The fences moved in, and Michael Wacha felt the pinch. The right-hander allowed exactly twice as many home runs in 2026 as he did in the prior year, and the obvious place to look is the ballpark. Kansas City pulled the Kauffman Stadium fences in by enough to turn it from one of the toughest places to leave the yard into a roughly average home run environment. Or at least, that’s where I started when I set out to analyze Wacha’s 30 homers allowed, the third-highest mark in baseball and a career worst for the veteran pitcher.

I kept an eye on Wacha’s home run issue for two reasons. First, I was curious about how the new fences would play, and as a fly ball pitcher without strikeout stuff, Wacha was a great barometer. Second, I’ve done a lot of work on which pitches are most likely to get hit for home runs in the past few seasons, and Wacha generally finished high on those lists. But despite showing the characteristics of a pitcher who should get hit hard, he basically didn’t. Over 2024 and 2025 combined, no pitcher in baseball had a larger divergence between his expected home runs allowed, as calculated by PitchingBot, and his actual home runs allowed. Wacha’s pitches racked up 50.6 expected HR allowed during that span, according to my formulation of PitchingBot data; he allowed only 32, a gap of 18 homers. No one else had a gap of 15 or higher.

Through the end of June, there wasn’t much to pay attention to. But on July 4, Wacha got tagged for three homers at home against the Phillies, and from then on out, it was as though a switch had been flipped. From that day through the end of the season, he gave up 13 long balls at home, and another seven on the road. Was it Wacha? The stadium? Luck? I made a note to check when the playoffs were over. Today, I’d like to give you the results of that investigation, as well as revisit my old definitions of meatballs and expected home runs. Wacha’s glut of home runs allowed wasn’t simply a fluke, and the stadium wasn’t to blame for all of those added homers.

Let’s start with an overview of Kauffman stadium in 2026. In 2025, teams hit 151 homers at the K; this year, they hit 196 home runs there. That’s almost bang on what you’d expect from a physics-based model. Taking the same set of batted balls and overlaying both wall dimensions on them, the closer fences produced between 40 and 60 additional home runs in all but one of the seasons I tested. Home runs were down a hair across the majors, but mostly, the league had a similar environment for power and Kauffman simply played smaller. That’s exactly in line with my expectations. Score one for physics.

What did that mean for Royals pitchers? In plain English, they couldn’t rely on the park’s home run suppression on elevated contact anymore. I’ve been using PitchingBot data to calibrate expected home runs, what I’m calling xbotHR, to figure out which pitchers throw the most crushable offerings. That metric uses physical characteristics of each pitch as well as information about the count, but it ignores everything else. For two identical sliders in identical counts, my model would expect the same chance of a home run for Junior Caminero batting at Coors Field as for Chandler Simpson batting in the Grand Canyon.

The batter identity part of the equation mostly comes out in the wash. Across an entire season, pitchers face broadly equivalent opposition. That doesn’t mean that it’s OK to throw a meatball to Caminero, and indeed some pitchers struggle because they can’t avoid the big part of the plate against scary hitters, but you can mostly ignore that when you’re evaluating an entire season. However, stadium identity doesn’t work that way. Pitchers don’t experience broadly equivalent home run environments. Pitching at Kauffman before 2026 was like a security blanket that other teams’ pitchers didn’t receive.

Put another way, Royals pitchers allowed 20 fewer home runs than expected in 2024. They allowed 21 fewer home runs than expected in 2025. And in 2026, they allowed only three fewer home runs than expected. You can’t blindly attribute all of that to the stadium, but again, the effect size feels about right: If the park was producing 20 fewer visitor home runs than expected per year, it would be reasonable to expect 20ish fewer home-team homers than expected. Indeed, that happened; both home-team and away-team homers were almost exactly what the model expected in 2026.

If you’re keeping all of these numbers in your head, by now you’ve likely realized that Wacha’s home run suppression vastly outstripped what can be attributed to his home environment. He allowed 18 fewer home runs than my model expected across 2024 and 2025, with about 11 homers worth of the gap coming in home games. The math’s not that hard here; Wacha threw about 11% of the pitches that the Royals tossed in Kauffman across those two years. If the stadium suppressed home runs for each pitcher in equal proportion, he would have allowed four or five fewer home runs than my model’s expectation, not 11 fewer.

That’s not particularly weird, of course. Allowing a home run is partially a mark of bad process, but it’s largely a mark of bad luck, and not all of that bad luck washes out at the seasonal level. Sometimes the other guy just hits a good pitch out. Sometimes he swings through a pitch that another hitter would have tattooed. The wind doesn’t blow the same way every day; two pitchers might play in the same park but experience very different “park effects.” And not every pitcher allows a similar number of balls in play that could even become homers. One thing I’ve learned from parsing these numbers over the years is that by this formulation of xbotHR, you should expect a ton of noise even if there’s a real signal.

But in the same way that Wacha’s home run suppression was greater than could be explained by his home ballpark over the 2024 and ’25 seasons, the extra home runs he allowed in 2026 are far more numerous than can be explained by the new dimensions. In 2025, I had Wacha down for 14.2 xbotHR allowed at home, and he gave up six homers. This year, I had him down for 14.1 xbotHR allowed at home – and he allowed 17 homers, nearly triple the previous year’s total.

To make sense of this, I started thinking more granularly about how I was producing my xbotHR calculations. PitchingBot works by taking a pitch and assigning probabilities to a number of variables: the chance the batter swings, the chance he makes contact, the chance the contact is fair, and the chance that the contact lands in one of a number of buckets of contact quality. But it doesn’t use any actual contact data, so there’s a gap between what the pitchers tend to allow and what they actually allow.

But I don’t have to limit myself to that data. PitchingBot might make its predictions without knowing what happens, but I don’t have to. For example, let’s consider Wacha’s 2025 home games. My xbotHR model says that when pitches like Wacha’s were thrown, they tended to result in contact that you’d expect to produce roughly 14 homers in a neutral ballpark. But if you look at the actual batted balls he allowed, those combinations of angle and exit velocity projected for just under 10 homers. In other words, Wacha was throwing pitches that the model thought would get hit pretty hard, but batters weren’t producing those hard-hit balls as frequently as expected.

Next, the same contact leads to different expected results depending on where it’s hit. Smoked line drives are great everywhere; hard-hit fly balls can be all over the place in value depending on where the game is being played. This is the stadium effect we’ve already discussed at length.

Finally, there’s still plenty of unmodeled “residual” left. Batted-ball spin, for which we have no public data, can change carry considerably. We have overall park effects, but that doesn’t cover whether a gust of wind knocked down or propelled a particular ball, or whether one particular day’s weather made a park play notably different than its average. Home run robberies would show up here, although there aren’t enough of those per year to be a huge factor. There could be data errors, though none jumped out at me. There are interaction terms – moving in the fences at Kauffman didn’t make every type of batted ball better, so batted-ball distribution and park effect can impact each other in ways that aren’t modeled in the previous steps. In any case, there’s a lot of stuff that our model doesn’t capture. The hope is that all of that stuff is noise – in other words, that it doesn’t have a consistent direction. I have good news for that assertion; I modeled every pitcher in baseball in this method, and the residuals had essentially no year-over-year correlation (an r-value of 0.04, for the statistically inclined).

Here’s a graphical representation of my mental model of how to go from the model’s xbotHR output to actual home runs:

I used this component-wise breakdown to explain what’s changed for Wacha. Let’s take 2025 as an example. I mentioned above that he allowed 14.2 xbotHR. Looking at his actual contact allowed, however, he did meaningfully better. Wacha tossed up some offerings that looked exceedingly mashable to the models, but hitters couldn’t mash them. Based on batted-ball results alone, you’d expect Wacha’s pitches to yield 9.7 homers at a neutral park. Some of that is skill, some of that is luck, some of that is that my model doesn’t know who the batters are. Or, well, some of it could be that my model doesn’t know who the batters are, so I tested that hypothesis. In 2024 and 2025 combined, the batters that Wacha faced hit 3.09 homers per 100 plate appearances when facing non-Wacha pitchers (league average was around 3.05 for those years). In 2026, the batters he faced hit 3.04 homers per 100 plate appearances against everybody else (league average was around 3.03).

In those years, the park also helped by quite a bit. More specifically, using the ratio between expected home runs based on leaguewide batted-ball data and actual home runs hit at Kauffman Stadium, Wacha could expect 1.7 fewer homers allowed in 2025 home games based on where he pitched and the type of contact he surrendered. I also know that Wacha allowed six home runs at home in 2025, so that means I can fill in the residual by subtraction; he allowed two fewer home runs than his contact quality and home park would imply, for any of a number of reasons that don’t appear to repeat all that much from one year to the next. But at the end of the day, I feel pretty confident in saying this: PitchingBot thought that Wacha’s home pitches deserved to allow around 14 homers. Hitters made weaker-than-expected contact on those pitches; if you only looked at the batted balls he allowed, you’d expect around 10 homers in a neutral park. Kauffman’s generous dimensions knocked that expectation down to eight, and then he actually allowed only six. Let’s fill in those values on our flowchart:

OK, now it’s time for the 2026 version. PitchingBot gave Wacha a near-identical 14.1 xbotHR without looking at batted-ball results. But unlike 2025, Wacha didn’t suppress contact relative to what the model expected. If you only look at the batted balls, you’d expect 16.6 homers. He went from allowing less dangerous contact than our pitch-only model forecast to more dangerous contact than it forecast. That’s borne out by looking at the actual batted balls. Define a dangerous batted ball as one hit 95 mph or harder, and at a launch angle between 20 and 40 degrees. In 2025, 11.5% of the batted balls that opponents hit against Wacha at Kauffman fit those criteria (league average was 12.4% that year). In 2026, 14.3% of the batted balls that opponents hit against him at Kauffman fit that criteria (league average was 11.7%).

You can’t give Wacha all the blame for that. The gap between PitchingBot-expected contact and actual contact allowed is a noisy variable. Some pitchers definitely have a contact suppression skill beyond what PitchingBot measures. Some are definitely more prone to loud contact than the model would suggest. But there’s also a ton of noise in the number, as you’d expect given that it’s based on what the batters opposing a pitcher did in addition to the parts that he himself controlled. Some testing on my end suggests that 25% or so of “contact suppression value” is a repeatable pitcher skill, as a rough rule of thumb.

From 16.6 homers, we add in the 2026 park effect. In previous years, you would have expected the park to suppress a ton of homers – roughly three, based on how much elevated contact Wacha allowed this year. But the new, closer fences meant that the park effect was subdued, a mere -0.4 homers, as Kauffman played roughly neutral on the home run front this year. Add in the last residual term, and the whole line looks like so:

I just threw a lot of numbers at you, and this article is already pretty dense, so I won’t keep up the math barrage. The point I was trying to make isn’t the specific values; it’s that the biggest change in Wacha’s home run suppression was not his home park but the change in contact allowed relative to what you’d expect from the shape and location of his pitches.

There’s no reason to expect anyone to be as good at this skill as Wacha was in 2024 and 2025. For example, he wasn’t nearly that good at the skill in the previous years of his career, when his xbotHR and actual home runs allowed were roughly equal. So if you’re forecasting how many homers Wacha will allow next year, you probably shouldn’t ascribe some kind of outlier contact suppression value. And in fact, Steamer projects him for 28 homers allowed in 2027, and it projected him for 26 this year. Maybe I was wracking my brain for reasons Wacha was beating the odds when the real reason was just random variation and short-term swings that don’t stick in the long run; both my breakdown and Steamer’s projections sure seem to think that way, at least.

I’m not sure if this is as fascinating a result to you as it is to me. But I set out to figure out why Wacha went from suppressing homers at a massive clip to being basically average at that skill, and I actually found several things to point to that weren’t just that the fences moved. I’m pretty pleased with that, even if there’s still plenty of fudge factor in the model. I hope you enjoyed this too-deep dive into something that had been on my mind all year.

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One story ends, another begins. The Milwaukee Brewers have hoisted the 2026 World Series trophy and earned an offseason of rest, but for the ZiPS projection system, there is no winter respite. The 2027 season is (hopefully) just around the corner, and as has been the case every year going back to 2005, it’s time to start rolling out projections.

For those new to my projections, ZiPS is a computer projection system I initially developed in 2002–04. It was officially released to the public in 2005, after it had reached a level of non-craptitude I was content with. The origins of ZiPS are similar to Tom Tango’s Marcel the Monkey, coming out of discussions I had in the late 1990s with Chris Dial, one of my best friends (our first interaction involved Chris calling me an expletive!) and a fellow stat nerd. ZiPS quickly evolved from its original version as a reasonably simple projection system, and now it both does a lot more and uses a lot more data than I ever envisioned it would 20 years ago. At its core, however, it’s still engaged in two primary tasks: estimating what the baseline expectation for a player is at the moment I hit the button, and then estimating what that player might do in the future using large cohorts of relatively similar players.

So why is ZiPS named ZiPS? At the time, Voros McCracken’s theories on how pitching, defense, and balls in play interact were fairly new, and since I wanted to integrate some of his findings, I decided (with his blessing) that the name of my system should rhyme with DIPS (defense-independent pitching statistics). I didn’t like SIPS, so I went with the next letter in my last name. I originally named my work ZiPs as a nod to CHiPs, one of my favorite shows to watch as a kid, but I mis-typed ZiPs as ZiPS when I released the projections publicly, and since my now-colleague Jay Jaffe had already reported on ZiPS for his Futility Infielder blog, I chose to just go with it. I never expected that all of this would be useful to anyone but me; if I had, I would have named it in less bizarre fashion.

ZiPS uses multiyear statistics, with more recent seasons weighted more heavily; in the beginning, all the statistics received the same yearly weighting, but eventually, this became more varied based on additional research. And research is a big part of ZiPS. Every year, I run hundreds of studies on various aspects of the system to determine their predictive value and better calibrate the player baselines. The data now included in the system has grown considerably since 2002. Basic hit, velocity, and pitch data started playing a larger role beginning in 2013, while data derived from Statcast has been incorporated in recent years as I’ve gotten a handle on its predictive value and the impact of those numbers on existing models. I believe in cautious, conservative design, so data are only included once I have confidence in their improved accuracy, meaning there are always builds of ZiPS that are still a couple of years away. Additional internal ZiPS tools like zBABIP, zHR, zBB, and zSO are used to better establish baseline expectations for players; these stats work similarly to the various flavors of “x” stats, with the “z” standing for something I’d wager you’ve already guessed.

How does ZiPS project future production? First, using both recent playing data with adjustments for zStats, and other factors such as park, league, and quality of competition, ZiPS establishes a baseline estimate for every player being projected. To get an idea of where the player is going, the system compares that baseline to the baselines of all other players in its database, also calculated from the best data available for the player in the context of their time. The current ZiPS database consists of about 158,000 baselines for pitchers and about 191,000 for hitters. For hitters, outside of knowing the position played, this is offense only; how good a player is defensively doesn’t yield information on how a player will age at the plate.

Using a whole lot of stats, plus information on the shape of a player’s production and other characteristics, ZiPS then finds a large cohort that is most similar to the player. I use Mahalanobis distance extensively for this. A few years ago, Brandon G. Nguyen did a wonderful job broadly demonstrating my process while he was a computer science/math student at Texas A&M, though the variables used aren’t identical. It should serve as a reminder that ZiPS is the product of a lot of work and time, rather than a particularly high level of inspiration. The main advantages of Mahalanobis distance are that it’s not stymied by different scales of variables and it adequately deals with the correlation between the different numbers.

As an example, here are the current top 50 near-age comparables for possible National League MVP Pete Crow-Armstrong, a particularly difficult player to comp. The total cohort is much larger than this, but 50 ought to be enough to give you an idea:

With candidates in the hundreds of thousands, not the billions, you’re never blessed with perfect comps. From testing, I know that ZiPS works significantly better over the long haul when players like Crow-Armstrong are compared to similar players rather than the Luis Arraezs or Tyler Stephensons or Chandler Simpsons of the world. The exact mix the algorithm uses to assemble comps was determined by extensive testing, basically by having a computer running ZiPS 24/7 for about a year. The large group of similar players is then used to calculate an ensemble model on the fly for a player’s future career prospects, both good and bad.

One of the tenets of projections I follow is that no matter what the ZiPS projection says, that’s what the projection is. Even if inserting my opinion would improve a specific projection, I’m philosophically opposed to doing so. ZiPS is most useful when people know that it’s purely data-based, not some unknown mix of data and my opinion. Over the years, I like to think I’ve taken a clever approach to turning more things into data — for example, the system’s use of basic injury information — but some stuff just isn’t in the model. ZiPS doesn’t know if a pitcher wasn’t allowed to throw his slider coming back from injury, or if a left fielder suffered a family tragedy in July. Those sorts of things are outside a projection system’s purview, even though they obviously can affect on-field performance. ZiPS isn’t mathemagical, and anyone using a useful tool should know its limitations and apply their own judgment to the question at hand.

It’s also important to remember that the bottom-line projection is, in layman’s terms, only a midpoint. You shouldn’t expect every player to hit that midpoint; 10% of players are “supposed” to fail to meet their 10th-percentile projection, just like 10% of players are “supposed” to pass their 90th-percentile forecast. This point can create a surprising amount of confusion. ZiPS gave a .300 batting average projection to just one player in 2026: Luis Arraez. But that’s not the same thing as ZiPS thinking there would only be a single .300 hitter. On average, ZiPS thought there would be nine qualified hitters who would eclipse .300, not one. In the end, there were seven.

Another crucial thing to bear in mind is that the basic ZiPS projections are not playing-time predictions; by design, ZiPS has no idea who will actually play in the majors in 2027. The system only makes projections for how players would perform in full-time major league roles. Having ZiPS tell me how someone would hit as a full-time player in the big leagues is a far more interesting use of a projection system than if it were to tell me how that same player would perform as a part-time player or a minor leaguer. That’s why for the depth charts that go live in every team projection article, I use the FanGraphs Depth Charts to determine the playing time for individual players.

I haven’t made any major updates to the system this year, though I’m inching closer to a ZiPS-specific stuff model, which probably needs a year or two more of live data. I did, however, make the usual calibration adjustments and quality-of-life updates that make ZiPS simpler to run, while providing more ways to look at projection data.

Have any questions, suggestions, or concerns about ZiPS? I’ll try to reply to as many of your inquiries as I reasonably can in the comments below. Also, if the projections have been valuable to you now or in the past, I would urge you to consider becoming a FanGraphs Member, should you be in a position to do so. It’s with your continued and much appreciated support that I have been able to keep so much of this work available to the public for so many years. Improving and maintaining ZiPS is a time-intensive endeavor, and reader support allows me the flexibility to put an obscene number of hours into the system’s development. It’s hard to believe I’ve been working on ZiPS for nearly half my life now! Hopefully, the projections and the things they’re helped us learn about baseball have provided you with a return on your investment, or at least a small measure of entertainment, whether it’s from being delighted or enraged.

I’ll start rolling out the team breakdowns tomorrow, beginning with the Brewers.

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As awards season bores its way on to the baseball offseason calendar, we thought we’d take a moment to spotlight some guys who won’t get any of the love in those categories but had tremendous seasons nonetheless.

The following five players all found major success in 2026 by improving some specific part of their game, but their numbers didn’t jump off the page enough to make them an All-Star or a finalist for any major hardware. As such, we have a quintet of players who each finished the most recent campaign with less than 3.0 WAR, but were worth your attention all year, and stand to be even more enticing moving forward.

Dominic Canzone – Seattle Mariners

2026 stats: .264/.336/.484, 23 HR, 28 2B, 134 wRC+, 20.6 K%, 9.0 BB%, 2.8 WAR

Dominic Canzone, a left-handed swinger the Mariners acquired in their 2023 Paul Sewald trade, finally broke out of platoon jail this year. The bat-first outfielder spent time in Triple-A in both 2024 and 2025, becoming a full-time member of Seattle’s big league roster for the first time in ’26. As a result, he made 265 more plate appearances than he ever had in a major league season, a number reached because he consistently pounded the ball, but particularly against left-handed pitching.

In his previous attempts at sticking in Seattle — rather than riding the shuttle back-and-forth to Triple-A Tacoma — Canzone was hampered by a complete inability to hit same-handed arms. Two years ago was a literal example of that, as he went 0-for-13 in his limited looks against southpaws, striking out eight times. He got more chances in 2025, both because of Luke Raley’s injuries and Mitch Haniger’s release, and Canzone’s overall numbers made the Mariners front office look genius for flipping an aging reliever for him. Canzone hit .300 that season while cutting his strikeouts and finding a more regular line-drive stroke, but was held to just 268 plate appearances as Jorge Polanco, Mitch Garver, and Dylan Moore saw more reps against lefties. Of those 268 total plate appearances, just 68 came against left-handers, but Canzone mustered a 113 wRC+ in that abbreviated sample.

This past season was a different story, as the Mariners’ roster construction — plus more injuries to Raley and Victor Robles — forced Canzone into the lineup regardless of the opposing pitcher’s handedness. He stepped into the box 145 times versus a lefty and picked up where he left off the year before, improving his left-on-left wRC+ to 147 and drawing a walk in 15.2% of his lefty looks, also a notable jump from his 11.8% in 2025.

The granular improvements came against breaking stuff, and even more granularly, in the slugging department. By simply getting more opportunities to see left-handed pitching, Canzone seemed to grow more accustomed to the sweepers and curves that were vexing him, and the baseball gods also rewarded him. Though his 2025 slugging percentage against lefty breaking pitches was just .214, his xSLG was .368. Canzone truly couldn’t buy an extra-base hit against lefties in 2025, finishing the year with a whopping zero. In 2026, his slugging percentage trampolined up to .449, even though his xSLG dipped to .341. Sometimes it is better to be lucky than good, like when this lurching swing led to a ball finding some turf.

That video demonstrates something else that Canzone improved drastically, though. In 2025, that MacKenzie Gore two-strike slider would have almost certainly gotten a whiff out of Canzone, whose swing and miss percentage against left-handed breaking pitches fell from 43.9% to a much more palatable 33.0% in 2026. And if you hang ’em, Canzone — whose bat speed, barrel rate, hard-hit rate, and average exit velocity were all in the 75th percentile or better — will happily bang ’em.

Christian Scott – New York Mets

2026 stats: 23 starts, 110 innings, 3.85 ERA, 3.61 FIP, 28.3 K%, 9.9 BB%, 2.1 WAR

The biggest reason for Christian Scott’s a 2.1-win season over 110 innings is that his arm healed from a hybrid Tommy John and internal brace procedure that put him on the shelf for all of 2025. Scott was a much ballyhooed prospect ahead of his 2024 debut, but questions surrounded his health, mechanics, and college history as a reliever rather than a weekend starter. After beginning 2026 in the minors, things got off to a rocky start for Scott when he was called up to face the Twins on April 23, as the former Florida Gator recorded more walks (five) than outs (four). But in the 22 starts that followed, Scott was nasty, emerging as the Mets’ best starter not named Nolan McLean.

While the Mets kept Scott on an understandably short leash coming off a major surgery — he did not throw 100 pitches in any game, topping out at 98 two different times — he made the most of his four- and five-inning outings. The standout skill for Scott became his ability to strike fools out, which he always showed in the minor leagues, but struggled with during his nine pre-surgery starts in the majors in 2024. When Scott hit the operating table, he had a 19.8% strikeout rate in his first 47 1/3 innings in The Show. New and improved in 2026, Scott finished with a sparkling strikeout rate of 28.3%.

Every pitch in Scott’s bag generated more whiffs upon his return, save for a splitter that was largely moved to the dustbin. His four-seamer not only missed bats more frequently — in the zone, specifically, Scott’s heater went from a 19.3% whiff rate in 2024 to 24.1% in ’26 — but it also bunny-hopped in velocity. When he needs to now, Scott can reach back and find 98 mph, like he did here to beat Aaron Judge at the top rail.

However, the most exciting toy at Scott’s disposal is a new shiny cutter. As a rookie, he threw it a grand total of two times. This year, he unleashed 372 cutters, making it his third most-used pitch (18.9%) after the four-seamer (47.1%) and a sweeper (22.8%), which is also quite good. The key to the cutter is that it’s about six miles per hour slower than the four-seamer and has proven effective against hitters on both sides of the plate. Whether it’s Kyle Schwarber or Ronald Acuña Jr., Scott has a putaway pitch for them, effective at both the top and bottom of the strike zone.

With a 25.0% whiff percentage, Scott’s cutter landed him in the same tier as well-known cutter merchants Drew Rasmussen and Kenley Jansen in that statistic. And while its .228 xBA points to some providence, the cutter spat out a .118 batting average against in 2026, the lowest of anyone who threw at least 300 of them. The same is true of its slugging percentage against, which at .184 was also the lowest mark in the majors, .352 xSLG be damned. Now I’ll show you Scott’s briefly aforementioned sweeper, the pitch of his that got the most empty swings and was responsible for 37 of his 134 strikeouts. It’s absolutely beautiful to behold when it’s dancing like this.

Brent Headrick – New York Yankees

2026 stats: 81 games, 78 1/3 innings, 2.18 ERA, 2.46 FIP, 30.1 K%, 8.3 BB%, 2.1 WAR

Among pitches that were thrown at least 100 times during the 2026 season, Brent Headrick’s split-finger of death was one of the 15 hardest to hit, placing it among legendary whiffers like Jhoan Duran’s sweeper, Mason Miller’s slider, and Tyler Glasnow’s curveball. At a ridiculous 51.3%, the whiff rate on that pitch shot up into the air like Tony Hawk at the X Games. In part three of Davy Andrews’ pitching superlatives, the offering also earned the prestigious Veganest Pitch honors, as only one of the 162 splitters that left Headrick’s hand ended up being a meatball. With that insane ability to avoid the middle of the plate, one can understand how Headrick’s splitter gets so many fruitless swings. But even when it did get put in play, the average exit velo on the pitch sputtered at 77.7 mph.

Headrick has now participated in four major league seasons and thrown 235 splitters. Nobody has ever hit one over the fence. Only two people have ever even recorded an extra-base hit against it, and they were both doubles that happened early in the 2026 campaign. Since this Mark Vientos grounder up the line on May 16 that you’re about to watch, every hit against Headrick’s splitter (and there were only five!) went for singles.

While David Bednar hogged up the Yankees’ saves, and Adrian Morejon stole the shine as the game’s prominent non-closer lefty reliever, Headrick was squarely in the conversation for best relief pitcher of the 2026 season. Developing this supreme splitter — which ran a 41.2% chase rate against righties — made Headrick an invaluable part of the Yankees’ third straight 90-win season, and yet another feather in pitching coach Matt Blake’s hat. Against righties, as a matter of fact, the splitter elicited 17 strikeouts and 17 balls in play. This all from a guy who was far from a guarantee to even make the team when he got to spring training, let alone become an inner-circle high-leverage dude.

“When I first started getting into those high-leverage situations, the first one or two, it was more stressful because I hadn’t been in that situation before,” Headrick told Alfred Santasiere III for MLB.com. “But once you keep doing it over and over again, it becomes normal.”

Sure, but this splitter — and the astounding stats Headrick put up because of it — are anything but normal, man.

Keibert Ruiz – Washington Nationals

2026 stats: .280/.316/.443, 10 HR, 24 2B, 105 wRC+, 10.5 K%, 4.5 BB%, 1.9 WAR

During Keibert Ruiz’s tumultuous 2025 season — in which he suffered two concussions, ran a career-low 63 wRC+, and was graded as one of the worst defensive catchers in the sport — the Nationals also held internal discussions regarding his defensive positioning. Those conversations centered on the question of whether Ruiz should move back in his crouch to limit his amount of foul tips to the face, not even whether the Nats could find something to turn their supposed cornerstone catcher from a liability behind the plate (-2 blocking runs above average, -9 framing runs, -10 FRV in 2025) into something passable.

But lo and behold, in 2026, the age-27 season of his embattled career, Ruiz finally righted the ship. The thing that earned him a shoutout here was the wholesale turnaround in framing, where he was worth 3 runs above average in 2026 and showed a knack for stealing strikes at the bottom of the zone and the part of the plate that’s inside to lefties and outside to righties.

The gallery-level framing, plus going from bad to merely neutral at blocking, gave Ruiz a 1 FRV, his first ever positive mark in a season with at least 500 defensive innings at catcher. This — along with a 105 wRC+, and personal bests in batting average, on-base percentage, slugging percentage, and ISO over a full season — could not have come at a better time for the Nats, who need someone, anyone, outside the CJ Abrams–James Wood duo to pop.

Nick Gonzales – Pittsburgh Pirates

2026 stats: .303/.367/.388, 7 HR, 27 2B, 111 wRC+, 16.3 K%, 7.1 BB%, 2.2 WAR

And finally, we have pint-sized Pirates infielder Nick Gonzales, one of just seven qualified batters to hit .300. It is somewhat funny that Chandler Simpson, the best American League comp for Gonzales, is a Silver Slugger finalist at his position despite Gonzales far outpacing him in wRC+ (111 to Simpson’s 93), finishing just three points behind him in batting average (.306 for Simpson and .303 for Gonzales), and playing a position with far fewer mashers (the average wRC+ for an American League outfielder in 2026 was 99, whereas the average wRC+ for an NL third baseman was 93).

Nevertheless, Gonzales enjoyed a magical run in 2026. Even if he was bogged down by the same lack of power that fuels Simpson’s haters — and, rightfully so, led to Alex Bregman and Max Muncy being the NL’s Silver Slugger finalists at the hot corner — Gonzales deserves greater acclaim. A 31-point spring in wRC+ from 2025 to 2026 is bananas in its own right, but so is the way Gonzales did it. As mentioned before, he is not a power threat, and clubbed only seven homers while his ISO declined for the fourth straight year. A sky-high .360 BABIP tells much of the story of his pleasing batting average, with his exit velocities still mostly residing in the 80s. It’s not like he hits the ball so hard that defenses have issues fielding it. In fact, the area that Gonzales refined was his plate discipline. Drill into that, and you’ll find that the key was not swinging at all.

Pete Crow-Armstrong will win an MVP for his 2026 season, one that saw him lead all qualified hitters in swing percentage decline. The Cubs’ center fielder swung at 60.1% of the pitches he saw in 2025, and whittled that down to 50.1% in 2026, good for a neat and tidy -10.0 difference. Not far off of that is Gonzales, who went from 57.4% to 52.5% (-4.9). There’s only 10 hitters on that board between PCA and Gonzales, and many of them — including Jackson Chourio, Elly De La Cruz, and Junior Caminero — also had their finest offensive seasons to date.

Unsurprisingly, with fewer swings came fewer whiffs for Gonzales, a contact hitter who wasn’t swinging and missing all that much to begin with. The Pirates knew what they were getting too when they drafted Gonzales — a five-foot-eight scrapper who hit .435 over his final two years of college ball at New Mexico State — with the seventh overall pick in 2020. Even if his registering 133 singles out of 167 total hits presents a bit of an empty-calorie offensive profile, Gonzales still has value in his .367 OBP, which was top-20 in the league and should continue to climb as he gets more discerning at the plate. Swinging less often predictably led to a higher walk rate and lower strikeout percentage, but that unfortunately doesn’t lend itself to video quite like the other skills highlighted in this article.

That is, unless you get your rocks off on sick 3-1 and 3-2 takes that hold up after ABS challenges.

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At least nine times during the 2026 season, a replay review overturned a hit-by-pitch. It may well have happened more often, but I found nine pitches that went down as foul balls because the umpire awarded the batter first base after an apparent hit-by-pitch, only for the defending team to successfully challenge that the ball hit the bat instead. Once every two or three weeks, a batter grabbed his hand and exclaimed, “Ye gods, I’ve been struck!”

Only for the catcher to arise and reply, “I’ll prove the contrary, thou subtle, perjured, false, disloyal man! Thy club’s the thing withstood th’ offending sphere.”

At which point the Mattress Firm Supermo replay intoned with just the right level of firmness, “Forsooth, this catcher is the messenger of truth.”

And the umpire had no choice but to swallow his pride and announce to the fans, “Lo, through the proof of the Mattress Firm Supermo replay I see how I’m hoodwink’d. Behold my fingers three.”

These may not be exact quotes, but you get the point. It’s not particularly rare for a hit-by-pitch to get overturned. However, during the 2026 season, I was hoping that we’d see one particular variety of hit-by-pitch get overturned. It is my favorite kind of hit-by-pitch, which I now realize seems like a weird thing to say. To be clear, I’m not in favor of people getting hit by pitches. However, as long as people are getting hit by pitches, I prefer for it to happen in a way that doesn’t involve injuries but instead involves some element of silliness. For example, this ball that hit Joey Votto in 2022 has a lot going for it. The first is the eloquence with which Votto expressed his feelings about getting hit, so please turn your volume up.

The second is the fact that the pitch was in the strike zone. It should have been a strike, and it wouldn’t be the last time Votto earned a free trip to first base on such a pitch. Here he is almost exactly a year later hurling himself into the path of another would-be strike.

Votto is by no means alone here. Since the beginning of the pitch tracking era in 2008, we’ve seen 40 hit-by-pitches on pitches that should have been called strikes, and at least one in every season except 2010 and 2011. When it happened in previous years, the defense had no recourse. Even if the fielding team were to challenge the play, the review could only look at whether the ball actually hit the batter, not where it hit him. In 2025, when Ketel Marte decided to send his elbow on a fishing expedition in the strike zone and caught himself a Germán Márquez fastball, Colorado catcher Hunter Goodman had no choice but to hang his head in despair.

The bright side of this Young Goodman Frown story is that the ladies in the background look delighted to be receiving their nachos.

In 2026, that changed. (The part about catchers not having any recourse, not the nacho part. People will always be delighted to receive nachos.) Or at least I’m pretty sure it changed. With the implementation of the ABS challenge system at the major league level, pitchers and catchers could finally tap their helmets if they believed that the pitch that hit a batter was in the zone. I think. I’ve looked in all the explainers I could find, and I wasn’t able to find any kind of exemption for hit-by-pitches, so I can’t imagine why that wouldn’t be the case. The rules about hit-by-pitches in the strike zone are clear; they’re strikes. In theory, the ABS system should have been the end of the z-HBP.

But even that theoretical utopia requires the catcher to challenge the call. So far as I can tell, that never happened once. Instead, we saw four hit-by-pitches on would-be strikes in 2026. That’s tied for the most in any season. Let’s name and shame the offenders, shall we? Here are the would-be strikes that struck Mike Trout, Tyler Heineman, Austin Martin, and Alejandro Osuna.

The weird thing is that although none of the catchers thought to challenge the pitches, they really did seem to know that they were strikes. We can say that because they tried their best to frame all four pitches. At the very least, they knew the pitches were close enough that they might get the call. Salvador Perez’s herky-jerky attempt at this task might help explain why he’s put up such poor defensive numbers over the past several years.

Once they realized what happened, three of the catchers lodged some form of protest. Heineman’s offense was the most grievous by far. Simeon Woods Richardson froze him with a comeback splitter that should have been strike three. It was the only pitch that was bending back toward the zone, which in theory should have made it an easier call for the umpire. Heineman, perhaps sensing that he was beaten, threw his elbow into the path of the pitch. Minnesota catcher Victor Caratini made his case to home plate umpire Jacob Metz (yeah, we’re naming and shaming everybody) by turning around and pointing to the spot in the strike zone where the ball would have landed.

The funny thing is that when this happened a couple months later, also in Minnesota, also when the Twins were in their lake-themed City Connect jerseys, Caratini’s teammate Ryan Jeffers made his case to home plate umpire Chris Guccione the exact same way.

The only logical conclusion from these two data points is that the Twins have a firm organizational policy in place for this occurrence. They are prepared for any eventuality, and the field operations manual clearly states that if a batter gets hit by a pitch in the strike zone, you turn around and explain the situation to the umpire, and you helpfully point just to remind the umpire that the strike zone lives a foot or so above home plate and is an elbow-free zone.

On August 5, the shoe was on the other elbow. When Minnesota’s own Austin Martin wore a 2-2 Noah Cameron curveball on the corner, Perez seemed less prepared. The Royals clearly never wrote a “Point at the Strike Zone” memo, and it showed. Instead, Perez whipped off his mask, turned toward umpire John Bacon, and, uh, proposed marriage maybe? Catchers will do anything to get a call.

I mean, Perez probably said something about the pitch being a strike rather than offering his hand in holy matrimony. But if a catcher were going to propose to an umpire between pitches, don’t you think this is what it would look like? Maybe that’s why one-knee-down catching has taken the league by storm. You never know when it’ll be the right time to pop the question.

By far the best reaction came from White Sox catcher Drew Romo. When you’re a rookie with 23 big league games under your belt and the person dipping an appendage into the strike zone is literally Mike Trout, you probably don’t feel secure enough to turn around and make your appeal to home plate umpire Nic Lentz. But you’re still a professional with a job to do, so you still try to mitigate the damage. You look out at your pitcher and you reassure him the best way you know how. For Romo, that means an understated head tilt, as if to say, “Well I thought it was a good pitch.”

You may have noticed that three of these pitches should have been strike three. In fact, 24 of the 40 in-zone hit-by-pitches Statcast has recorded came with two strikes. That’s 60%, more than double the percentage of all pitches (29%) that have come with two strikes during the pitch tracking era. I know it’s a small sample, but that’s still way too high to be a coincidence. Batters who get frozen on a pitch on the corner are making a very quick decision to avoid a strikeout by spelunking into the depths of the strike zone.

The good news is that catchers finally have a tool for fighting back against this encroachment. They can use their heads. Wait, sorry, I mean they can tap their heads. They just have to remember to do it.

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I’ve decided that my guy in this free agent class is left-handed pitcher Adrian Morejon. Ben Clemens ranked him eighth on the top 50 free agent list, and predicted that he’d get $72 million over three years. Our readers came to a median estimate of $64 million over four years.

I think they’re out of their minds. Me? I would’ve had Morejon no lower than fifth in this caffeine free Diet Pepsi of a free agent class, perhaps as high as third. I’d give Morejon $100 million over five years without blinking.

I don’t get the sense that I’m sticking my neck out too far by saying this; someone’s going to pay over the odds for this non-closer reliever because they think they can translate his upper-90s velocity and elite groundball rate to the rotation. Morejon got four or more outs in 25 of his 78 regular-season appearances in 2026, and he has the elite changeup that conventional wisdom requires from a lefty starter.

But I don’t want Morejon to start. I’ve got something better in mind.

Over the past three seasons, Morejon leads all relief pitchers in innings pitched. He’s third in ERA, sixth in xERA, and ninth in FIP. The Padres used him as a setup guy and general high-leverage stopper, on account of having at least one of either Robert Suarez and Mason Miller available to close games out. So over the past three seasons, Morejon has just eight saves, but that usage pattern put him in position to rack up 60 holds (ninth among qualified relievers), 95 shutdowns (eighth), and a win probability added total of 7.32 (sixth).

Morejon also won 25 games over that span, five more than any other relief pitcher. In 2025 alone, he picked up 13 victories; only one of that year’s six Cy Young finalists had more wins.

This sparked off a familiar itch in my brain.

On a long enough timeframe, everything I write about baseball will eventually circle back to one core belief: They should bring back the 1970s-style relief ace. Unless I get fired before Christmas or something, this is not going to be the last time I write about it.

Over a long season, it makes a lot of sense for your best relief pitcher to be consigned to protecting close leads in the ninth. Maybe have him throw in a tie game every so often when he hasn’t had a save opportunity in a while, or stretch him out to two innings in an emergency or the playoffs. It makes bullpen management simple, settles everyone’s expectations, massages the relief ace’s ego, and lessens the temptation for overuse.

But all things being equal, the modern one-inning closer is not how you get the most bang for your buck from a relief ace.

Integration is a useful historical dividing line for professional baseball history, but 1947 is also about the time when relievers started to come into fashion as a distinct pitcher role, rather than a less desirable alternative to the starter. Hugh Casey came back from military service and finished 12th in NL MVP voting in 1947 without making a single start. The Yankees converted Joe Page to full-time relief around the same time, with similar results, and in 1950, Jim Konstanty won the NL MVP Award ahead of teammate Robin Roberts, who threw 304 1/3 innings and tossed five shutouts.

The modern closer role has definitely led to some of the best per-inning relief pitcher performances in baseball history.

Since 1947, there have been 7,582 individual seasons in which a pitcher has thrown at least 50 innings in relief. The best of those seasons, in terms of ERA-, are almost all from modern closers. The top four are Zack Britton in 2016, Emmanuel Clase in 2024, Fernando Rodney in 2012, and Dennis Eckersley in 1990 — all memorable campaigns.

Of the top 100 reliever seasons in ERA-, 84 came from a pitcher who averaged fewer than four outs per appearance. In 44 of those cases, the pitcher in question also registered either a save or blown save in more than half of his appearances. Only one of the top 27 ERA- seasons — Blake Treinen in 2018 — ran 80 innings.

What if you sorted by a different metric? Like WAR, for instance? The top 100 WAR reliever seasons include 39 by a pitcher who met my criteria for a closer — fewer than four outs per appearance, more than half of appearances resulting in a save or a blown save — but only one of the top 15 fits the bill.

The one exception is Eric Gagne’s 2003, which is not only probably the best season ever by a one-inning closer, but it came at an unusually high volume for that role: 82 1/3 innings. The no. 2 WAR total for a one-inning closer was Mason Miller this season; he only threw 70 innings.

If you sort by WPA, you get a mix of one-inning-closer seasons and traditional-relief-ace campaigns: 59 closers, 41 non-closers. Of those 41, another 15 averaged fewer than four outs per appearance.

That breakdown makes sense. The one-inning sprinters get the best results, but the multi-inning stoppers throw more volume. WAR and WPA are both counting stats, which reward volume, but WPA especially penalizes pitchers who get overextended and blow up in crucial moments.

For example: One of the best and most famous relief seasons ever came from Mike Marshall in 1974. Dodger manager Walter Alston called on Marshall 106 times for a total of 208 1/3 innings, both single-season records for a reliever. And Marshall pitched well, with a 2.42 ERA and a K%+ of 125. He won, and I’d argue, deserved, the Cy Young for doing the work of three high-leverage relievers. To this day, that’s one of the 10 best relief seasons since integration, by WAR.

But Marshall finished with a negative WPA, because when you pitch in almost literally every close game, you’re going to have a few stinkers.

What we have here is the stolen base conundrum in a different form: Use your relief ace too little and you’re leaving high-leverage outs on the table. Use him too much and you’ll overextend him and get beat.

To say nothing of the long-term effects on the pitcher’s body; by the end of his career, the inside of Marshall’s shoulder looked like shredded cabbage. He’s arguably most famous now for his second career as an exercise physiologist. In his one-man lab in Florida, he reinvented the overhand pitching motion in a way that, he claimed, would eliminate elbow injuries. But like so many iconoclasts, Marshall lacked the diplomatic skills to get his techniques adopted — or even tested seriously — by the mainstream.

Clearly there’s a middle ground between the conservative modern closer and spreading the relief ace too thin. One thing is for certain: The modern closer role isn’t putting the best pitchers in the highest-leverage situations.

Since 1947, there are 61 seasons in which a reliever posted a gmLI (leverage index when entering the game) of 2.2 or higher. Just six of those came from modern one-inning closers. If you lower the gmLI threshold to an even 2.0, you get 237 seasons, 59 of them from modern closers.

There has to be a way to make a relief ace’s bullets count for more: Target not just save situations but all late-and-close situations, perhaps even sometimes throwing the relief ace when your team is trailing by a run.

That is, of course, what the closer used to do. The top WPA and WAR seasons came mostly from relievers in the 1970s and 1980s, who did exactly that: Willie Hernandez, Dan Quisenberry, Rich Gossage, Kent Tekulve, and Bruce Sutter.

I suspect that we’re getting into the Nolan Ryan Memorial Survivorship Bias territory here; these aren’t your normal relief aces. Quisenberry and Tekulve famously threw sidearm or underhand; Sutter had to invent a new pitch.

But I dunno, if Miller can throw 70 innings over 66 appearances, and Morejon can throw 86 innings over 76 appearances, couldn’t one of them throw 90 or 100 high-leverage innings in a season through indifference to the save?

This is far from an original thought, I’ll grant you. It’s the subject of an essay in Bill James’ New Historical Baseball Abstract, so this has been a thing for at least 25 years.

A couple teams have flirted with that role — especially those that have a durable hard-throwing stopper (often, for some reason, a lefty) to pair with a traditional closer. There have been others — most recently Aaron Ashby — but the most famous example was Andrew Miller, on a 2016 Cleveland team whose nominal closer was Cody Allen.

In honor of Miller, and at the risk of getting Derek Gardner’d, I give you a new stat: Multi-Inning Lots of Leverage Relief Appearances, or MILLER Appearances, for short. These are relief outings of at least four outs, with an average leverage index of 1 or higher.

In the 2026 regular season, 8.6% of all relief appearances were MILLER appearances. That’s the highest percentage since before the pandemic; actually, 2019 and 2020 beat 2026 by less than a hundredth of a percentage point. The last time the MILLER rate got to 8.7% or higher was 2008.

And guess who had more MILLER appearances than anyone else this past season?

Three lefties in the top four. It’s like the three-batter minimum has caused the LOOGY to be replaced by the Lefty Multi-Inning GuY (LMIGY). Someone remind me to come back to this if I get bored during the lockout.

Back to Morejon in particular. He had 24 MILLER appearances in 2026; outside of Will Venable’s Bullpen of Perpetual Emergency, no other pitcher had more than 15. Morejon also leads the league in MILLER appearances since 2024; only 12 other pitchers have a 24-pack of MILLER over the past three years combined.

And here’s the best part: During this three-season run of excellence, Morejon has been excellent no matter the conditions. But he’s been better when he’s pitching more frequently, and longer.

It’s pretty rare for the high-performance version of a thing not only to be durable but also to get better with repeated usage. Morejon is to relief pitchers what cast iron is to cookware.

The actual usage of a relief ace is going to vary wildly, but just for the sake of argument: If last year’s Padres had thrown Morejon for exactly two innings whenever he hadn’t pitched the day before, he would’ve thrown 172 innings. And when Morejon went multiple innings last year, he averaged 5.03 pitches per out; 30 pitches every other day doesn’t seem like a crazy workload.

And that’s probably overstating things some; a lot of those six-out outings would probably end up being four or five. He might throw the odd back-to-back, but go two or three days without pitching afterward. But if managing to the save rule gets you 70 innings over 65 appearances, Morejon could have a bigger impact on 70 games over, say, 110 innings.

Proposing this has the effect of yada-yada-ing some pretty important particulars: Specifically, you need a manager who’s really good at identifying high-leverage situations before they happen, so Morejon has time to warm up. And he’d have to have the confidence and discipline not to warm Morejon up just in case, and then not bring him in. Over the course of a whole season, with a flesh-and-blood human being to consider, the gap between theory and practice is gigantic.

But consider what even a successful relief ace-to-rotation conversion looks like. Let’s set my idea to re-create Goose Gossage from first principles; are you really getting more value by converting a relief ace to a starter? I’m not convinced.

And that’s not even considering the possibility that a conversion goes sideways. Don’t get me started about Jordan Hicks.

In short: Don’t sign Morejon to be a closer. Don’t sign him to be a starter. Give that man however much money he asks for, and roll the calendar back to 1980.

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Even though the offseason has technically begun, we’re currently in the lull between the end of the World Series and the real start of hot stove season. Teams are just about done with the annual housekeeping necessary to prepare their rosters for the winter, but the big moves are still on the horizon and the owner’s lockout is looming. That means it’s as good a time as any to take stock of how each team measures up.

The rankings below present each team as they are currently constructed, based on our Depth Charts playing time projections. This should give us a pretty good idea of which teams would be ready to compete if the 2027 season started today, and which teams have a lot of work ahead of them this offseason. I’ll start with teams projected to finish below .500, and then will have the top half of the rankings later this week.

Our power rankings use a modified Elo rating system. If you’re familiar with chess rankings, you’ll know that Elo is an elegant ranking format that measures teams’ relative strength and is very reactive to recent performance. For these offseason rankings, I’ve pulled the Depth Charts projections and calculated an implied Elo ranking for each team. Our projections are entirely powered by the 2027 Steamer projections right now; the ZiPS projections will be added later on in the offseason. The delta column in the full rankings below shows the change in ranking from the final regular season run of the power rankings.

…

The Athletics actually led the thoroughly mediocre AL West through most of May, but a rash of injuries to nearly all of their offensive stars resulted in a bummer summer and their fourth season with 90-plus losses in the last five years. The good news is that Nick Kurtz, Shea Langeliers, Tyler Soderstrom, Jacob Wilson, and Brent Rooker should all be healthy to start next year. And with young Leo De Vries knocking on the door to the big leagues, the team’s offensive core looks potent. The pitching staff is another matter, though 2027 will be the final year the A’s spend in West Sacramento. The upcoming move to Las Vegas puts a little more pressure on the organization to take a big step forward next year to ensure an exciting product is on the field for the franchise’s inaugural season in its new home in 2028.

For a team that looked like it had such a promising future just a few years ago, the Orioles suffered through their second consecutive hugely disappointing season. So many of their top prospects just haven’t panned out in the big leagues and trading Adley Rutschman felt like the end of an era that never actually got started. That leaves Baltimore in the awkward position of having a fairly young team, but far too many holes to fill to suddenly turn the roster into a contender overnight. The O’s will need to be extremely judicious in figuring out how to supplement a core led by Pete Alonso while determining if guys like Gunnar Henderson are actually pieces to continue building around.

Three years have passed since the Rangers won the World Series, and it’s looking more and more like that championship was a flash in the pan instead of the beginning of a long contention window. Most of the team’s best players — Jacob deGrom, Corey Seager, Nathan Eovaldi, and Brandon Nimmo — are on the wrong side of 30, and there isn’t really a wave of young prospects to inject new talent into the roster. The Rangers managed to stay competitive in the AL West for most of the season despite hovering around .500 for the entire year. That probably won’t cut it next year, so they’ll either have to figure out a way to take a big step forward with their aging roster or tear it all down and start over.

Barely anything went right for the Giants this year, and many of their woes — from the uninspired play on the field to the anti-Pride Night demonstration by a few players and the organization’s bungled response to it — were self-inflicted. How the team can best repair its relationship with its fans is unclear, and the path forward on the field is similarly murky. There’s a ton of money wrapped up in three players — Rafael Devers, Willy Adames, and Matt Chapman — and only Devers played up to the level demanded by those massive contracts this season. It’s not all doom and gloom in San Francisco; Bryce Eldridge finally looked settled in by the end of the season and Drew Gilbert was really fun to watch in center field. Still, this is a flawed roster with no easy paths to quick improvement.

Like the Rangers, the Diamondbacks have struggled to build upon their World Series appearance in 2023. They remained competitive in the NL Wild Card race through most of summer, but they ultimately fell short of a postseason berth for the third consecutive season. There are some questions about Ketel Marte’s future with the organization after his unannounced departure from the team in August. According to Nick Piecoro of the Arizona Republic, “in the days surrounding Marte’s return from the restricted and injured lists in late August/early September, players seemed to intimate that they expected Marte to be moved over the winter. Multiple players made comments about getting through the year and ‘dealing with the situation’ after the season.” Beyond whatever happens with Marte, the pitching staff will need some reinforcements this offseason. Corbin Burnes should be healthy next year, but with Michael Soroka and Zac Gallen both free agents, the rotation looks pretty thin behind him.

The Nationals were one of the most fun teams to watch this year thanks to a high powered offense led by James Wood and CJ Abrams. The pitching side of the equation wasn’t anywhere near as enjoyable, but at least Cade Cavalli put together a healthy season and earned a well-deserved contract extension after his breakout. Trade deadline acquisition Connelly Early and a quiet breakout from Andrew Alvarez provide some intriguing pieces behind Cavalli in the starting rotation, too. If Washington can bring in the right pieces during the offseason to bolster its young core, this feels like a team that’s on the cusp of taking a huge step forward.

Like the Nationals, the Marlins also look like a team on the up and up. Breakouts from Otto Lopez and Xavier Edwards give the lineup a dynamic duo to build around, while Sandy Alcantara and Eury Pérez anchor the starting rotation. Unfortunately, Robby Snelling and Jakob Marsee both underwent Tommy John surgery this year — it’s a much longer road back for Snelling as a pitcher, but Marsee probably won’t be healthy until the season is underway. Top pitching prospect Thomas White will also be returning from a shoulder injury that wiped out most of his 2026 season; he probably would have made his big league debut sometime this summer if he hadn’t gotten hurt. The team will have to navigate through all those injury issues and any potential trades it makes (Alcantara, for example, is entering the final year of his contract), but nearly the entire roster is under club control for 2027. Veteran reliever Pete Fairbanks is Miami’s only free agent.

The Cardinals’ final record fell short of .500 for the second consecutive season — the first time that’s happened since 1994–95 — but they really committed to a youth movement in 2026. They gave JJ Wetherholt, Joshua Báez, Leo Bernal, and Quinn Mathews opportunities to make an impact as rookies after trading away a bunch of their veterans last offseason. Weatherholt is a strong contender to win NL Rookie of the Year honors, and there’s more young talent coming up through the farm system. Coming off his long-awaited breakout year, Jordan Walker and the steady Alec Burleson give the lineup a pair of anchors. There’s work to be done on the pitching side of the roster, but St. Louis feels like it’s poised to take a big leap forward next year.

After three consecutive 100-plus loss seasons, the White Sox shocked the baseball world by making the playoffs and coming within one win of reaching the ALCS. Ultimately, the pitching staff was the weak link down the stretch and in the postseason. Noah Schultz and Hagen Smith both made their major league debuts this year and should feature prominently in the rotation in the coming years, but the Sox desperately need some veteran starters to reinforce the youngsters. There are fewer issues on the offensive side of the roster thanks to Munetaka Murakami’s excellent transition to MLB and Miguel Vargas’s big breakout. This is a super young and promising team that has even more talent matriculating through the farm system. The future definitely looks bright on the Southside.

The two teams in this tier made the playoffs in 2026, but each has an uphill battle to get back next year.

Despite a surprise division crown, the Astros are facing some tough questions after finishing the year at .500. It’s the fourth consecutive season they’ve seen their win total drop after their last World Series victory back in 2022. Yordan Alvarez had a MVP-caliber season that propelled the team to the top of the historically bad AL West, but his supporting cast just wasn’t what it used to be. Jose Altuve is deep into the decline phase of his career, Carlos Correa can’t stay on the field, and the pitching staff is a bit of a mess behind Hunter Brown. Randy Flores is the new GM in Houston, and he has the unenviable job of trying to reset this roster while working with meddlesome owner Jim Crane.

The Padres were one of the best teams in baseball down the stretch and nearly toppled the Brewers in the NLDS. Unfortunately, 16 of their players — who combined for 15.5 WAR in 2026 — are now free agents. The potential departures from the pitching staff are particularly striking: Michael King, Nick Pivetta, Casey Mize, Robbie Ray, Walker Buehler, Adrian Morejon, and Jason Adam, just to name a few. For those keeping track at home, that works out to five starting pitchers and two high-leverage relievers. Thankfully, some key hitters won’t be going anywhere — Fernando Tatis Jr., Jackson Merrill, Manny Machado, and Xander Bogaerts still form the core of that group — but the team will need to figure out how to replace the production from Ty France.

The Royals failed to maintain the momentum of the last two years, since their surprise postseason appearance in 2024. Instead, they lost more than 90 games for the third time in the last five years. The loss of Cole Ragans to another elbow repair is a significant blow to a pitching staff that is filled with veteran starters on the decline. Bobby Witt Jr. is an unquestioned superstar, but he can only carry the lineup so far. With so many issues up and down the roster, this team looks closer to another teardown than it does to another playoff run.

The Angels are in the beginning stages of a huge transition. The sale of the franchise to Stan Kroenke has been agreed upon, but not yet made official. That delay has put the hiring of a new general manager on hold. Whoever the team brings in to lead baseball operations will have a tall task ahead of them. Mike Trout played in more than 130 games for the second consecutive season, the first time he’s done that since 2018–19. Still, he’s not the dominant force that he used to be and his supporting cast leaves a lot to be desired. The Halos took their first steps toward tearing down the roster by trading away a bunch of pieces at the trade deadline, but this offseason will mark the true beginning of the rebuild.

The Reds are in a weird position. Elly De La Cruz and Chase Burns are legitimate superstars with enormous ceilings. Hunter Greene would have been mentioned in that previous sentence, but he’s out for all of 2027 after undergoing Tommy John surgery in August. Sal Stewart made a great case for NL Rookie of the Year this season and should provide a nice sidekick to De La Cruz in the lineup. Beyond that, though, the roster is made up of a ton of broken pieces, prospects who didn’t pan out, and spare parts. Cincinnati is nowhere close to building a contender, yet the team has two (or three depending on your opinion of Stewart) stars to anchor the roster. With Greene left to rehab next year, will the organization be OK with staying in a holding pattern until he’s ready to pitch again in 2028? Or will the Reds pull the plug and trade away their most valuable pieces to restart their rebuilding cycle?

With Paul DePodesta now leading baseball operations, the Rockies took a small step forward this year. There were moments when the team looked almost competent on the field. Hunter Goodman continued to mash, TJ Rumfield was a savvy pickup last offseason, and prospects like Cole Carrigg and Zac Veen made promising debuts. The eternal question of how to build a pitching staff at altitude still hasn’t been answered, but at least there’s some progress being made on the position player front.

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