while balls inside the zone are being called strikes more frequently than before.

Let’s set aside the top of the zone for a moment. On the other three edges, the transition from 2025’s all-umpire strike zone to the 2026 challenge/umpire hybrid zone has been, well, striking. Balls that are just barely in the strike zone on those three edges were called strikes 56.7% of the time in 2025; they’re being called strikes 76.7% of the time in 2026. Balls just off those three edges were called strikes 37% of the time in 2025; they’re being called strikes 13.5% of the time in 2026. In other words, the strike zone is getting less fuzzy. The shape is only changing at the top, but the number of incorrect calls in a given area is declining across the board.

How does that lead to an increase in walk rate? It’s a neat little mathematical relationship. The closer a pitch is to the center of the strike zone, the more likely a batter is to swing, particularly in two-strike counts. That means that an increase in accuracy across the board will add more balls than strikes, because there will be more takes, and thus more chances for the umpire to call a ball or strike, on pitches located outside of the strike zone.

Take the example we just used. Swing rates on the inside, outside, and bottom edges of the zone – but still in the zone – hover around 75%. Swing rates on pitches just off those edges are around 70%. That’s a small but non-negligible effect from a one-inch difference in location – and it’s bigger in counts that don’t feature two strikes, where swinging at a ball in the strike zone is optional. There’s an even bigger difference between pitches over the heart of the plate and pitches outside the strike zone. Centrally-located pitches are being called strikes 1.2 percentage points more frequently in 2026 than they were in 2025, while pitches far outside the zone are being called strikes 1.5 percentage points less frequently. But batters swing at 90% of the strikes and only 40% of the balls, so the net effect is that improving ball/strike accuracy in three-ball counts leads to more walks.

There are three effects driving the change in outcomes on 3-2 counts this year: pitcher/batter behavior, a change in the definition of the top of the strike zone, and increased call accuracy. I mathematically decomposed those into three parts using a simple test. First, I calculated what the walk rate would be if we took all of the actual pitches, swings, and takes from 2026, but used the called strike rates by zone from 2025 (based on the consistent strike zone definition detailed above) for taken pitches. This explains how much the walk rate would increase merely from changes in batter/pitcher behavior with a constant strike zone. A methodological note here: I only considered pitches thrown to batters who appeared in both 2025 and 2026 so that I could standardize the size of the strike zone for our analysis. That means that the overall numbers differ slightly from league-wide rates, though the divergence is minimal.

Next, I took the relevant pitches from 2025 and used the 2026 called strike rates for the top of the strike zone and the 2025 called strike rates for the rest. That gave me the increase in walk rate you’d expect if the only change was the shape of the top of the zone. Finally, I took the relevant pitches from 2025 and the 2026 called strike rates for everywhere except the top of the zone, where I kept the 2025 rates. That gave me the increase in walk rate you’d expect from increased ball/strike accuracy. I found that you can attribute 0.9% of the increased rate of 3-2 balls to changing batter/pitcher behavior, 0.1% to changes in calls at the top of the strike zone, and 0.4% to changes in correct call frequency in the rest of the strike zone.

That analysis explains the change in 3-2 results. To understand the whole picture, I just repeated the calculation for every count. That gave me values for how much changes in batter/pitcher behavior, changes at the top of the strike zone, and increased call accuracy changed the rate of balls and strikes in each count so far this year. Then, to complete the circle, I fed this data back into our Markov chain from above; I ran hypothetical Markov chains for each of the three effects independently, which let me calculate the change in overall walk rate attributable to each.

In the aggregate, you can split the change in walk rate into three parts. One is a change in pitcher/batter behavior. This covers changes in where pitchers locate, how frequently batters swing in each location, how frequently they make contact, and how frequently that contact is fair. Those changes have added 0.5 percentage points to the overall walk rate. Next, changes in the shape of the top of the strike zone have added 0.2 percentage points. Finally, an increase in the accuracy of calls has added 0.4 percentage points to the overall walk rate. That’s the headline finding of this study: Walks are increasing for three different reasons, all working in concert.

The next question I had was how much of that increased accuracy is due to challenges – not the overall challenge system, but specifically the pitches that players have challenged and in some cases overturned. There’s an easy way to test this: I just told my computer to take the original umpire calls instead of the final calls. The results are both interesting and intuitive: ABS challenges themselves have actually decreased the walk rate. That’s not surprising – more balls have been overturned into strikes than the reverse – but it sounds funny when you say it out loud. MLB switched to an ABS challenge system this year, and the direct effect of that system is slightly decreasing walk rates. Also, walk rates have increased by a striking amount, and more than half of that is attributable to changes in the way that balls and strikes are called, which appears to be an indirect effect of the ABS challenge system. Isn’t that weird?

Finally, I performed some analysis to ensure that my findings are robust. I varied the sizes of the slices I used to define the various zones in this analysis. Regardless of how large or small I made those slices, the contribution of pitcher and batter behavior to walk rate was stable at around 0.5 percentage points. But the relative contributions of the top of the zone and of increasing accuracy changed; the larger I defined the top of the zone to be, the more effect it had. For very large definitions of “top of zone,” the effect was roughly equal in magnitude to the effect of increased accuracy. In other words, it’s difficult to disentangle exactly how much of the walk rate increase can be attributed to increased accuracy of an existing zone and how much can be attributed to a change in the size of that zone, but both factors are important, and I think it’s quite likely that the accuracy component is of slightly greater import.

So 3,000 words in, what does it all mean? This year’s strikingly high walk rate isn’t just about pitchers and batters behaving differently, and it isn’t just about the size of the strike zone. It’s both, and it’s also about umpires making calls more accurately. I think that’s why the increase appears so dramatic; lots of things are all changing at once, and they all happen to be changing in the same direction.

This isn’t a stable equilibrium. Both pitchers and batters will continue to adjust to the new way that balls and strikes are being called. Batters are swinging less frequently this year, and pitchers will likely adjust to that by throwing in the strike zone more frequently. Now that the rewards to fishing off the edges have declined thanks to an increase in call accuracy, attacking the zone is being rewarded even further. And batters don’t have to take those potential changes lying down. If pitchers start throwing in the zone more frequently, batters will likely increase their aggression.

I’m not sure where walk rate is headed. But I do feel confident in saying that plenty of this year’s increase comes down to a change in the way balls and strikes are called. I also feel confident that a majority of that effect is about the increased accuracy of calls rather than a change in the size of the strike zone. Finally, challenges themselves aren’t contributing to this change; taken in isolation, they’ve actually decreased walk rate.

As is customary, I’ve included the dataset and Python code used to generate these results here. The study can also be expanded to previous years or run on different data; in fact, I couldn’t upload the 2025 data to GitHub for size reasons, so you’ll need to download that yourself. You can also replace those with your own similarly-formatted data if you’re interested in expanding the analysis.

Ben Lindbergh and Meg Rowley banter about Spencer Jones facing an overclocked Jacob Misiorowski in Jones’s MLB debut, the distance from the mound to home plate when Ryan Waldschmidt is batting, Gage Workman’s middle name, and Tarik Skubal’s loose lima bean, then discuss the surprising Patrick Bailey trade—including takes on Bailey’s bat and framing value in the ABS era, the leadership of Buster Posey and Tony Vitello, Cleveland doubling down on the Austin Hedges catching model, and the virtues of Matt “Tugboat” Wilkinson—plus thoughts on the bouncebacks of Bryce Harper and Michael Conforto, the Pirates’ rotation, iron man Matt Olson, a Craig Kimbrel meltdown, and the death of Bobby Cox.

Audio intro: Garrett Krohn, “Effectively Wild Theme”
Audio outro: Benny and a Million Shetland Ponies, “Effectively Wild Theme (Pedantic)”

Link to “POV” meme
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Link to fastest pitches of 2026
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Link to FG MLB WAR leaders
Link to longest consecutive games streaks
Link to Freeman vs. Olson WAR post-2022
Link to worst RP WPAs
Link to Kimbrel loss
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Link to Chavez’s Giants origin story
Link to “OTP” explainer
Link to Cox obit
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Link to Cox research 1
Link to Cox research 2
Link to Cox research 3
Link to manager longevity article
Link to data on ejection causes
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Link to 2026 manager ejection count
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Link to 2024 manager ejections count
Link to manager ejections data over time
Link to 2016 THT article on Cox DV
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The current standings between the two leagues are quite lopsided entering the second full week of May. Just three teams in the American League have winning records, while all five clubs in the NL Central are above .500. Then again, that division, which was not supposed to be all that strong entering the season, is doing a lot to prop up the National League as a whole; seven of the remaining 10 teams in the Senior Circuit have losing records.

Our power rankings use a modified Elo rating system. If you’re familiar with chess rankings or FiveThirtyEight’s defunct sports section, you’ll know that Elo is an elegant ranking format that measures teams’ relative strength and is very reactive to recent performance. To avoid overweighting recent results during the season, we weigh each team’s raw Elo rank using our coin flip playoff odds. (Specifically, we regress the playoff odds by 50% and weigh those against the raw Elo ranking, increasing in weight as the season progresses to a maximum of 25%.) The weighted Elo ranks are then displayed as “Power Score” in the tables below. As the best and worst teams sort themselves out between now and October, they’ll filter to the top and bottom of the rankings, while the exercise remains reactive to hot streaks and cold snaps. If you’re looking for a visual representation of the ups and downs of your team throughout the season, look no further than the brand new Power Rankings Board in the FanGraphs Lab.

First up are the full rankings, presented in a sortable table. Below that, I’ve grouped the teams into tiers with comments on a handful of clubs. You’ll notice that the official ordinal rankings don’t always match the tiers — there are times where I take editorial liberties when grouping teams together — but generally, the ordering is consistent. One thing to note: The playoff odds listed in the tables below are our standard Depth Charts odds, not the coin flip odds that are used in the ranking formula. Read the rest of this entry »

Read the rest of this entry »

In his first three seasons, Patrick Bailey carved a niche as one of the game’s top defensive catchers, dominating the Statcast defensive leaderboards and winning two Gold Gloves. The development of his offense has lagged, however, and with the Giants struggling to score runs and sporting one of the majors’ worst records, they’ve decide they can live without Bailey’s glovework. On Saturday, they traded the 27-year-old backstop to the Guardians for 23-year-old lefty pitching prospect Matt “Tugboat” Wilkinson and a Competitive Balance pick in the upcoming draft.

This is the second season in a row that president of baseball operations Buster Posey has shaken up San Francisco’s roster with an early-season trade; last year, it was the mid-June acquisition of slugger Rafael Devers in a blockbuster with Boston. You don’t have to squint too hard to accept that both trades were aimed at upgrading moribund offenses, but when the Giants dealt for Devers, they were 11 games above .500 (41-30), one game behind the Dodgers in the NL West. They felt they’d landed the offensive cornerstone that had eluded them after unsuccessful pursuits of Aaron Judge and Shohei Ohtani, a player who could help them return to the postseason for the first time since 2021. This time around, they entered the day of the trade 15-23, last in the division, and the move appears far more tilted toward the future, as Wilkinson has just gotten his feet wet in Double-A and the draft pick won’t make an immediate impact.

If this trade had occurred just prior to the deadline (August 3 this year), it might have been characterized as a white flag, part of a larger selloff. To these eyes, it’s a shakeup that at worst smacks of panic and at best places a lot of faith that Posey — a likely Hall of Fame catcher who has yet to show similar prowess as an executive — has found a diamond or two in the rough with his two recent catching acquisitions: Jesus Rodriguez, who came from the Yankees in last year’s Camilo Doval trade, and Daniel Susac, who was flipped by the Twins in December after being plucked from the A’s as a Rule 5 pick. Both are 24 years old and have fewer than 10 games of major league experience, with Susac, who turns 25 on May 14, currently on a rehab assignment after being sidelined by neuritis in his right elbow. Eric Haase, a 33-year-old backstop who hit his way out of a starting job in Detroit in 2023, started in Saturday’s 13-3 drubbing by the Pirates — San Francisco’s ninth loss in 11 games — while Rodriguez started Sunday’s 7-6 win, which lifted the team’s record to 16-24, still third worst in the NL. Read the rest of this entry »

Kai-Wei Teng had a limited repertoire when he signed with the Minnesota Twins out of Taiwan in 2017. The right-hander from Taichung possessed just a fastball and a curveball. A lot has changed since that time. Now 27 years old and pitching for the Houston Astros, Teng attacks hitters with a five-pitch mix that includes a sweeper that is not only hard to hit, it is no fun to be on the receiving end of in catch-play.

“It’s insanely good,” Spencer Arrighetti told me last weekend at Fenway Park. “I throw a sweeper. Lance [McCullers] throws a sweeper. We have a couple of other guys who toy around with it. But Teng’s is incredible. Truly. I played catch with him, and it looks like a fastball for 48 feet, then takes a 90-degree left turn. Not all sweepers are created equal. Some of them are a little loopier and bigger, but his is 85 mph. I mean, it’s gross. It really is a great pitch.”

The numbers back that up. Teng has relied on his most-used offering 36.3% of the time this season to the tune of a .118 BAA, a .118 SLG, and a 27.9% whiff rate. His other numbers are impressive, as well. Over 14 appearances, Teng has a 2.35 ERA, a 3.83 FIP, and a 24.7% strikeout rate over 23 innings.

I asked Teng for the story behind his best weapon. Read the rest of this entry »

One of my biggest regrets in the years I’ve been covering baseball is that I never got John Sterling’s list. You see, in addition to our mutual love of baseball, Sterling shared my appreciation for film noir. I don’t remember how it came up, but I learned of Sterling’s noir kick in the summer of 2023, when Yankees beat writer Chris Kirschner, of The Athletic, suggested I talk to the longtime Yankees radio broadcaster about it. I had never met Sterling before, but the next day in the Yankee Stadium press box dining room, I introduced myself. He was so excited to know that this 27-year-old kid also loved noir, and he immediately asked me what my favorites were. Right away, I rattled off In a Lonely Place, Out of the Past, and Double Indemnity, which looking back on it, must have made me seem like a noir novice, as if I said my three favorite Springsteen songs were “Born to Run,” “Born in the USA,” and “Dancing in the Dark.” But Sterling didn’t think anything of it. Or if he did, he didn’t show it. Instead, his face lit up, and in his baritone voice, he beamed about Bogart and Mitchum and MacMurray. We chatted for a few minutes before I asked him for his recommendations. He had to get back to the booth — it was almost game time — but he told me to come find him next homestand and he’d make a list for me. Unfortunately, I didn’t see him for another month or so, and when I did, I didn’t ask him for the list. We didn’t really know each other, and I didn’t want to bother him with something so trivial. He retired early the next season.

Growing up a Yankees fan from the Hudson Valley, I listened to Sterling for most of my life. His voice is woven into the fabric of my baseball fandom. It’s not a stretch to say that all those years spent listening to him on the radio contributed to my becoming a baseball writer. And yet, when I saw the news that Sterling had died on Monday at age 87, the first thing I thought about was the brief time we spent talking about film noir in front of the press box coffee machine that summer day in 2023. I never got the list, but I did get a wonderful memory. I’ll cherish it forever.

There’s no natural transition to the mailbag from there, so let’s just get to it. This week, we’ll be answering your questions about Austin Hedges’ unexpected hot start at the plate, the most efficient pitchers on a per-pitch basis, teams that register a .500 OBP in a game, and the largest percentage of career stolen bases coming in the shortest span of time. But first, I’d like to remind you that 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 an upcoming mailbag, send me an email at mailbag@fangraphs.com. Read the rest of this entry »

Imagine a video game designed around failure. One where winning isn’t defined as completing a set of objectives, but rather as finding the most creative, painful, and improbable ways to avoid completing the task at hand. I haven’t heard of such a game, but I’m convinced that it must exist, because the Reds are speedrunning it before our very eyes.

Entering May, Cincinnati was 20-11 and in sole possession of first place in the NL Central. To that point, they hadn’t been more than a game out of the division since April 3. One week later, the Reds are now 20-18, six games back, and in sole possession of last place in the division. Now, measuring strictly on length of losing streak, Cincinnati’s skid isn’t nearly as notable as the 12-gamer put up by the Mets or the 10-gamer that contributed to the dismissal of Phillies manager Rob Thomson. But by several other measures, the last week of Reds baseball has been an even more profound and excruciating experience of failure.

The Reds’ true talent as a team is still a bit of an enigma at this point in the season. They haven’t hit well — their team wOBA sits at .311, which ranks all the way down at 23rd in the majors, but a BABIP of .262 and an xwOBA of .332 suggest some misfortune at the plate. On the other side of the ball, their 4.61 team ERA is in the bottom third of the league, their 5.16 xERA ranks last in the majors, and their 4.80 FIP doesn’t rate much better. With those numbers in mind, it should come as no surprise that Cincinnati’s win total as estimated by BaseRuns sits around 16, a full four wins fewer than their actual mark. Read the rest of this entry »

With Thursday’s 6-2 win over the Mets, the Rockies snapped a six-game losing streak and lifted their record to 15-23, momentarily escaping the distinction of owning at least a share of the National League’s worst record, which is currently shared by those Mets and the Giants (14-23). If they are again one of the majors’ worst teams, the Rox are at least not on pace to approach last year’s 119 losses, nor are they entirely devoid of bright spots, including catcher Hunter Goodman, starter Tomoyuki Sugano, and relievers Chase Dollander and Antonio Senzatela. But by far their brightest spot lately has been the play of Mickey Moniak. Now in his second season with the team, Moniak leads the league in slugging percentage (.700), ranks second in wRC+ (176), and is third in home runs (11) despite barely having enough plate appearances to qualify for the batting title.

Alas, the 18-game hitting streak Moniak rode into Thursday came to an end in that victory, as he went 0-for-3 with a strikeout and a walk. He’d barely kept the streak alive on Wednesday night, going hitless in his first four plate appearances. He got under a pair of hard-hit balls against Mets starter Freddy Peralta, producing a popup to shortstop and a fly out to center field, both routine, and struck out twice, once against a high Peralta fastball and once against a low-and-away Brooks Raley sweeper. By the time he came to the plate for the fifth time, the Rockies were down 10-4 with one out in the ninth. Moniak ripped a hot smash 106.7 mph just to the left of pitcher Sean Manaea and past the outstretched glove of second baseman Marcus Semien as he dove to his right.

During Thursday’s game, Moniak’s contact wasn’t nearly as solid, though he almost kept the streak alive with a soft liner. The ball’s 64.3-mph exit velocity and 21-degree launch angle made it the kind of flare that actually lands for a hit more often than not, with just enough oomph to get over the infield dirt; the expected batting average on such balls is .550, but Semien did a fine job chasing that one down. Read the rest of this entry »

The Marlins have accumulated the fifth-most WAR of any team from their catchers this year. Their backstops have a collective 133 wRC+ at the position, third highest in baseball. This has been one of the team’s biggest strengths to start this season, so it was a bit of a surprise to see Miami make a pretty significant change at the position earlier this week. On Monday, the Marlins optioned Agustín Ramírez to Triple-A, calling up top catching prospect Joe Mack to take his place on the big league roster. The reason why they felt comfortable making this swap has been the standout play of Liam Hicks, the much less-heralded catcher also in his second big league season.

As Miami’s top overall prospect a year ago, Ramírez spent nearly the entire season in the majors. He put up a .231/.287/.413 slash line (91 wRC+) in 136 games as a rookie. Despite the nearly league-average batting line, he accumulated exactly 0.0 WAR because of some pretty atrocious defensive numbers. Per Statcast, he had the second-lowest Fielding Run Value of any catcher with at least 500 innings at the position. He was actually a slightly above-average pitch framer, but his throwing and blocking grades were the worst in baseball.

Through a month of play this year, Ramírez’s bat hasn’t really taken a step forward; his 86 wRC+ is a hair below what he accomplished last season, though the shape of his production looks a little different. His walk rate is nearly four points higher than it was in 2025, but his power output has cratered thanks to a six-point drop in barrel rate. The defense hasn’t improved either, and so the Marlins sent him back to Triple-A to work on his skills behind the plate. Here’s how manager Clayton McCullough put it on Monday:

“It got to the point where it is performance and felt like, especially on the defensive side of things, that while he put in a lot of good work this offseason and had seen some glimpse of things getting better, that part of his game needs to continue to improve to be able to catch up here for us.”

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