Hey there, and welcome to the last edition of my data-driven look at some mid-tier hitting prospects I like more than the industry consensus. It feels weird, almost funereal, to start this article by mentioning that the series is ending, but that’s just how it is. This will be the fourth installment of my variably named Prospect Week contribution. In it, I use data and a big pinch of intuition to point out some hitters who I think have a good chance of sticking in the majors, even if they’re not your average Top 100 type.

In the past, I’ve done acceptably well at this; I don’t think it’d be fair to say that I’m great at it, but I’ve come up with my fair share of interesting players using this process. In looking through my past lists, I feel good about the process that led me to some guys you’ve heard of (Miguel Vargas and Ezequiel Tovar are probably my biggest hits so far, but I’ve also gotten some role players, and both Gabriel Moreno and Alejandro Kirk performed incredibly well by my model, though I didn’t end up including them in a list thanks to their pedigree) and plenty you haven’t.

What’s so hard about this project? The obvious thing is that my methods are archaic. I’m using some sorting techniques that are still reasonably current. K-nearest neighbors and multiple binary logistic regressions are still my two favorite techniques, and I think they both still do what I want them to. These approaches aren’t state of the art in statistical analysis, but they’re not particularly far from it, especially when you take into account that I’m a baseball writer instead of a data scientist. Read the rest of this entry »

A few articles ago, I was engaging in one of my favorite pastimes: making up the names of non-existent statistics. What can I say? I got into writing because I like lining words up in funny ways. I got into baseball writing because I love baseball. But when the two things I like line up, then we’re really cooking with gas.

The fake statistic in question? Whomps per whiff. You can grasp what it is right away: how often you absolutely whomp the ball, as compared to how often your swing results in nothing but a tiny gust of air and perhaps an emphatic umpire reaction. Is this a predictive statistic? I have no idea whatsoever, but I thought I’d try to see who’s good at it.

The good news: The good players are good. I defined a whomp as a barrel, a whiff as a whiff, and then limited it to players who saw at least 500 pitches in 2023. The best in baseball at it? Ronald Acuña Jr., who just put up an all-time offensive season. Neat! Second best? Mookie Betts, who finished second in MVP voting behind Acuña. Maybe we’re on to something here. Here’s the top 10 by that metric:

One thing that I love about this statistic is that it isn’t secretly ranking players based on their plate discipline. Betts doesn’t swing much, so he doesn’t whiff much. Seager is aggressive but selectively so. Luis Arraez is 12th. Lars Nootbaar is 13th. Those two are polar opposites who nonetheless are both good hitters.
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I thought that today’s article was going to be an easy one to write. Reading Alex Chamberlain’s post on the pulled fly ball revolution made me imagine the worst pitch a pitcher could throw: a sinker that ended up high and inside, an easy-to-contact fastball in the area of the plate that leads to the most damaging types of opposing batted balls. Then I extrapolated my idea out a little bit. Maybe I could look up the pitchers who throw their sinkers high in the zone most often. We could all laugh about how they’re called “sinkers” — so that’s clearly a bad place to throw them. Maybe we would gawk at a table of a few pitchers who do this bad thing, and then we could move on with life.

Well, I can do at least one thing. Here’s a table of the pitchers who threw elevated sinkers in or around the strike zone most frequently in 2023:

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I don’t think I’m alone in my fascination with pulled fly balls. In fact, I know I’m not, because Alex Chamberlain wrote about them today too. These days, we’re practically drowning in data: exit velocities, launch angles, chase rates, aggression rates — the list goes on and on. There are so many different ways of thinking about exit velocity that you can read an entire great article about what they all mean. If you want to translate how hard someone hits the ball into how they’re likely to perform, there’s no shortage of instructive articles. But in that deluge of data, horizontal angle has been left out, for reasons both purposeful and accidental, and the unavailable is always interesting.

Earlier this month, I did some idle digging into what pull rate means for production on contact. The takeaway was, to be generous, middling. It seems like pulling your aerial contact results in better overall production on that contact, but the effect isn’t huge. Perhaps the more interesting takeaway was that xwOBA on these batted balls had a bias: the more pull-happy the hitter, the lower their xwOBA was on the balls they hit in the air. That was the case despite greater overall production on those balls.

That’s a weird little artifact, though I didn’t think too much of it because I kind of knew what it would say in advance. Every time I look at a dead pull fly ball hitter, they’re getting home runs out of batted balls that xwOBA hates. But that doesn’t mean the statistic is working incorrectly; it’s doing exactly what it says on the label by bucketing batted balls based on exit velocity and launch angle. Read the rest of this entry »

Few positions on the Brewers depth chart are more set than catcher. William Contreras, whom they acquired before last season, was their best player in 2023. He led Milwaukee in hitting and finished third on the team in plate appearances despite shouldering a full-time catching load, which normally limits playing time. Most impressively, he delivered a sensational defensive performance a year after he was one of the worst receivers in baseball. On a team that struggled to generate offense, Contreras was a rare and brightly shining exception.

Naturally, the Brewers just signed the best free agent catcher on the market, give or take DH Mitch Garver. That’d be Gary Sánchez, who is joining the team on a one-year, $7 million contract, as Jon Heyman reported. It sounds bizarre – and it may well be bizarre. But there’s a method to Milwaukee’s madness, so let’s try to figure it out together.

There’s one obvious thing going for the Brewers: They really needed a second catcher. Before they signed Sánchez, the plan was to use Eric Haase, he of the 42 wRC+ in 2023, as their second backstop. That plan was not great, to put it succinctly. Haase probably isn’t that bad offensively, but he’s also not particularly good behind the plate. In his best years in Detroit – he hit a career-high 22 home runs in 2021 and topped out at 1.3 WAR in 351 plate appearances the following season – he wasn’t used as a pure catcher, dabbling in the outfield and at DH and racking up meaningfully negative framing numbers when he did don the tools of ignorance.
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Hey there, FanGraphs reader. Great news! Our playoff odds just went up for the 2024 season. These odds, as always, are mostly enlightening, but also a tiny bit mystifying. The model itself remains simple: We take projections for each player, aggregate them up to the team level based on playing time projections, and then use that to create expected team run scoring and prevention numbers. From there, we simulate out the season 20,000 times and note what happened in each instance. The odds are just a summary of those simulations.

As simple as the process is, it’s also inscrutable. How good are the projections? We think they’re very good, as they’re a combination of ZiPS and Steamer. But those projections inevitably differ from people’s perceptions of both individual players and teams. So in what’s become an annual tradition, I’m going to give you a guided tour through the projections and point out the notable points in each division, then explain how our model got there and what I think of it. Read the rest of this entry »

You’ve seen this movie a million times. The Rays make some innocuous transaction, adding a reliever you’ve heard of but perhaps forgotten about in trade or free agency. You remember that guy – but now? Him? Surely they can’t be serious. But of course, they are serious, and it ends up working out better than anyone expected, and next thing you know that guy is getting key outs against great hitters.

You might think the team’s most recent reliever transaction fits both parts of this trope: an obscure(ish) pitcher who will no doubt become good. But you’d only be half right about Phil Maton, who has reportedly agreed to a one-year deal for $6.5 million, with a $7.5 million team option for 2025, per Mark Feinsand and Robert Murray. A physical is still pending, and the contract isn’t expected to become official until next week, per Marc Topkin. Will Maton lock down key innings for Tampa Bay this year? I’d bet on it. But where you’d go wrong is in thinking that Maton came to the Rays to get better. While you weren’t looking, he’s already become a great reliever, and the Rays are in fact engaging in another of their favorite offseason pastimes: seeing a great performance before the rest of the league and capitalizing.

I can hear your skepticism, and that’s perfectly okay. Phil Maton is a great reliever? How come our Depth Charts project him for a 4.10 ERA next year? How come his best season produced a 3.00 ERA and peripherals on either side of four? How come he signed this deal in February? Am I thinking, perhaps, of a different Phil Maton? Read the rest of this entry »

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As I write this, I’m in a fair amount of discomfort. I went to the dentist’s office for a routine filling and next thing you know, bam, root canal. I’m a little out of it, is the point, and in my dental chair daze, I did what everyone probably does when they’re upside down with blood rushing to their head for a long time: I started musing about Isaac Paredes.

Oh, I hear you. This isn’t what normal people do when they’re discombobulated, not even a little bit. To that I say, you’re not wrong. Also, though, I’m not a normal person. This is my job, and daydreaming about work is inevitable, not weird. In any case, I came up with an incredible idea, a way to work out the next Paredes before teams did. I was a genius. Here’s the bad news, though: I don’t really remember it now that I’m lucid again.

That’s a bummer, but it’s OK, because in trying to reconstruct my thoughts, I think I came up with a pretty cool way of contextualizing how much it pays to sell out for pulled contact. As an added bonus, I got to pore over a ton of data and play with it to my heart’s content. That’s the dream, coming up with some silly junk stat in a haze and then spending hours manipulating data to show that it’s worthwhile.
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