FanGraphs After Dark Chat – 3/14/17

1:51
Paul Swydan:

Who do you think will win the World Baseball Classic?

Cuba (0% | 0 votes)
 
Dominican Republic (46.1% | 77 votes)
 
Israel (5.9% | 10 votes)
 
Japan (3.5% | 6 votes)
 
Netherlands (1.1% | 2 votes)
 
Puerto Rico (8.9% | 15 votes)
 
USA (18.5% | 31 votes)
 
Venezuela (1.1% | 2 votes)
 
I don’t care I’m not watching (10.7% | 18 votes)
 
I can’t decide!!!!! (3.5% | 6 votes)
 

Total Votes: 167
2:03
Paul Swydan:

Which movie debuting between now and the end of April are you most excited to see?

Beauty & The Beast (17.5% | 19 votes)
 
T2: Trainspotting (15.7% | 17 votes)
 
Life (6.4% | 7 votes)
 
Power Rangers (10.1% | 11 votes)
 
Ghost in the Shell (13.8% | 15 votes)
 
The Fate of the Furious (13.8% | 15 votes)
 
The Lost City of Z (8.3% | 9 votes)
 
The Circle (3.7% | 4 votes)
 
Sleight (0.9% | 1 vote)
 
Other (say in comments) (9.2% | 10 votes)
 

Total Votes: 108
4:24
Paul Swydan:

In honor of Pi Day, what is your favorite kind of pie?

Apple (20.4% | 39 votes)
 
Pecan (13.6% | 26 votes)
 
Sweet Potato (2.0% | 4 votes)
 
Blueberry/Strawberry/Cherry/other kind of berry (15.7% | 30 votes)
 
Chocolate Mousse (7.8% | 15 votes)
 
Pumpkin (9.9% | 19 votes)
 
Lemon Merengue (6.2% | 12 votes)
 
Rhubarb (5.2% | 10 votes)
 
Key Lime (12.5% | 24 votes)
 
Other (say in comments) (6.2% | 12 votes)
 

Total Votes: 191
9:01
Paul Swydan: Hi everybody!

9:01
Jeff Zimmerman: Hi

9:01
Paul Swydan: I’m disappointed so many of you want to see the horrifying live action Beauty and the Beast,

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Examining Two Years of Catch Probabilities

Earlier today, my first post about catch probability was published. In that post, I mostly looked at the two years of information, together. In here, I’d like to keep the two years separate. I mean, this is a whole new data source, with a number of potential applications. Why would I ever write just the one article and stop there? I have a weekly quota to hit, and this is better than whatever else there is to analyze.

Catch probability is a new Statcast metric, which you can read about here. As complicated as it might seem, it’s actually quite simple to understand, and it can give us better answers to questions people have been asking for decades. This is where you can find all the data, so you can poke around on your own. This is all brand new, and it’s kind of a first draft. The data will improve as adjustments are made for batted-ball direction and for outfield dimensions. Already, though, we can learn from what’s been provided.

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Yonder Alonso Has Changed His Mind

Have you seen what Yonder Alonso is doing this spring? You might not recognize it. If he qualified, his .421/.560/.789 line would the third-best in baseball. While it’s easy to dismiss a spring fling from an established player, this player spent the offseason thinking differently. Now he’s moving differently at the plate, too.

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Eric Longenhagen Prospects Chat, Pie

1:02
Eric A Longenhagen: Howdy, chat.

1:02
Eric A Longenhagen: You’re all perfect children of god. Let’s chat about baseball.

1:03
Eric A Longenhagen: Oh wait, top 100…

1:03
Eric A Longenhagen: Please check that out if you have yet to.

1:03
Eric A Longenhagen: OKay, now let’s start.

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One Cause for Optimism in Cincinnati

The Reds’ pitching staff was absolutely dreadful last year. Their rotation and bullpen were both the worst in baseball. With a ghastly -0.5 WAR, their staff was the worst since the 1800s, which basically means it was the worst of all time.

Not much has changed since last year. Here’s the current depth chart for the Cincinnati rotation:

Name IP K/9 BB/9 HR/9 BABIP LOB% ERA FIP WAR
Brandon Finnegan 171.0 8.2 3.9 1.4 .297 73.0 % 4.42 4.66 1.4
Anthony DeSclafani   136.0 7.7 2.4 1.2 .305 72.8 % 4.06 4.14 1.9
Scott Feldman 133.0 6.1 2.6 1.3 .305 69.6 % 4.65 4.65 1.1
Robert Stephenson 119.0 8.9 5.5 1.5 .301 71.8 % 5.07 5.25 0.5
Bronson Arroyo 117.0 5.0 2.2 1.8 .299 68.8 % 5.34 5.44 0.1
Homer Bailey   93.0 7.6 2.8 1.2 .309 70.7 % 4.37 4.27 1.1
Cody Reed 81.0 8.3 3.1 1.3 .306 72.8 % 4.24 4.38 0.9
Tim Adleman   37.0 6.6 3.0 1.5 .300 70.3 % 4.90 5.03 0.1
Austin Brice 19.0 8.0 4.2 1.3 .306 70.8 % 4.79 4.88 0.1
Amir Garrett 9.0 7.9 4.7 1.3 .303 71.6 % 4.77 4.94 0.1
Keury Mella 9.0 6.4 4.2 1.4 .306 69.1 % 5.27 5.32 0.0
Nick Travieso 9.0 6.4 4.0 1.4 .301 69.4 % 5.12 5.23 0.0
Total 933.0 7.4 3.3 1.4 .303 71.3 % 4.62 4.72 7.4

Brandon Finnegan is at the top, which is fine, I guess. After that, however, things go downhill in a hurry — especially with Homer Bailey and Anthony DeSclafani slated to open the year on the DL. For example: both Bronson Arroyo and Scott Feldman are apparently not only still pitching, but are penciled in for 250 innings in Cincinnati’s rotation. The rest of the list is made up of unproven youngsters. Each of them has some promise, but none have had much success in the major leagues, either. Hence their middling projections.

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Man’s Search for Meaning in Spring Training

This is Kate Preusser’s second piece as part of her month-long residency.

It’s no secret that there’s considerable overlap between bookish types and baseball fans, all tucked cozily in the center of that particular Venn diagram. Distance readers have an inborn patience for the nine-inning drama of a baseball game. These are a people who understand the three-act structure, exposition leading to rising action leading to the climactic moment; this past World Series, in fact, felt a little like the baseball gods had taken a Khan Academy class on Aristotle’s Poetics.

But there’s a narrative that most serious baseball fans have come to reject, and that’s the one of spring training. Every year there seem to be pieces poking fun at the cliches of spring training — Best shape of his life! Swing mechanics change! Learning a new pitch/grip/arcane religious philosophy! LASIK! — and those pieces exist because these cliches persist, so much so that poking fun at spring-training cliches is now itself a form of cliche.

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Miguel Sano, Defensive Superstar

I’m going to be up front with you: that headline is seriously misleading. Based on what we can tell, Miguel Sano is probably not a good defensive player. Last year, though, to try and get the club’s offense going, the Twins decided to try Miguel Sano in right field. Regret kicked in pretty quickly.

He played right field most days for the first couple of months of the season, until a strained hamstring put him on the disabled list for the entire month of June. During the month that the team didn’t have to watch Sano chase balls around the outfield, they decided that they didn’t really want to see that ever again. When he returned to the team at the beginning of July, he was promptly moved back to third base. He split his time between there and DH over the rest of the year.

As a pretty large human being, Sano certainly doesn’t look like an outfielder, and while we only saw him out there for a little over 300 innings, the early returns weren’t particularly positive.

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Let’s Play With New Defensive Data

Here’s the thing about catch probability: It’s existed for close to two decades. It’s at the heart of what we refer to as the advanced defensive metrics. Defensive Runs Saved, Ultimate Zone Rating — they couldn’t exist and do anything without catch probabilities in some form. It’s just that, for the longest time, those probabilities were generalized, educated guesses. You might’ve heard that baseball has entered the information era.

Here’s a weekend tweet from Daren Willman:

If you missed the link in there somehow, here it is again: the Statcast Catch Probability Leaderboard. We have most of two years of Statcast information, and now we’re getting to see it applied to player defense. Specifically, in this case, outfielder defense. If you don’t entirely understand what catch probability is, here’s the MLB.com glossary entry. Take a given fly ball or line drive to the outfield. What are the odds a given batted ball is caught? Statcast can tell us, by considering hang time and necessary distance to cover. This is the start of something beautiful.

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FanGraphs Audio: Travis Sawchik on Necessity, Invention

Episode 723
The prolific Travis Sawchik is a former beat reporter for the Pittsburgh Tribune-Review and author of the book Big Data Baseball. He’s also the guest on this edition of the program, during which he discusses players like Jose Bautista, J.D. Martinez, and others who’ve been compelled to follow unconventional paths to success.

Don’t hesitate to direct pod-related correspondence to @cistulli on Twitter.

You can subscribe to the podcast via iTunes or other feeder things.

Audio after the jump. (Approximately 1 hr 6 min play time.)

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Does J.J. Hardy Even Like Hitting?

Last April 4, Adam Jones swung at the first pitch two times. He swung at the first pitch five times on April 6, and then he swung at three more first pitches on April 14. By bedtime April 20, he was up to 16 first-pitch swings. The next day, he added four more.

Teammate J.J. Hardy also swung at the first pitch 16 times. All season. Out of 438 first pitches.

Hardy has never been aggressive early on. His highest-ever first-pitch swing rate is 11.9%, set as a rookie. His career rate is 8%, against a league average north of 27%. Last year, though, he was particularly patient. Not that Hardy is aggressive in any count, but I’ve highlighted him in this plot of first-pitch swing rates and all-other-count swing rates.

The next-lowest first-pitch swing rate was more than twice as high. Hardy’s other-pitch swing rate isn’t so weird, around 47%. But he swung at the first pitch just 3.7% of the time. The other players in his peer group, by other-pitch swing rate, went after the first pitch 25.7% of the time. It’s not that Hardy would never go after the first pitch, but every single time, it came as a surprise.

You’d figure Hardy might be really selective then, right? Welp! Of the 16 first-pitch swings, seven came at pitches out of the zone. Seven swings put the ball in play, but Hardy wound up with one hit, on a grounder. Perhaps it’s additionally worth noting that Hardy took all of three first-pitch swings when there was no one on base. When he was aggressive, mostly, he was just trying to move runners around.

It should go without saying that I don’t know exactly what Hardy’s plan is, because I’m not J.J. Hardy. He might just feel a lot more comfortable after he sees one pitch out of the hand. But just looking at this from the outside, Hardy could probably stand to just pay closer attention from the on-deck circle, because he’s been taken advantage of. Unsurprisingly, Hardy last year had one of the league’s very highest first-pitch zone rates. And no other hitter in the game had a higher percentage of his plate appearances advance to an 0-and-1 count. Hardy went through that count in about 61% of his trips. The average was 49%. If anything, it might be strange these rates weren’t even higher.

Again, hey, Hardy’s his own man. He’s coming off a much better season than the one he had the year before, so more power to him for his 2.3 WAR. He’s not doing everything wrong. But that’s an Orioles lineup full of guys unafraid to take an early hack. Maybe Hardy’s just trying to be different on purpose, but it seems to me he’s doing himself a disservice by watching as much as he does. There has to be a better way to get yourself prepared.