When I sat down to watch last night’s game between the Dodgers and the Padres, I was ready for some offense. The Padres jammed their lineup with righties against Julio Urías, and while the Dodgers didn’t do anything special on their side to face Chris Paddack, they’re pretty much always terrifying. But I absolutely didn’t expect what happened, an 11-2 rout complete with a three-homer game from Mookie Betts.
The game was an impressive show of force from the Dodgers. Those are almost a foregone conclusion with such a potent lineup, even against Paddack — you can’t keep this group from the occasional offensive eruption. What impressed me most, however, was Betts’ first home run of the day. Take a look:
Mookie would hit a homer on the night he got his Silver Slugger. pic.twitter.com/bdBFAWvApw
— MLB (@MLB) August 14, 2020
Mookie would hit a homer on the night he got his Silver Slugger. pic.twitter.com/bdBFAWvApw
— MLB (@MLB) August 14, 2020
Paddack would have been pleased with that pitch if he didn’t know the result. Betts is a judicious first-pitch swinger, so you can’t throw him something uncompetitive and expect to get a strike. At the same time, he’s Mookie Betts; you can’t toss a fastball down Main Street and expect to get out of it alive. Paddack chose an excellent compromise, just off the outside corner but close enough to draw a swing. He might have preferred it a few inches higher, but it was a good idea for a first pitch.
Read the rest of this entry »
It’s always important to remember that statistics can lie. They’re interesting, and if used with caution they can reveal all kinds of truths. Most statistics are silly, though. When we mock old guard baseball minds who quote eight-plate-appearance samples of one batter against a particular pitcher, or what Mike Moustakas has done in home day games this year, it’s implied: those statistics don’t tell you anything meaningful. So here’s what we’ll do today: I’m going to tell you a statistic, and then we’ll try to find out if it’s meaningful.
Carlos Santana has walked in 30.4% of his plate appearances this year. If you hear that and think “Wow, that’s a lot of walks,” you’re absolutely correct. Santana has always walked a lot, but not like this. Walking that often hardly looks like baseball. It lets him run a ludicrous, .182/.430/.255 slash line. The question is, does it mean anything?
Here’s a simplistic way of looking at it: Santana has batted a lot of times in the major leagues. He’s up to 6,226 plate appearances over 11 seasons of work. How many times has he walked this often in a 19-game stretch? Exactly none:
Think of it this way. Before the season, we projected Santana for a 14.8% walk rate. You can use a binomial probability calculator to estimate how likely it is he’d sustain a 30.4% walk rate over 79 plate appearances. As you might expect, it’s wildly unlikely — if his true-talent walk rate is still 14.8%, there would be a 0.03% chance of this happening. Read the rest of this entry »
When baseball finalized its jam-packed schedule for this year, one thing was immediately evident. Between an abbreviated ramp-up schedule and a dense slate of games, relievers would be in more demand this year. Starters would need time to get stretched out, and that’s extra innings for the bullpen. Stretches of six games in five days would be more common with fewer off days — a perfect time for a bullpen game, or for three competent frames from a minor leaguer and six relief innings.
True to form, 2020 has been a relief-heavy endeavor. As Jay Jaffe noted, starters are on pace to throw their fewest innings per start ever. You can do the math — that means that relievers are on pace to throw their most innings per game ever. Given all that, here’s a question for you: what does that mean for reliever rest and usage patterns?
The correct answer, as usual, is that it’s complicated. Not every relief pitcher is built equally, and not all of them play the same role on a team. You want 2014 Craig Kimbrel in the big spots and some worse reliever (saw the 2020 Kimbrel joke, passed it up, too easy) when the game isn’t close. “Relievers are pitching more innings” is incontrovertibly true, but I wondered how that usage broke down between groups.
Read the rest of this entry »
Before you start reading this article, you should know that the conclusion stinks. This isn’t one of those articles where facts stack neatly upon facts, revealing a hidden truth of baseball at the eleventh hour. It’s the opposite of that, essentially. Sometimes the hidden truth doesn’t reveal itself. Sometimes the stack of facts collapses, and you’re left trying to put the pieces back together. Anyway, I warned you.
The story starts with promise. Howie Kendrick, a 15-year veteran with a swing-first-and-ask-questions-later game, was doing something weird. Take a look at an extremely specific statistic, current as of August 9 — first-pitch balls in play, by year:
Of note, I’m only going back to 2008, because that’s the first year of pitch tracking data — Kendrick started in 2006, but those two missing years don’t really change the narrative here. That zero in 2020 doesn’t look all that suspicious — the Nats had only played 10 games — but it looks a little suspicious. It might not be holding a match, but there are burn marks on its fingers. Could Kendrick be changing something on the fly? Read the rest of this entry »
Heading into this season, the NL West looked like a three-team race. That’s not completely fair — it looked like a one-team race for first with two other solid teams — but with a 16-team playoff field, somewhere between two and three teams from each division are headed to the playoffs, leaving it a three-team race for either two or three playoff spots.
Fifteen-ish games later, there are indeed three NL West teams in playoff position. The Dodgers are there, of course, and the Padres — no surprises here. But then there are the Colorado Rockies, 11-4 and leading the National League. It’s early — although with a quarter of the season already in the books for many teams, how early is up for debate. But regardless of the time of year, the Rockies are in first place, and I wanted to learn more.
One thing I could do to learn more is look at the Rockies’ individual performances, particularly on the pitching side. Charlie Blackmon is off to a hot start, though looking at a player with a .500 BABIP is rarely compelling 15 games into his season. For whatever reason, neither of those paths grabbed me. I thought I’d take a look at whether we could have expected this, and how surprised we should be. Read the rest of this entry »
As Pablo Picasso once said, “Good artists copy. Great artists steal.” Why start the article with that quote? To paraphrase my junior year English teacher Ms. Woods, “Ben, Advanced Placement readers expect essays that start with a quote, so it’s a safe way to start even if you think it’s trite.” Now, this isn’t an AP essay, but it is an article about how to write an article, so I feel comfortable getting a little bit more meta than usual.
It’s also, to be clear, still an article about baseball! More specifically, it’s about Tyler Duffey. He’s “breaking out” this year, in that he’s faced 16 batters and struck out 10 of them. That sample size? It’s too small to really say anything. Take a look at our handy sample size tool, and you’ll realize it in no time. And yet, we write these articles. Maybe it’s this piece on Chaz Roe, or this one on Tommy Kahnle getting good, or this one on Nick Anderson striking everybody out — over the years, they’ve become FanGraphs staples. How?
Here’s the secret: we’re not confining ourselves to that one sample. Sometimes, the pitcher was already good. Sometimes they had some good points and some bad points, and it looks like they changed the bad points. The idea, though, is that they had something going for them already, and the article is just catching the audience up to the reality on the ground.
Tyler Duffey is a great example of this. By pretty much any conceivable measure, he’s the best reliever in baseball so far this year. FIP? Tied for first with three guys who have only thrown an inning. xFIP? Second behind Colin Rea, one of the aforementioned one-inning wonders. Strikeout rate? First? Walk rate? Well, he hasn’t walked anybody, so that’s a yes.
Read the rest of this entry »
Yu Darvish’s calling card has always been his dizzying array of pitches. Hard cutter, slow cutter, curve, knuckle curve, slow curve, shuuto — if you can name it, he can probably throw it in a major league game. That’s not an obviously great skill, in the same way as Gerrit Cole’s overpowering fastball or Jacob deGrom’s ability to throw sliders in the mid 90’s with command, but the results speak for themselves: Darvish has the third-highest career strikeout rate of any starter, active or otherwise, and impressive run prevention numbers to boot: his career ERA- and FIP- both check in at a sterling 82.
So okay, fine, Yu Darvish has two calling cards: tons of pitches and the ability to use those pitches effectively. Let’s talk about the tons of pitches today, though, because they’re way more fun. Consider, if you will, the two systems we use to classify pitches. Darvish’s career looks like a bingo board on both, but they’re two very different bingo boards. First, our standard pitch types:
It’s a little bit of everything, with a heavy emphasis on cutters in the last two years. Meanwhile, the sliders have gotten slow — a near-career-low 79.9 mph, nearly as slow as his curveball, which has gotten fast. It’s a confusing mess. Next, take a look at pitch types per Pitch Info:
Rafts of sliders! More curveballs! The only thing the two systems seem to agree on is the 3.6% splitters, thrown at a dizzying 90 mph. You can’t see Pitch Info’s velocity numbers on here, but they’re divergent as well: these cutters are blazing, checking in at 92.3 mph, and the sliders are much faster than the first classification set, checking in at 86 mph.
What’s happening here is that the two systems don’t know what to do with Darvish’s array of breaking balls. Say, for the sake of argument, that Darvish throws seven different breaking balls, each with a different velocity and movement profile. Try to classify those using three buckets: cutter, slider, and curveball. Good luck! Here’s a pitch that Baseball Info Solutions, which doubles as our generic “Pitch Types” data source, classified as a cutter last night:
Looks like a cutter to me, or maybe a four-seamer that he over-cut inadvertently. It has a hair of glove-side break, which moves it from where O’Hearn thinks he’s swinging — middle-in fastball, a juicy first pitch target — to where he’s actually swinging, directly over the inside corner. At 93 mph, that’s a nasty pitch, no doubt, and it’s also pretty clearly a cut fastball. Darvish, who throws his four-seam fastball in the 95-96 mph range, is hardly throwing a 93 mph slider.
That was a gimme. How about this one?
Victor Caratini’s overzealous framing aside, that looks like a pretty different pitch to me. It’s slower, and bendier; if the last pitch had a hair of break, this one has an entire bearskin rug. It doesn’t have that cutter-esque ride, either. Just one problem: Darvish, by his own admission, throws two types of cutters. So maybe that’s a cutter too.
And what about this one?
Aside from Caratini’s framing paying off, that looks like a completely different pitch. It has as much vertical break as horizontal, and it’s 10 mph slower than the first cutter we looked at. Maybe this one’s a slider, then.
But what about this one, literally the previous pitch?
That’s even slower, but it has less drop; that looks more like a textbook slider, mostly glove-side break, though not a ton of break at that. East-West movement in the low 80s? Sounds like a slider to me. Before you go calling that a slider, though, consider this pitch, which was classified as a slider:
Gravity took this one far more than the last one, despite almost identical velocity. How can those two be the same pitch? And don’t go calling it a curve, either, because I’ve got one of those to show you, and it’s more North-South despite similar velocity:
And of course, Darvish throws two different types of curves — three, really, though we haven’t seen the extremely slow curve/eephus yet this year. Take a look at this majestic lollipop:
I just showed you seven different pitches. None of them were obviously the same if you look at the three critical elements of a pitch: velocity, vertical break, and horizontal break. Try fitting them into three buckets — cutter, slider, and curve — and you start to see the problems inherent in classifying Darvish’s pitches.
Still, even if you don’t have the right names for things, there’s often some internal logic. Take Shane Bieber’s new arsenal, for example. He calls his pitches a cutter, slider, and curve. I looked at them and saw two curves and a slider. We’ve since reclassified the “hard slider” to a cutter and the “hard curve” to a slider, which gives you this graph for all of his pitches in 2020:
If you ignore the colors and shapes, there are five distinct spots. Quibble all day about what to call them — and we here at FanGraphs love to quibble, don’t get me wrong — but Bieber does five distinct things to the ball when he throws it, and that moves it into five distinct areas. Here’s Darvish’s 2020 chart:
This uses the Pitch Info classifications from above, which is why there are more “sliders” than “cutters,” but c’mon. These dots overlap. The edges bleed together, and there’s less center of mass. Some of the splitters are in the sinker quadrant, some in the slider quadrant. The cutters are everywhere, with some rising and some falling. The curveballs could easily be two pitches, and some could be sliders. Some of the curveballs have vertical movement if you don’t account for gravity!
When I set out to write this article, I wanted to talk about how Darvish was willing to throw any pitch in any count. The league as a whole decreases its fastball usage (excluding cutters) by five percentage points on two-strike counts. Darvish has thrown his more often with two strikes this year, 32.3% against 31% in all other counts. Take 0-0 out of the equation, and it’s even stranger: Darvish throws 43% fastballs to start an at-bat, then 24.5% fastballs until he hits two strikes, then 32.3% fastballs.
As I mulled over what to call each pitch and where to draw bright lines in describing his pitch usage, however, I changed my mind. Darvish isn’t exactly going against the grain, using his curveball when others would use their fastball and his slider when others would use their changeup. He changes each of his pitches so much, more run here or drop there, that while he does sometimes pitch against the grain, he sometimes throws a slider in a slider count and is still bucking convention, easier to do when you have fifteen sliders or whatever.
So in the end, forget all that noise. This isn’t an article about why Yu Darvish is great, at least not one of those nuts-and-bolts analytical articles where I show you the new pitch, show you how he’s using it in an interesting way, and then show you how that reduces hitters to a quivering mess in the batter’s box while unlocking fame and fortune for the pitcher.
This is an article about how fun it is to watch Darvish pitch and try to name the pitch he’s throwing. It’s wild. When he’s on, he can command them all at will — and as his 3.1% walk rate will tell you, he’s on right now. This form of Darvish is both dominant and delightful. Through three starts, he has a 2.12 ERA and a 1.63 FIP (2.99 xFIP). He has the second-most WAR among all pitchers this year, behind only Bieber. And yet, that’s not the fun part. The fun part is when he does this:
Which is a nasty enough pitch on its own, 97 on the black with some arm-side run to paint the corner, even if he missed Caratini’s target. But it’s not just that; it’s that in the same outing, he’s liable to do this:
And batters are so geared up for so many things that they just sometimes let it go by. Anyone can throw a 90 mph cutter that backs up and spins instead of breaking. When Darvish does it, though, you think hey, wait, maybe that was on purpose. Baseball is fun when you can analyze it, but it’s also fun when you’re left wondering, and no pitcher in baseball leaves me gleefully wondering more than Darvish right now.
There weren’t a lot of bright spots on the 2019 San Francisco Giants. Pablo Sandoval was fun here and there, particularly when he pitched. Alex Dickerson hit a few dingers. Donovan Solano isn’t cooked just yet. For the most part, though, those were marginal. The real splash, the only real splash, was Mike Yastrzemski, who went from feel-good legacy to bona fide major league outfielder in the course of one slugging season.
2019 was already surprising enough for the career minor leaguer. After showing flashes of patience, power, and a feel to hit in previous seasons, he put them all together in Triple-A Sacramento, and there was no one blocking him from the majors. Four hundred plate appearances and a .272/.334/.518 batting line later, he was the best outfielder on the team, and the Giants were constructing their 2020 roster with one spot on the depth chart written in pen.
If the start of 2020 is any indication, however, last year wasn’t Yastrzemski’s ceiling. His ceiling is this year’s white-hot start: .310/.473/.643 with three homers, good for a 204 wRC+. Oh yeah — he’s playing freaking center field every day, too. Twelve games does not a season make, but if you could make his whole season out of the last two weeks, he’d basically be Mike Trout — an up-the-middle defender with a 200-ish wRC+.
Is he a good fielder? It’s unclear. He looked good both by the eye test and by the advanced statistics troika of DRS, UZR, and OAA last year in the corners, and looks at least reasonable in center so far this season. He’s not a long-term premium defender — he’s nearly 30, for one thing, and has only average straight-line speed — but tuck him in a corner, and he’ll be inoffensive at worst and an asset at best.
But the exciting part about Yastrzemski isn’t the fielding, at least not mostly. It’s the offensive value, the leading-baseball-in-WAR offensive explosion that makes Giants fans mostly shrug their shoulders but also rub their hands together greedily when they think no one’s looking. Sure, it’s early. Sure, it’s not our year. But it could be real, right? The team could have found a new superstar, right? Read the rest of this entry »
When I launched this OOTP fan-sourcing project in March, the prospect of an actual season of baseball felt remote. I didn’t give much thought to how I’d feel virtually managing the Brewers while the real Brewers played, because it simply wasn’t an option. The real Brewers weren’t playing, regardless of what we did, so it hardly seemed to matter.
Why bring this up now? Because having both sets of Brewers play at the same time is making it difficult to keep track of the two. In the real world, Lorenzo Cain opted out of playing this season, leaving the Brewers scrambling for center field depth. They resorted to playing Avisaíl García in center yesterday, but they’ll be searching for answers elsewhere. In the Out Of The Park universe, Cain hurt his wrist throwing the ball — he’ll be out a week or more, leaving the team scrambling for depth in the interim.
In the real world, the rotation has some questions. Josh Lindblom left his first start early with back spasms, Brett Anderson looked shaky in his return from injury, and it feels like more arms will be needed. In OOTP, Lindblom missed the first four months of the season with injury, Anderson perpetually looks shaky in his return from injury, and even after an early trade for Kevin Gausman, more arms are surely needed.
Oh, right. There are some big differences. First, the OOTP Brewers are without the services of franchise cornerstone Christian Yelich for the next month or so after he strained his oblique. The team is running out a platoon of Tyrone Taylor and Matt Joyce in left field to replace as much as possible of Yelich’s production — oof. No team could replace Yelich’s production and not miss a beat, but that feels particularly bad, even if Joyce can still hit righties. Read the rest of this entry »