You truly cannot make this stuff up. Back in December, the Padres were involved in the biggest trade of the offseason, sending Juan Soto to the Yankees in return for a heaping helping of pitching prospects. It’s the kind of trade you make when you’ve missed out on your goal, a classic attempt to turn a bad situation into an OK one. When you trade one of the best handful of players in baseball for some dudes most people outside of New York have never heard of, it’s fairly easy to guess your team’s trajectory.

But, uh, don’t tell A.J. Preller that. On Wednesday, the Padres made their second blockbuster of the winter, this one headed in the opposite direction: They acquired Dylan Cease from the Chicago White Sox in exchange for Drew Thorpe, Jairo Iriarte, Samuel Zavala, and Steven Wilson, as Mark Feinsand first reported.

This is wild stuff. It’s so hard to get a player like Soto on your team; if you have him, and you’re trying to make the playoffs, there’s almost never a good reason to move him. If you do move him, you’re probably rebuilding, though, not turning around and using one of those same prospects you got in the first deal to add a new star. The Padres, man.
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On Monday, I dove into Kevin Gausman’s fast and furious two-strike fastball approach. Last season, Gausman led the majors in terms of the velocity gap between his normal fastballs and his two-strike offerings, and he prospered with that approach. In 2022, however, he had the same juicy gain in velocity and was one of the worst pitchers in baseball with two strikes.

In that article, I mused that it was really difficult to know what pitchers were doing differently with two strikes. Short of using a stuff model, I said, trying to figure out relative pitch quality between two-strike fastballs and their early-count brethren wouldn’t work. Then I had an epiphany. We have a stuff model. We have two, in fact, one of which is entirely in-house. So like a kid asking for the keys to the candy store, I went to David Appelman and asked if I could get pitch-by-pitch stuff grades.

Now I have those! It turns out that running a giant data-focused baseball website comes with access to a tremendous amount of baseball data. I pulled every four-seam fastball thrown in 2023 and broke them into two categories for every player: two-strike counts and all other counts. Read the rest of this entry »

Here’s an undeniable truth: Your performance matters most in the biggest spots. It sounds silly to write that, in fact. It’s so obviously true. I’m not just talking about professional sports, or even just sports. No one cares if you nailed your violin solo in your basement when you were practicing it Tuesday evening; they care whether you fumbled the chord progression in Thursday’s big recital.

That self-evident truth has led to decades of squabbling over baseball performances. It’s incontrovertibly true – and yet it seems that players don’t have a lot of control over when they have their best performances. If you want to start an annoying discussion with your uncle (not my uncle, hi Roy, but your generic back-in-my-day uncle), just talk about RBIs or pitcher wins and say something about clutch. You won’t thank me, because just imagining that discussion is giving me anxiety, but you’ll certainly prove my point.

What if we could find a place where players can control their best performance, though? There’s one place in baseball that follows an orderly progression of leverage: the count. The first pitch of an at-bat just matters less, on average, than one thrown with two strikes. That’s true regardless of who’s at bat, regardless of who’s pitching, and regardless of the game situation.

What’s more, there’s an easy way that pitchers can change their performance, and it’s largely in their control. They don’t throw every single pitch the exact same; that would be flatly impossible. Some of the variation in pitch shape is inevitable, caused by minute differences and grip or infinitesimally different release points. But velocity? Pitchers can mostly control that.
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Over the next month, we at FanGraphs will be highlighting a number of site features and showing you how we use them. The goal is to make your visit to the website more enjoyable, and to help you get the most out of the features we’ve added over the years. Today, I’m going to walk through the various ways we deploy projections to make predictions about the future. Let’s explore our projected standings and playoff odds pages.

Before I ever worked at FanGraphs, I spent countless hours messing around with the playoff odds page. I like learning about the future, or at least learning about many possible futures, and I always found the slow-changing nature of projections early in the season to be soothing as a Cardinals fan. Stressed about last night’s crushing loss? On May 15? I could always look to the odds page, see that the team’s chances had barely budged, and calm myself down.

Five years into working here, I still use many of the same pages I did then, but they’ve been upgraded a good deal in the meantime. Let’s start with the nerve center of our predictions, the page that shows everything that feeds into our much-discussed playoff odds: the Projected Standings. You can find them using the navigation bar at the top of the site:

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I’m not the first member of the Cole Ragans fan club – that’d be Nick Pollack. I’m not an early member – hi Eno and Esteban. The cat is out of the bag: A scout called Ragans “left-handed deGrom” in a recent Jeff Passan roundup. The Royals’ left-hander looks like an absolute terror on the mound.

So I’m not going to try to convince you that Ragans is good. Those other articles have surely done a good enough job of doing that. I’m also not going to try to convince you that he’s a left-handed version of the best inning-for-inning pitcher of the 21st century. But I do want to take a quick look at how he’s continuing to change his arsenal, and how some of his old skills could help him keep his tremendous run of form going in 2024.

The reason Ragans has drawn such flashy comparisons likely starts with his fastball. As Passan noted, he averaged 99.2 mph in his first start of spring. Statcast didn’t track it, but I was able to capture some of it by watching the broadcast. There was no radar gun, but the announcers frequently mentioned his velocity and never said a number lower than 98. It certainly looked pretty sharp when he blew it past Mike Trout:

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Spring training is a reliably terrible time for injury news. After a whole winter of not playing (though still training, of course), ramping back up to game speed inevitably creates new injuries or aggravates old ones. This process is always worse for pitchers, because their job is inherently more injury prone. I’m not telling you anything you don’t already know in this introduction.

Here’s something you might not have known, and certainly didn’t know before this week: The Boston Red Sox look to be hit hardest by this yearly attrition. As Jeff Passan reported, Lucas Giolito is probably going to miss the entire season with an elbow injury. He has both a partially torn UCL and a flexor strain, a double whammy that almost always leads to surgery. That’s a tough injury for a team that absolutely couldn’t afford it.

Oh, sure, other teams have suffered unfortunate injuries to top starting pitchers. Justin Verlander will begin the season on the IL with shoulder soreness. Sonny Gray tweaked his hamstring and might miss Opening Day as a result. Kevin Gausman is dealing with shoulder fatigue and his timeline for returning is murky. The list goes on and on. But Giolito’s injury looks more severe and will likely require a much longer recovery time that the other ones will, and that puts Boston in a particular bind. Read the rest of this entry »

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I’ve had depth on my mind a lot recently. That’s because a lot of us here at FanGraphs have, and it’s turned into some pretty cool work that I previewed last week. That’s probably the last you’ll hear about that little project for a bit while we keep refining it and trying to figure out how to use the general concept in different ways. But there was one takeaway in the comments section that I found pretty amazing and I’m going to riff on it today because hey, it’s still early March and baseball news is in short supply.

Remove the top 10 players from 28 teams in baseball – all but the Rockies and Nationals – and look at every team’s winning percentage against neutral opposition. The Rockies are projected 29th out of 30 teams, ahead of only the White-Sox-Minus-10s. The Nationals, meanwhile, are 27th, ahead of just the Angels-Minus-10s and then those Rockies and the Pale-Hose-Minus-10s.

That just sounds wrong. Remove the Mets’ best 10 players, to pick a so-so divisional rival for one of our benighted franchises, and their best remaining player would be either Brett Baty or Luis Severino, both projected for 1.6 WAR. Again, that’s their best player in this hypothetical world. And we have them down as a .425 team. We think the Nats are at .408 at full strength! It’s truly hard to wrap your head around how that could be possible. Read the rest of this entry »

Yesterday, I laid out a new method of quantifying depth that we’re looking into here at FanGraphs. It’s based on the idea that while our depth charts are a point estimate of how much each player will play, the real-life way things work is different. To mimic reality more closely, we’re experimenting with removing players from the depth charts algorithmically and rebuilding teams on the fly to see how they look without their best players. Yesterday’s article covers our methodology in great detail.

There’s one thing that I wanted to add to that article but couldn’t find the space for: more tables. There was one big giant table in there that showed each team’s winning percentage as we removed more and more players from their squad. But that’s just not a great way to look at anything – 300 numbers in a giant table is more information than our brains can easily process. I don’t have a lot of new information today, but I thought I’d slice that data up into more bite-sized chunks so you can look at it without your eyes glazing over. One quick note: All the tables in this article are sortable, so you can order them by whichever category you so desire. Read the rest of this entry »