The first baseball cap I remember buying was a gorgeous Orioles throwback. I’m not sure what exactly drew me to it. Maybe it was my mom’s lifelong Orioles fandom. Maybe it had to do with the crisp colors. Maybe I’d just listened to noted ornithological transporter Jay-Z on the drive to West Town Mall. “Before Mitchel and Ness did it/I was moving birds like an Oriole fitted/I’m Cal Ripken Jr., let’s get it” always got me excited to watch some baseball. Whatever the reason was, though, that hat called out to me, so I paid an exorbitant price for something I ended up not wearing very frequently.

I’m telling you this story for a few reasons. First, I want to establish my bona fides as someone who has always had a soft spot for the O’s. Second, I get to show my age a bit — I was in high school when The Blueprint 2 came out. Third, who doesn’t like telling stories? But the main reason is that ledes are hard to write, and I want to talk about the O’s today. To quote Jay-Z: Let’s get it.

A recent Ken Rosenthal article had me double-checking payroll lists and salary tables. The Orioles – the Orioles!! – were listed as the team who increased its payroll by the most from 2024 to 2025. I looked at that for a little bit, looked at the data to confirm that the never-errant Rosenthal had, in fact, not erred, and then I let out a long puzzled sigh. It’s true! The O’s have opened the purse strings this winter. There are a few ways to calculate payroll, but based on the yearly expenditures listed in RosterResource, here are the top five payroll increases across the majors:

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The biggest remaining free agent of the 2024-25 offseason is off the board. In a splashy signing Wednesday night, the Boston Red Sox and Alex Bregman agreed to a three-year, $120 million deal. There’s no shortage of things I want to say about this match of team and player, so let’s stop with this boring introduction already and get right into it.

The Team

The Red Sox needed Bregman, or someone like him, badly. Just one problem – there was no one else like him. When Dan Szymborski ran the numbers last week, he found that the Sox were one of the teams who would receive the greatest boost in playoff odds from signing Houston’s long-time third baseman. Per Dan, Bregman adds 10.8 percentage points to Boston’s chances of reaching October.

The Red Sox play in the toughest division in baseball. They have some holes in their lineup, particularly a decided lack of juice at the bottom of the order. Their bullpen projects well but is packed with uncertainty. A sure thing was just what they needed. Bregman is just that. Since his 2016 debut, he’s been the 10th-best hitter in baseball according to our measure of WAR. “Oh, but Ben, he’s old, he’s faded, he’s past his prime, no one cares about 2019.” Yeah, well, over the last four years, Bregman has been the 11th-best position player in baseball. So much for a decline phase.
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In the middle of the 2024 season, MLB released bat tracking data for the current year. It was a huge revolution in publicly available data, taking something previously observable but not measurable and turning it into numbers. You can see how hard Giancarlo Stanton swings, but now you can also quantify how different that is from other large hitters. Luis Arraez’s superhuman coordination is obvious from watching him play. But in terms of getting his barrel on the ball, relative to the rest of the league, how superhuman is he? Now we know. I think that public research on this front is likely to deliver more and more insights in the coming years.

Of course, what we all wanted to know about bat speed wasn’t available right away. Namely: How does it change? Was Ronald Acuña Jr.’s disappointing start to the season related to an inability to impact the ball with force? Did Matt Olson’s decline have more to do with bat speed or plate discipline? Also, plenty of non-Braves questions, presumably. In any case, we couldn’t say much about that because all we had were the 2024 numbers.

Guess what: Now we have some 2023 data. MLB and Statcast released 2023 data starting after the All-Star break, the earliest data we’ll ever get because that’s when the bat tracking infrastructure got going. Obviously, we’re also going to get more year-over-year data when the 2025 season starts. But our first crack at multiple seasons of data is still noteworthy, so I set out to look through the numbers and came to a few conclusions. I don’t intend for these to be comprehensive, and I’m sure that a measured and careful approach is going to tease out some new insights that I don’t have. But the data came out yesterday, and here are a few highlights.
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Pulled fly balls, to me, are hitter highlights. Just as strikeouts showcase the nastiness of pitchers, and groundballs allow infielders to demonstrate what they can do, balls in the air promote the powerful sluggers who hit them.

I’m including “pulled” in the description because plenty of research over the past decade has established that pulled fly balls are more productive than their straightaway and opposite-field counterparts. We here at FanGraphs have certainly jumped on that trend. Even if you ignore all my articles about Isaac Paredes, our writing about hitters who either pull the ball a lot or should pull the ball a lot is voluminous.

With that introduction in mind: This article is about pitchers. Bear with me for just a minute, and I’ll explain to you how I got here. It took me a while to wrap my head around why pulled fly balls perform so well. It’s not like the wall is much closer to that side, at least not consistently, and given that both lefties and righties display this trend, that clearly can’t be the thing. But thinking about how it actually feels to swing helped clue me in.

To broadly generalize, hitters make contact with the ball out in front of the plate when they pull it. The angle of the bat starts pointing toward the pull side as soon as it crosses the plane running parallel with the front of home plate. For the most part, because bat speed and “attack angle” — the vertical angle of the bat path — increase throughout a swing, batters tend to hit the ball harder when they catch the ball out in front and put in in the air. As a result, pretty much every hitter produces better on pulled air balls. Read the rest of this entry »

Hello, and welcome to Prospect Week! (Well, closer to Prospect Fortnight — as you can probably tell from the navigation widget above, the fun will continue well into next week, including the launch of our Top 100.) I’m not your regular host – that’d be Eric Longenhagen – but not to worry, you’ll get all the Eric you can handle as he and the team break down all things minor leagues, college baseball, and MLB draft. I’m just here to set the stage, and in support of that goal, I have some research to present on prospect grades and eventual major league equivalency.

When reading coverage of the minor leagues, I often find myself wondering what it all means. The Future Value scale does a great job of capturing the essence of a prospect in a single number, but it doesn’t translate neatly to what you see when you watch a big league game. Craig Edwards previously investigated how prospect grades have translated into surplus value, but I wanted to update things from an on-field value perspective. Rather than look at what it would cost to replace prospect production in free agency, I decided to measure the distribution in potential outcomes at each Future Value tier.

To do that, I first gathered my data. I took our prospect lists from four seasons, 2019-22, and looked at all of the prospects with a grade of 45 FV or higher. I separated them into two groups — hitters and pitchers — then took projections for every player in baseball three years down the line. For example, I paired the 2019 prospect list with 2022 projections and the 2022 prospect list with 2025 projections. In this way, I came up with a future expectation for each player.

I chose to use projections for one key reason: They let us get to an answer more quickly. In Craig’s previous study, he looked at results over the next nine years of major league play. I don’t have that kind of time – I’m trying to use recent prospect grades to get at the way our team analyzes the game today. If I used that methodology, the last year of prospect lists I could use would be 2015, in Kiley McDaniel’s first term as FanGraphs’ prospect analyst.

Another benefit of using projections is that they’re naturally resistant to the sample-size-related issues that always crop up in exercises like this. A few injuries, one weird season, a relatively small prospect cohort, and you could be looking at some strange results. Should we knock a prospect if his playing time got blocked, or if his team gamed his service time? I don’t think so, and projections let us ignore all that. I normalized all batters to a 600 plate appearance projection and all pitchers to a 200 innings pitched projection.

I decided to break future outcomes down into tiers. More specifically, I grouped WAR outcomes as follows. I counted everything below 0.5 WAR per season as a “washout,” including those players who didn’t have major league projections three years later. Given that we project pretty much everyone, that’s mostly players who had either officially retired or never appeared in full-season ball. I graded results between 0.5 and 1.5 WAR as “backup.” I classified seasons between 1.5 and 2.5 WAR as “regular,” as in a major league regular. Finally, 2.5-4 WAR merited an “above average” mark, while 4-plus WAR got a grade of “star.” You could set these breakpoints differently without too much argument from me; they’re just a convenient way of showing the distribution. There’s nothing particularly magical about the cutoff lines, but you have to pick something to display the data, and a simple average of WAR projections probably isn’t right.

With that said, let’s get to the results. My sample included 685 hitters from 45-80 FV. Allowing for some noise at the top end due to small sample size, the distribution looks exactly like you’d hope:

Consider the 55 FV line for an explanation. Of the players we graded as 55 FV prospects, 17% look washed three years later – Jeter Downs, a 2020 55 FV, for example. Another 17% have proven to be backup-caliber, like 2022 55 FV Curtis Mead, or 2019 55 FV Taylor Trammell if you don’t think Mead’s trajectory is set just yet. Continuing down the line, 30% look like big league regulars – 2021 55 FV Alek Thomas, perhaps. A full 31% appear to be above-average major league contributors three years later, like 2019 55 FV Sean Murphy or 2021 55 FV Royce Lewis. Finally, 6% project as stars three years later – Jackson Merrill, a 55 FV in 2022, feels appropriate as an example.

Two things immediately jump out to me when looking at this data. First, the “above average” and “star” columns increase at every tier break, and the “washout” column decreases at every tier break. In other words, the better a player’s grade, the more likely they are to be excellent, while the worse their grade, the more likely they are to bust. That’s a great sign for the reliability of our grades; they’re doing what they purport to do, essentially.

Second, each row feels logically consistent. The 45 FV prospects are most likely to bust, next-most-likely to end up as backups, and so on. The 45+ FVs look like the 45 FVs, only with a better top end; their chances of ending up above average are meaningfully better. The 50 FVs are a grab bag; their outcomes vary widely, and plenty of those outcomes involve being a viable major leaguer. By the time you hit the 55 and 60 FV prospects, you’re looking at players who end up as above-average contributors a lot of the time. The gap between 55 and 60 seems clear, too; the 60 FVs are far more likely to turn into stars, more or less. Finally, there are only six data points above 60 FV, so that’s mostly a stab in the dark.

This outcome pleases me greatly. Looking at that chart correlates strongly with how I already perceived the grades. For a refresher, roughly 30 prospects in a given year grade out as a 55 FV or above, give or take a few. Something like three quarters of those tend to be hitters. That means that in a given year, 20-ish prospects look like good bets to deliver average-regular-or-better performance. The rest of the Top 100? They’re riskier, with a greater chance of ending up in a part-time role and a meaningfully lower chance of becoming a star. But don’t mistake likelihood for certainty – plenty of 55 and 60 FVs still end up at or below replacement level, and 45 FVs turn into stars sometimes. Projecting prospect performance is hard!

How should you use this table? I like to think of Future Value in terms of outcome distributions, and I think that this does a good job of it. Should a team prefer to receive two 50 FV prospects in a trade, or a 55 FV and a 45 FV? You can add up the outcome distributions and get an idea of what each combination of prospects looks like. Here are the summed probabilities of those two groups:

Another way of saying that: If you go with the two-player package that has the 55 and 45 FV prospects, you’re looking at a higher chance of developing a star. You’re also looking at a greater chance of ending up with at least one complete miss, and therefore lower odds of ending up with two contributors. Adding isn’t exactly the right way to handle this, but it’s a good shorthand for quick comparisons. If you want to get more in depth, I built this little calculator, which lets you answer a simple question: For a given set of prospects, what are the odds of ending up with at least X major leaguers of Y quality or better? You can make a copy of this sheet, define X and Y for yourself, and get an answer. In our case, the odds of ending up with at least one above-average player (or better) are 40.7% for the two 50s and 41.4% for the 45/55 split. The odds of ending up with two players who are at least big league regulars? That’d be 28.1% for the two 50 FVs, and 16.1% for the 45/55 pairing. Odds of at least one star? That’s 4% for the two 50 FVs and 6% for the 45/55 group. In other words, the total value is similar, but the shape is meaningfully different.

For example, you’d have to add together a ton of 50 FV prospects to get as high of a chance of finding a star as you would from one 60 FV. On the other hand, if you have three 50 FVs, the odds of ending up with at least a solid contributor are quite high. Meanwhile, even 60 FV prospects end up as backups or worse around a quarter of the time. That description of the relative risks and rewards makes more sense to me than converting players into some nebulous surplus value. Prospects are all about possibility, so representing them that way tracks analytically for me.

Take another look at the beautiful cascade of probabilities in that table of outcomes for hitting prospects, because we’re about to get meaningfully less pretty. Let’s talk about pitching prospects. Here, the outcomes are less predictable:

I have tons of takeaways here. First, there are substantially fewer pitching prospects ranked, particularly as 50 FVs and above. Clearly, that’s a good decision by the prospect team, because even the highest-ranked pitchers turn into backups at a reasonable clip. Pitching prospects just turn into major league pitchers in a less predictable way, or so it would appear from the data.

Second, there are fewer stars among the pitchers than the hitters. That’s true if you look at 2025 projections, too. There are only six pitchers projected for 4 WAR or higher, while 42 hitters meet that cutoff. It’s also true if you look at the results on the field in 2024; 36 hitters and 12 pitchers (22 by RA9-WAR) eclipsed the four-win mark. You should feel free to apply some modifiers to your view of pitcher value if you think that WAR treats them differently than hitters, but within the framework, the relative paucity of truly outstanding outcomes is noticeable.

Another thing worth mentioning here is that pitchers don’t develop the same way that hitters do. Sometimes one new pitch or an offseason of velocity training leads to a sudden change in talent level in a way that just doesn’t happen as frequently with hitters. Tarik Skubal was unmemorable in his major league debut (29 starts, with a 4.34 ERA and 5.09 FIP). Then he made just 36 (very good) starts over the next two years due to injuries. Then he was the best pitcher in baseball in 2024. Good luck projecting that trajectory. Perhaps three-year-out windows of pitcher performance just aren’t enough thanks to the way they continue to develop even after reaching the majors.

There’s one other limitation of measuring pitchers this way: I don’t have a good method for dealing with the differential between reliever and starter valuation. Normalizing relievers to 200 innings pitched doesn’t make a ton of sense, but handling them on their own also feels strange, and I don’t have a good way of converting reliever WAR to the backup/regular/star scale that I’m using here. A 3-WAR reliever wouldn’t be an above-average player, they’d be the best reliever in baseball. I settled for putting them up to 200 innings and letting that over-allocaiton of playing time handle the different measures of success. For example, a reliever projected for 3.6 WAR in 200 innings would check in around 1.2 for a full season of bullpen work. That’s a very good relief pitcher projection; only 20 players meet that bar in our 2025 Depth Charts projections.

In other words, the tier names still mostly work for relievers, but you should apply your own relative positional value adjustments just like normal. A star reliever is less valuable than a star outfielder. A star starting pitcher might be more valuable than a star outfielder, depending on the degree of luminosity, but that one’s much closer. This outcome table can guide you in terms of what a player might turn into. It can’t tell you how to value each of those outcomes, because that’s context-specific and open to interpretation.

This study isn’t meant to be the definitive word on what prospects are “worth.” Grades aren’t innate things, they’re just our team’s best attempt at capturing the relative upside and risk of yet-to-debut players. Being a 60 FV prospect doesn’t make you 17% likely to turn into a star; rather, our team is trying to identify players with s relatively good chance of stardom by throwing a big FV on them. And teams aren’t beholden to our grades, either. They might have better (or worse!) internal prospect evaluation systems.

With those caveats in mind, I still find this extremely useful in my own consumption of minor league content. The usual language you hear when people discuss prospect trades – are they on a Top 100, where do they rank on a team list, what grade are they – can feel arcane, impenetrable even. Breaking it down in terms of likelihood of outcome just works better for me, and I hope that it also provides valuable information to you when you’re reading the team’s excellent breakdown of all things prospect-related this week.

Major league job boards don’t exist, at least not for players. You can’t walk past some mythical player’s union clubhouse, see a sign that says “Team seeking middle reliever, please tear off a number and call it to apply,” and find a job that way. The team calls you, or emails your agent, and they do that after working up their own list of targets independently. Or at least, that’s what they tell us. But after seeing the Minnesota Twins acquire the same type of player for the third year running, as they did in signing Harrison Bader to a one-year deal this week, I’m not so sure.

Bader’s deal is for one year and $6.25 million, with bonuses that could kick in another $2 million. That’s a reasonable deal for a quality backup, and that’s exactly what Bader looks like. He’s put up between 300 and 450 plate appearances in six of the past seven seasons – the only year he missed that mark was in the COVID-shortened 2020 campaign. At first, that was because he couldn’t stay on the field, but in recent years, he’s turned into a defensive specialist and righty platoon bat.

How much do the Twins like those two roles? Well, in 2023, they traded for Michael A. Taylor, a defensive specialist and righty platoon bat, and then gave him 110 starts in center field. Sure, they had Byron Buxton, but that year Buxton never took the field, all the better to protect him from injuries. Taylor was so good that he got a new deal in free agency to head to Pittsburgh – so the Twins went out and traded for Manuel Margot, a “defensive specialist” and righty platoon bat. Read the rest of this entry »

Today, we released the first run of our playoff odds for the 2025 season. With both the ZiPS and Steamer projections loaded in and playing time projections added to the mix, the FanGraphs supercomputer (okay, fine, our cloud services account) can get cranking and spit out some predictions. As is customary, I’ll walk through my first thoughts on them, while later today, Michael Baumann will contribute his own takeaways on the teams most likely to surprise our model. Let’s quickly walk through the process, and then get to the takeaways.

The model itself remains simple. We use those aggregated production and playing time numbers I mentioned earlier to create team-level projections, then use BaseRuns to turn individual outcome projections into scoring and run prevention. That gives us team strength against a neutral opponent. We use those values to simulate the season 20,000 times. The odds are a summary of those simulations as of earlier this morning. That might sound intuitive, but intuition doesn’t always match reality, so let’s go division-by-division to look at how our model got there and what I think of it. Read the rest of this entry »

If you had to associate a single current major leaguer with throwing sinkers, Framber Valdez would be toward the top of the list. His standout career is all about throwing sinkers and keeping the ball on the ground. So imagine my surprise when I was perusing a leaderboard of starters who used their secondaries most frequently with two strikes in 2024. The top of that list is dotted with pitchers who confounded my classification system: We’ve got Corbin Burnes, Graham Ashcraft, and Clarke Schmidt there representing the cutter brigade. Most of the other pitchers in the top 10 mix in cutters liberally with two strikes. Then we’ve got Valdez, in 10th and looking sorely out of place.

Train your eyes on Valdez, and you’ll start to ask yourself: What’s going on here? In some ways, his statistics are consistent to the point of monotony. Take a look at his strikeout and walk rates over the years, plus some league-adjusted run prevention numbers:

After some early-career wildness, Valdez has produced a string of near-identical seasons. But while doing that, he’s cut back on using his sinker to finish off hitters. I know what you’re thinking: Sure, to throw his wipeout curveball. But nope! It’s a changeup story:

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Ketel Marte was one of the best 10 hitters in baseball in 2024. That’s just an objective fact – or at least as objective as facts can get in baseball. Our calculation of WAR? He was 10th among hitters. Baseball Reference has him 10th as well. Baseball Prospectus put him in seventh place. That’s not surprising; he set career highs in home runs, league-adjusted OBP and slugging, and wRC+. He played solid defense and even added a little value on the basepaths.

He was one of the best 10 hitters in baseball in 2019, too. In fact, he’s the only player to crack the top 10 in both 2019 and 2024. That’s wild. Aaron Judge, Mookie Betts, Shohei Ohtani, Corey Seager, Juan Soto, Bryce Harper, José Ramírez – they all played in both years. None of them – none! – managed the double that Marte did. This isn’t some weird defensive value issue, either: He’s the only hitter with a top-10 wRC+ in both years.

Those in between years? Don’t look too closely. Marte totaled 9.1 WAR across the 2020-2023 campaigns. He posted 6.3 WAR in each of 2019 and 2024. In that 2020-2023 span, he was 64th among hitters in total WAR. He had two seasons of roughly average offensive production in that span, and produced at a 3 WAR/600 pace instead of the 6.3 WAR/600 pace from 2019 and 2024. So it’s safe to say he’s streaky – one hitter some years, and a different guy other years. Read the rest of this entry »

It’s been a quiet winter in the AL Central. After Michael Wacha signed an extension at the beginning of the offseason, the division’s five teams combined to add only one deal worth more than $20 million in guaranteed money; that was Shane Bieber’s surgery-affected pillow contract with the Guardians. Now, finally, we can add another to the ledger, courtesy of the Royals. On Wednesday, they signed Carlos Estévez to a two-year, $22.2 million deal with a club option tacked on the end, as ESPN’s Jeff Passan first reported.

The Royals came into the winter looking for relief help. It’s not the only place their roster needed a glow-up – even after trading for Jonathan India, they could still use another bat or two, especially in the corner outfield – but the bullpen was also a particular area of need. Last year’s Royals made the playoffs on the back of pitching, but their starters were the ones doing the heavy lifting, not their relievers. Deadline acquisition Lucas Erceg was the best of the group by a large margin, and John Schreiber was the only other reliever with impressive full-season numbers.

It’s not so much that a team can’t make the playoffs with such a thin bullpen – obviously, the Royals did. But they did it by the skin of their teeth at 86-76, and that despite spectacular seasons from Cole Ragans, Seth Lugo, and Wacha. Counting on those three to combine for 94 starts, 12.9 WAR, and ERAs in the low 3.00s across the board again would be wishful thinking. Additionally, they no longer have last year’s fourth starter Brady Singer, who was Cincinnati’s return in the India trade.

The 2024 bullpen finished last in baseball in shutdowns – appearances that increased win probability by six percentage points or more – and fifth worst in win probability added. Those are outcome statistics, not process ones, but the process statistics weren’t exactly pretty either. Kansas City was middle of the pack in WAR (3.6), 20th in ERA (4.13), 26th in K-BB% (12.0%). It’s not just that this team didn’t have a “true closer” – its bullpen was light on contributors from top to bottom. Read the rest of this entry »