It’s no secret that I’m an obsessive chronicler of bunting in the big leagues. Very good and very bad bunts frequently populate my Five Things column. I’ve written about the best and worst bunts you’ll see in a season, the optimal strategy for bunting in extras, and any number of other interesting bunting-related things – or at least, bunting-related things that are interesting to me. And there’s another great bunting topic to write about right this instant. See, bunts are making a comeback, and for once, they’re doing it for the right reasons instead of the wrong ones. So let’s celebrate the return of the bunt – and also think about why it’s back.

So far this year, batters have bunted the ball into play (or struck out by bunting the ball foul) 640 times. That’s 0.9% of all the plate appearances in the majors in 2026, and while that might not sound like much, it’s a new high in the universal DH era, 25% higher than the 2025 season, which was itself the bunt-heaviest year in that stretch at 0.7%. There were a lot more bunts in the days when pitchers batted in National League parks, of course. But if you limit the search to American League parks and reach into the past, a clear trend emerges. Bunting declined as teams thought more about how bad sacrificing an out is. But then it bottomed out, and now teams are starting to bunt more often:

This is just a chart of how many bunts there are, not how good those bunts have been. In fact, the reason the bunt started to decline in the first place is that many bunts were counterproductive. Sacrificing a runner from first to second at the cost of an out is usually a bad decision on the run-scoring front. It might be a fine fail case – if you fail to bunt for a hit and accidentally sacrifice, that’s not so bad – but pure surrender bunts only make sense in very limited circumstances. Read the rest of this entry »

If you’re a casual follower of great relief seasons, this year has probably been all about Mason Miller for you. That’s eminently reasonable. It’s June 4, and his strikeout rate is still above 50%. If there’s a second name in the running, it’s probably Cade Smith, whose 21 saves pace the big leagues. Maybe Cleveland just has a “dominant closer” machine in the clubhouse somewhere. Who needs Emmanuel Clase? But the reliever atop our leaderboards isn’t either of those guys. (They’re second and third, mere hundredths of a win behind, but let me have my bit.) It’s rubber-armed October stalwart Louis Varland, who is most famous for being available a lot.

Varland pitched in nearly every game of the Blue Jays’ playoff run last year, which made him something of a folk hero in Canada. Those appearances weren’t notable for their outrageous quality – he had a middle-of-the-road 3.94 ERA and a 5.01 FIP in 16 innings – but for how impressive it was to take the ball day after day, no matter the situation, and give his team valuable innings. No Toronto reliever entered in more important spots, and while Varland had zero win probability added in the aggregate, that availability was just cool, and particularly noticeable in today’s splintered world of playoff pitching.

This year, Varland is still throwing a ton of innings. He’s 11th in relief innings pitched, but the guys in front of him are pretty much all long relievers. He’s also tied for 11th in relief appearances. Consider this: No reliever who has appeared as often as Varland has thrown as many innings as him, and no reliever who has thrown more innings has appeared more often. You can rack up a lot of innings pitched if you throw multiple frames per appearance. You can rack up a lot of appearances by being a short-stint guy. It’s pretty difficult to be both, but Varland accomplishes it. Read the rest of this entry »

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I’m not sure whether it’s called the Effectively Wild rule or not, but I learned a fun rule of thumb from that podcast: Statistical samples are only stable after Mike Trout leads the league in WAR. Until then, it’s still too early. This rule made more sense a decade ago, when Trout was the clear best player in the sport, but the sentiment applies today. When Aaron Judge, Shohei Ohtani, and Bobby Witt Jr. are near the top of the leaderboard, it’s probably been long enough to believe the statistics. If they aren’t, it’s too early.

Ohtani and Witt are indeed atop the combined WAR leaderboards, but Judge isn’t even in the top 30. And the rest of the names are kind of strange, too, particularly if you limit yourself to the hitter’s leaderboard and leave Ohtani’s singular two-way nature behind. Oh, there’s a Dodger in the top five, but it’s Andy Pages. There’s a Yankee, but it’s Ben Rice. Two rookies are in the top 10, and they’re both behind Xavier Edwards. It’s an odd leaderboard, no matter how you look at it, and it got me wondering two things. First, is that Mike Trout rule generally true? And second, what does it say about 2026 if so?

I settled on one thing first: no two-way players. That might annoy the Ohtani fans out there, but I had two good reasons. One, he’s been around for a while now, so it’s not like this is some special consideration that only applies to 2026. Second, pulling all these numbers is hard work. I didn’t want to handle corner cases in every year, so I stuck with the pure hitting leaderboard. Given that I wanted to look at the whole 21st century and see how often hitters stay atop the heap from one year to (early in) the next, I opted for a simple definition and only looked at hitters. Read the rest of this entry »

It’s May 29, roughly two full months into the regular season, which means, given the year, that it’s time for everyone’s favorite pastime: parsing competing proposals for a new collective bargaining agreement. Wednesday, the MLBPA released its first proposal for a new agreement. Thursday, MLB followed suit with a proposal of its own. Both are best thought of as opening offers, likely to be heavily modified as the negotiations heat up ahead of the existing agreement’s December 1 expiration. But that doesn’t mean that they’re meaningless. I think these early offers are revealing of what each side cares about most. The specific numbers quoted are unlikely to survive multiple rounds of bargaining, but the concepts and structures that each side favors at this stage could tell us a lot about what an eventual compromise looks like. So without getting too bogged down in the details, let’s peruse both proposals and try to tease out what each side is trying to accomplish.

The MLBPA’s Proposal
The players’ first salvo focuses on two things: revenue sharing and early-career pay. Revenue sharing is going to be a key point of discussion in this negotiation. The league has raised competitive balance concerns for years, and it’s clear that there’s public interest in leveling the playing field. Collectively bargained labor agreements don’t solely play out in the court of public opinion, but making the sport more interesting and marketable is a benefit for both sides, so a more balanced system of distributing revenue seems like a clear path towards sustaining the game’s recent growth.

The central piece of the MLBPA revenue sharing proposal is a redistribution of TV money. Currently, teams share a flat 48% of all local revenue, TV included. The MLBPA proposal would change that significantly. In their framework, the first $50 million from each team’s local TV contract, and two-thirds of the amount above $50 million, would be pooled centrally, along with all national TV revenue. Read the rest of this entry »

It has been a good year for walks. Whatever you want to attribute it to – and trust me, I’ve done a lot of attributing – batters are drawing free passes more frequently than they have for a long time. Well, most batters. The San Francisco Giants didn’t get the memo. As a squad, the Giants have walked only 5.8% of the time this year. That’s last in baseball by a mile. The gap between them and the 29th-place Rockies is as large as the gap between the Rockies and the league average. What gives?

My investigation started with the 2025 Giants. Walk rate is a stable statistic on the whole. If you walk a lot in one year, you’re likely to walk a lot the next year. But the Giants were no slouches when it came to taking a free base in 2025. In fact, they had one of the highest team walk rates in baseball – 9.2%, fourth in the majors. In the second half of the year, they walked 8.7% of the time. The 10 Giants who batted most frequently had a combined 9.6% walk rate. Four of those players are no longer on the team, but they were actually hurting the average – the six remaining Giants who batted most frequently in 2025 posted an aggregate 10.2% walk rate.

Let’s start, then, with those six players:

As Keanu Reeves memorably put it: Whoa. These six have taken 61.5% of the Giants’ plate appearances this year. If they were walking at the clip they did last year, that would add a whopping three percentage points to the team’s overall walk rate, placing San Francisco squarely in the middle of the pack instead of historically low. Read the rest of this entry »

Welcome to another edition of Five Things I Liked (Or Didn’t Like) This Week in Baseball. In keeping with the increasingly lenient definition of “this week” that I’ve been using of late, we’ve got stuff from all throughout May in this column. May is a great time to watch baseball. (It’s always a great time to watch baseball, but May is particularly good.) The weather is heating up. Ballparks are swelling with the start of summer crowds. Tarps are coming off. So please join me on a trip through the league, from fun teams to watch to nifty little plays. And as always, thanks to Zach Lowe of The Ringer for the inspiration.

1. The Go-Go Nats
Nationals fans have endured seven years in the wilderness since the team’s 2019 title. Washington’s season-high win total in that span was 71 (2023 and 2024). This year’s team is finally playing around .500 ball, though our projections think the Nats will end up right around that 71-win high-water mark again. (We have them down for 74 at the moment.) But while the winning hasn’t quite come back yet, the fun has.

This year, the Nationals are dominating on offense. They’re leading the majors in scoring by a mile, averaging an enormous 5.49 runs per game. They’ve hit the most doubles in baseball – in fact, they have the most extra-base hits in baseball. They’re top 10 in on-base percentage, top five in slugging, and top five in stolen bases. They’re first in overall baserunning value. They’re third in BaseRuns-projected scoring. This isn’t smoke and mirrors. Read the rest of this entry »

When a meteor* slams into Earth’s atmosphere, it’s moving so fast that it compresses the air in front of it. That compression superheats the air to nearly 3,000 degrees Fahrenheit, and the extreme heat in turn melts the outside of the meteor. The outer layers of rock glow brilliantly as they disintegrate, leaving a trail of plasma in the meteor’s wake. By the time the flying object has descended to around 30 miles above the surface, air resistance slows it to a more reasonable speed, though still hypersonic. At that elevation, the meteor is in what’s known as “dark flight” – without the plasma trail, the remaining hunk of rock is impossible for the human eye to pick up at that speed and distance. This explains why it’s so difficult to hit Chase Burns’s fastball.

*It’s technically a meteoroid until it encounters Earth’s atmosphere, and then the rock plus the trail of plasma is a meteor until the plasma burns out, at which point it becomes a meteorite. You’re welcome, pedants.

Few pitchers release the ball higher than Burns:

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As the resident FanGraphs playoff odds watcher, I spend a lot of time looking at our playoff odds and trying to figure out both what they’re seeing and what they’re missing. Over the years, I’ve written many audits of how well our odds perform. Last fall, I described a Bayesian method that does slightly better than any of our existing models at predicting playoff teams. It’s particularly useful early in the season, when the headline FanGraphs mode (using projections) can be slow to pick up on new information and the season-to-date mode is prone to overreaction. A Bayesian filter does a good job balancing those two – or so I found last year.

If you’re looking for a detailed technical description of the way that I’m blending up our existing playoff projections to churn out different odds projections, you can find it at the bottom of the article. But first, let’s take a Bayesian trip through the league and highlight the divisions where reconsidering our odds in light of how much the results so far have diverged from preseason expectations matters the most.

AL East

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In high school statistics, we got one rule beaten into our heads over and over again: Don’t extrapolate outside the bounds of your data. Then, when we were done learning that one, we got another rule: Outliers tend to revert towards the mean. Gee, thanks a lot, Mr. Gilliam – how am I supposed to explain Cristopher Sánchez using those two rules?

Look at this table of pitching statistics. Clearly, extrapolating past the edge of Sánchez’s performance seems fine:

We have all of these ERA estimators – FIP, xFIP, xERA, SIERA – because merely looking at someone’s ERA can be misleading. ERA is noisy. Between inherited runners, sequencing, scoring decisions, and just plain old variance, knowing a player’s ERA in one year doesn’t necessarily mean you know how well they played. The whole alphabet of advanced pitching statistics comes down to trying to solve that noise problem by focusing on indicators with greater stability.

In other words, advanced ERA estimators tend to move around less than actual ERA. It follows naturally that changes in ERA estimators are more predictive of future results than changes in ERA. When all of these markers are moving in tandem – and moving by a lot, to boot – the aggregate picture looks very different than your average pitcher with a shiny ERA early in the season. Read the rest of this entry »