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 »

One of the great perks of working at FanGraphs is that I get to discuss baseball with my equally obsessed coworkers. Obviously, this is the kind of job you don’t get into unless you love the sport. A lot of the time, that means we just end up nerding out over how much we enjoy some minor but cool thing, or perhaps discussing our favorite of the game’s idiosyncrasies. Sometimes, though, we come up with new ideas together, or one person’s passing fancy turns into another person’s brainstorm, and before you know it, something nifty and novel is happening.

That’s why I’m writing this article today. At the December Winter Meetings, a subset of us sat down for our annual let’s-talk-about-fun-baseball-problems technical meeting. David Appelman and Sean Dolinar ran things. Folks like Jeff Zimmermann and Dan Szymborski popped in at various points. Jason Martinez and Keaton Arneson had big plans for how to improve the site’s functionality. Those guys are great at building models, running websites — advancing the state of how FanGraphs (and ZiPS) works, basically. I like to make jokes and write articles about bunts, so as far as I can tell, I got invited because I’m good at coming up with bad but interesting ideas.

That said, this year one thing was on a lot of our minds: depth. I’ve written a lot about how well our playoff odds reflect reality. They’re pretty good! But there’s always been an obvious problem with them. They use static rosters, which means they don’t account for the fact that some teams are more vulnerable to injury or underperformance than others. Read the rest of this entry »

When the Dodgers traded for Tyler Glasnow this offseason, he wasn’t the only player the Rays sent west. Manuel Margot also joined Los Angeles, where he would to fill Jonny DeLuca’s old role as a righty-hitting outfielder capable of playing any of the three spots. Yet, Margot wasn’t exactly a snug fit for the Dodgers; his inclusion in the trade felt more like a way for Tampa Bay to shed salary. It seemed likely that Los Angeles would flip him to another team before the start of the season.

That’s exactly what happened on Monday, when the Dodgers sent Margot and minor league infielder Rayne Doncon to the Twins in exchange for minor league shortstop Noah Miller. Los Angeles also agreed to cover $6 million of Margot’s $10 million salary for 2024, along with the $2 million he’d be owed if Minnesota doesn’t exercise its team option for 2025, as Aaron Gleeman reported. So, in trading Margot, the Dodgers are saving $4 million; naturally, they promptly turned around and signed Enrique Hernández to a one-year, $4 million deal.

You can almost analyze the Dodgers’ side of this trade in a box, because the things being exchanged are so similar. In fact, to make my analysis make sense, you have to know how close the prospects are in value, so let’s start there. Doncon is a 20-year old middle infielder who spent 2023 at Single-A Rancho Cucamonga struggling against older pitchers. Want a prospect novel? Eric Longenhagen has one for you:

Doncon was a 2021 and 2022 backfield prodigy who looked like he could become a slugging middle infielder. His bat speed, body projection, as well as his struggles on defense and with chase, prompted Alfonso Soriano pipe dreams and more level-headed Esteury Ruiz comparisons at the time. Doncon had a mediocre 2023 with the bat – .215/.283/.368, albeit with a career-high 14 homers – but looked much better on defense. He currently has the actions and arm strength for shortstop, but he’s still young and has a lot of room on his frame, which means he may yet outgrow that position and move to either second or third. Doncon’s pitch recognition is not great, and he’s a bit more chase and whiff prone than is ideal, but he has good power for a hitter his age and is probably going to grow into more. The longer he can stay at short, the better chance he gives himself at being a useful big leaguer despite his flaws. The Twins have two seasons to develop Doncon before they have to decide whether to expose him to the Rule 5 draft, and realistically, they have another year or two beyond that to let him barbecue on the 40-man if they really want to. He adds an element of upside to their system as well as an element of risk. He is not likely to have a meteoric rise. Instead, he is a slow-burning, high-variance prospect.

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