If you just glanced at his player page for a second, you might think Lucas Giolito was falling apart. After a triumphant first half, during which he paired a 30% strikeout rate with a 9.5% walk rate on his way to a 3.15 ERA and 3.23 FIP, he made the All-Star team. And this was no automatic invite extended to the best available White Sox player; he was simply one of the best pitchers in baseball, running comparable park-adjusted numbers to Stephen Strasburg, Walker Buehler, and Zack Greinke.

From that great height, Giolito’s second half has had a rocky beginning. In three post-break starts, he’s compiled a 5.6 ERA, with a FIP over five. A lot of that ugliness is driven by a pasting at the hands of the Twins, when he allowed four home runs and seven runs over five innings, but it’s not as though there weren’t other warning signs. In his last pre-break start, he went only four innings against the Cubs, walking five batters on his way to giving up six earned runs. All told, it was a beyond-forgettable July for Giolito.

Situations like this are among the most difficult for writers to assess. Pitchers are fickle, and there’s no better example of that than Giolito. In parts of three seasons from 2016 to 2018, he was below replacement level, whether you’re into runs allowed or FIP; over 240 innings, he ran a 5.48 ERA and 5.68 FIP. He only struck out 16.2% of batters he faced while walking 11%. He still had some prospect shine, but projection systems weren’t buying it: ZiPS projected him for a 5.03 ERA in a lower-scoring environment than what we’ve realized in 2019, while Steamer foresaw an even higher 5.32 ERA.

Of course, Giolito proceeded to make those projections look ridiculous. Through 16 starts, roughly the first half of his season, he pitched nothing at all like the projections. That 30% strikeout rate was nearly double what the two projection systems expected, and his walk rate was significantly lower — you get the idea. Essentially, Giolito looked like an ace. If there was cause for concern, it was unsustainable home run suppression — he’d allowed a 9.7% HR/FB rate in the first half, and for a fly ball pitcher, that adds up. The point, though, is that Giolito went from replacement-level disappointment to deserving All-Star. Read the rest of this entry »

Recently, I’ve been pondering the strange way I think about HR/FB ratio. On one hand, it’s a way to explain away a hot or cold stretch from a hitter. When Joc Pederson got off to a blazing start this year, I looked at his HR/FB, a spicy 33.3% through the end of April, and told myself it was a small sample size phenomena. That’s the first way I use HR/FB for hitters — as a sanity check.

At the same time, HR/FB is something we’ve all used to explain someone’s power. Joey Gallo is powerful, obviously. How do we know that? Well, he hits the ball really hard, which gets expressed by more of his fly balls turning into home runs. Gallo had a 47.6% HR/FB at the end of April, and even though I didn’t expect that to continue, I was willing to accept high numbers for Gallo’s HR/FB much more easily than I was for Pederson.

This leaves HR/FB in a weird spot. It’s a number we use to see if players are getting lucky or unlucky relative to average, but it’s also a number we use to look for underlying skill. Problems arise when it’s unclear what is noise and what is signal. Is David Fletcher unlucky to have a 5.4% HR/FB? Surely not — he’s a contact hitter. Is Jose Ramirez unlucky to have a 6.5% HR/FB? I assume so, but I only assume so because he hit 39 home runs with a 16.9% HR/FB last year. What if last year was the outlier, not this one?

Another way to think about this conundrum is that HR/FB contains an inherent contradiction we have to work around mentally. Putting fly balls as the bottom of the ratio implies that all fly balls are created equal, and that’s clearly untrue. Gallo is unloading on the ball, crushing many of the fly balls he hits into orbit. Fletcher, meanwhile, sports one of the lowest average exit velocities in the game. Even though a home run counts the same for each, the population of fly balls is tremendously different. How do we handle this contradiction? Read the rest of this entry »

Watch a baseball game. Pick a side. Now, wait for a pitcher on the team you’re rooting for to fall behind in the count 3-0. It feels pretty bad, doesn’t it? There is, I think, no feeling quite like the helplessness that comes when your team is behind in the count 3-0. There are worse feelings, sure, even within the confines of baseball. There’s the feeling of losing a close game, coughing up a lead, or seeing a favorite player injured. Nothing is quite the same, though, as the long dread of trying to escape from 3-0.

Why does 3-0 feel so uneasy? I think it’s because there are no good quick ways out of the jam. You feel nervous, and you’re going to feel nervous for a while. Next pitch a ball? That’s disappointing for obvious reasons, but at least the tension is over. No, the real problem is that a strike doesn’t feel much better than a ball. So what are you hoping for? You certainly don’t want a swing — swings on 3-0 are tremendous for the batter.

Do you want a take, then? The pitcher grooves a fastball, and the batter watches it fly by? Sure, that’s probably the best outcome you can hope for in the situation, but that’s small consolation. Get a strike, and it’s still 3-1; time for another 30 seconds of watching your team in a tough situation. Even then, what are you hoping for? Batters are producing a .475 wOBA after 3-1 counts this year, better offensive production than any player in baseball’s overall line.

Even if, and this is a huge if, your team gets two straight strikes — now it’s 3-2. This is after a nerve-wracking minute of real time, potentially involving some loud foul contact. You’ve worried about walks for two straight pitches, wondered if the pitcher has it today, and still — 3-2 is a hitter’s count. At the beginning of the at-bat, if I told you it was headed for a 3-2 count, you wouldn’t have been happy. That’s the best case scenario after you reach 3-0. No wonder 3-0 feels so bad. Read the rest of this entry »

Last week, FanGraphs wrapped up our annual Trade Value Series. As a window into teams’ valuation of players, it’s an invaluable resource, built as it is from a mixture of industry sources. One thing it isn’t, though, is a list of players we realistically expect to be traded. The top 10 players on the list, for example, have an average of six years of team control remaining, and all of them except Vladimir Guerrero Jr. play for teams that are currently contending. They’re great theoretical trade pieces, in other words, but not likely to actually be traded.

That conundrum, the fact that the most valuable players are among the least likely to be traded, has always been a feature of the exercise. Mike Trout topped the list for five straight years at one point, for example, and was quite literally too valuable for teams to be able to acquire, even if the Angels had been willing to deal him. Evan Longoria, likewise, was a repeat Trade Value champion, but his first extension with the Rays made him so valuable to the team that they couldn’t even contemplate moving him.

Most of the time, then, the Trade Value Series is more of a Theoretical Value Series. Most isn’t all, however, and that’s where this article comes in. One of the benefits of having 12 years of trade values is that we can look at things that don’t happen all that often. If only 1% of top-50 players get traded, we should still have six results in our sample. With the benefit of aggregation, then, let’s take a look at how often the trade in trade value comes into play.

The first question you probably have is how often a player on the Trade Value list gets traded at all. The answer to that is tricky. For example, here are the number of Top-50 and honorable mention players traded within the next year after appearing on a FanGraphs Trade Value list:

Read the rest of this entry »

Here’s a sentence that I didn’t think I’d be writing in 2019: Andrew Miller has accumulated -0.2 WAR this season. By FanGraphs’ version of WAR, he’s been less valuable than a replacement-level reliever. Here’s another sentence that makes a little more sense, but is at odds with the one I just wrote: Andrew Miller might be the Cardinals’ best reliever. Now, reliever performance is volatile and all, but we’re going to need an explanation. How can those two things be true at once?

Let’s start with Miller being below replacement level, because that would have been a surprising assertion before the year. Andrew Miller has faced 139 batters this season. He’s allowed eight home runs. 6% of his plate appearances have ended with the opposing batter trotting around the bases. That surely already sounds like a ton — indeed, Miller is second in the majors in home runs allowed per nine innings, behind only Josh Osich. You don’t need a sabermetric writer to tell you that’s bad.

As bad as 2.2 home runs per nine innings sounds, though, it might be underselling how wild Miller’s season has been on the home run front. Josh Osich is a great example of the kind of pitcher who normally leads the league in home runs allowed per nine. He’s a pitch-to-contact depth reliever who works by letting opponents put the ball in play and counting on his defense to make plays behind him. Now, that strategy mostly hasn’t worked — Osich has a career ERA of 5.11, and his FIP is 5.31, so it’s not as though he’s just been getting unlucky. Still, while Osich is homer-prone, he’s mostly just contact-prone, with the home runs a cost of doing business. Strike out only 19% of the batters you face, and there will be plenty of opportunities to give up home runs.

Andrew Miller’s case of the dingers isn’t like that at all. Miller is actually one of the least contact-prone pitchers in all of baseball this year. Only 51% of the batters he has faced have put the ball in play. That severely limits the opportunities they have to hit home runs. Osich, for comparison’s sake, has let 75% of batters put the ball in play. Miller is giving up home runs at a truly alarming rate considering how few opportunities he gives batters to put a ball in play. Read the rest of this entry »

The list of batters who go down in the count 0-1 least often mostly makes sense. Mike Trout and Cody Bellinger are in the top five, due to a combination of their sterling batting eyes and pitchers staying away from them. Justin Smoak, Mike Moustakas, and Anthony Rizzo comprise the rest of the top five, and even if they don’t quite have the fearsome power of Bellinger and Trout, they have enough power that pitchers often pitch them carefully. Smoak has the lowest ISO of the five at .205. Pitchers are being rationally cautious.

Number six on the list will make you question what you think you know about first strike rate. David Fletcher, the Angels infielder, is number six, and he couldn’t look any more different than the guys ahead of him. I don’t mean physically, though that’s true as well — at 5-foot-10 and 175 pounds, Fletcher isn’t an imposing power presence. No, what I mean is that Fletcher plays baseball in a style that can best be described as a throwback. Not only that, he’s succeeding, putting together a second consecutive solid major league season despite a game that would look more at home in the 1980s than in 2019.

If Tyler O’Neill is one extreme of the game, David Fletcher is the other. Think of a stereotype about baseball in 2019, and Fletcher probably defies it. Strikeout rates inexorably on the rise? Fletcher is striking out 8.3% of the time this year, the lowest rate among qualified hitters. Big swings and big whiffs? Fletcher makes contact on a dizzying 92.1% of his swings. The world gone mad for home runs and power? Fletcher’s .126 ISO is 12th-lowest in baseball this year, and that comes largely from his 20 doubles; he hits home runs on 5.6% of his fly balls, the sixth-lowest rate in the majors.

It’s easy to read the headlines in 2019, to see Pete Alonso hitting balls to Andromeda and Christian Yelich crushing home runs on nearly a third of his fly balls, and think that the only way to succeed in baseball is via home runs. There’s some truth to that, honestly — as pitchers throw harder and harder, stringing together a series of hits gets increasingly challenging, and a home run lets the offense skip all of that. That’s not a rule, though — it’s merely the path of least resistance. Read the rest of this entry »

On an extremely superficial level, Tyler O’Neill looks like any other high-level prospect bouncing between the minors and the majors. After posting a 107 wRC+ in his first shot at Triple-A in 2017, he’s been excellent there over the past two years, putting up a combined 143 wRC+ in 427 PA. He’s been above-average in parts of two seasons in the majors — a 121 wRC+ over 232 PA. If the Cardinals didn’t have such an outfield logjam, he might have earned more major league playing time; indeed, the team traded Tommy Pham last summer in an attempt to find more plate appearances for O’Neill and Harrison Bader.

Look even slightly closer, though, and the narrative of O’Neill as average baseball player falls apart. Here is O’Neill, after his teammates tore off his jersey and undershirt following a walk-off home run. Even through the water droplets on the camera lens, his bulk is obvious:

How average can someone with biceps the size of most human beings’ legs be? Read the rest of this entry »

Ronald Acuña had Steve Cishek right where he wanted him. He had worked the count to 3-0, and with a man on first base, Cishek was in a tough situation. The Cubs led by only two, and that put Cishek in quite the bind. Walk Acuña, and the tying run would be aboard with no one out. Give him a pitch to hit, and the game could be tied in a single swing. Acuña waited, Cishek dealt, and the result:

Cishek, no doubt, made the exact pitch he was hoping for. Still, it was a tremendously aggressive swing from Acuña, at a pitch that he couldn’t do much with. No real harm done — Acuña walked on the very next pitch. Cishek, as it turns out, was wild that day — he’d walked Freddie Freeman before Acuña, and he walked Nick Markakis after him to load the bases. All three scored, and the Braves won. Still, what was Acuña doing swinging there? Cishek had thrown seven straight balls to start the inning. The Braves weren’t punished for Acuña’s aggression, but the swing seemed a bit out of place. Read the rest of this entry »

One of the most significant stories of the past few years of baseball has been the changing composition of the baseball. I mean story in the grand narrative sense, but I also mean it in the sense of literal stories. The slice-open-a-baseball-and-catalog-its-contents article has gotten very popular over the last few years, as have studies of drag and bounciness. Physics is having a moment in baseball analysis.

One of the frustrating parts of breaking down the new ball’s effect on offense is that there was no clean way to isolate which hitters were helped most. Many batters adapted their swings to the new ball as the ball kept changing. The ball undoubtedly led to more home runs, as an independent panel reported in 2018. Which batters, though, were the biggest beneficiaries of the new ball? The launch angle revolution might increase batters’ home run rates, but surely a lot of its popularity comes down to the fact that home runs started flying out of the park at elevated rates as the ball changed. Separating cause from effect as swings and baseballs change over years’ worth of games is difficult. Our own Jeff Sullivan took a shot at it in 2016, but didn’t find much evidence for one group over another.

Luckily, this season provides a convenient, natural experiment. To much fanfare, Triple-A switched over to using the major league ball this year. Home runs predictably skyrocketed, driven by the new ball. This creates an opportunity for all kinds of research, such as this attempt by Baseball America to test out whether the ball changes fastball velocity. I thought I’d take the occasion of this new ball to investigate something I’ve always wanted to know about the home run surge: what types of hitters does the new ball help most? Read the rest of this entry »

I’ve been on something of a fastballs-down-the-middle kick recently. I hadn’t realized that it was possible to be so bad at hitting them until I looked into Wil Myers and his flailing ways. Then I started looking at a few underperforming hitters, and I was shocked by how many batters were missing middle-middle fastballs. Pitchers are throwing fastballs less often than ever before, and they’re designing new breaking balls every offseason. Meanwhile, some batters can’t handle a straight pitch in the center of the hitting zone. Baseball is weird sometimes!

Looking into these center-cut whiffs was baffling. There were a decent number of Jacob deGrom and Chris Sale fastballs on there, sure, but there were also plenty of replacement level relievers. Does the pitcher even have anything to do with it? Sure, Clayton Kershaw used to be great at throwing down the middle, but he’s thrown 96 pitches over the heart of the plate this year and gotten a paltry four swinging strikes. Aroldis Chapman excelled at it in 2016, but he’s thrown 43 of them this year and gotten only five swinging strikes. What if it’s a batter-centric phenomenon? Could it just be that batters sometimes miss because baseball is hard, regardless of pitcher?

Ha, no. Silly Ben. If you watched the 2018 playoffs, you’d already know: Josh Hader is the absolute king of throwing down the middle and coming out unscathed, and it’s not even close. Hader’s fastball is a magic trick, a sleight of hand performed on batters. In your head, he’s probably getting all his strikeouts at the very top of the strike zone or even a little above that, getting hitters to swing at pitches they can’t do anything with. That’s true, of course, but he’s also beating hitters when he messes up. Read the rest of this entry »