Ah, the playoffs. The smell of fall in the air, the sight of towel waving and packed stadiums across the country, and the endless stream of pontification on social media. Are the Rays just not built for the postseason due to a lack of star power? Have the Dodgers been playoff slouches because they’re too dependent on their stars? Do the Astros know something about how Martín Maldonado manages a pitching staff that we don’t? Do we know more about how to manage a pitching staff than John Schneider? The list goes on.

Especially with the new opportunities to weigh in given the expanded playoff structure, it’s been harder than ever to hone in on ideas worth pondering, let alone hypotheses that are falsifiable. But the other day, a xweet from MLB Network researcher Jessica Brand caught my eye:

Of the 145 pitchers with 50.0+ innings pitched in the playoffs, their average ERA changes by -0.32. Genuinely surprised it's to their favor too!

Worried about outliers? Median further cements this point, at -0.36.

44 of 145 go up, 100 go down, 1 stays the same: Catfish Hunter. https://t.co/AcqKFqyJyA

— Jessica Brand (@JessicaDBrand) October 9, 2023

Thanks to our handy new postseason leaderboards, this was indeed an interesting assertion that I could test. I limited my sample to hurlers who not only tossed at least 50 frames in the playoffs, but who also managed 500 innings in the regular season. There were 142 pitchers who met these criteria, and they averaged an ERA three tenths of a run lower in the playoffs. Per a paired-samples t-test, this result was statistically significant. Read the rest of this entry »

This all started because I wanted to write about Isaac Paredes. He’s my kind of player, excellent despite all sorts of warning signs that what he’s doing shouldn’t be working. Advanced metrics and in-person scouting assessments are both quite negative on Paredes, and yet he’s batting .255/.354/.503, good for a 140 wRC+, in mid-September. He’s been one of the most valuable players on one of the best teams in baseball. It’s so weird!

But lo and behold, the exact thing I wanted to write about has already been written. Curse you, Esteban Rivera! Well, not actually, of course. Esteban’s writing is great, and it’s also of particular interest to me because he’s so observant of hitting mechanics. But I can’t exactly write an article about how Paredes’ pull-happy tendencies have helped him keep regression at bay when there’s a better article talking about just that already on the site. Read the rest of this entry »

A couple of weeks ago, I saw Jonah Heim take a called strike that he felt should have been a ball. As a catcher, Heim knew better than to argue. Instead, he performed the delicate dance of the catcher who wants to make a point without showing up the umpire. I’m not sure if the clip below is the exact pitch I saw, but it’s certainly representative of the conundrum a catcher faces when he doesn’t like the strike zone.

You can see Heim duck his head and furtively say something to home plate umpire Doug Eddings. I like to imagine that whatever he says begins with, “I beg your pardon, good sir.” He doesn’t make a show of his displeasure. He asks something, Eddings nods his head yes, and everyone moves on with their lives. Still, Heim thinks he’s seen ball two, and it’s hard to blame him. Even the person operating the score bug got fooled.

For some reason, that little moment has been rattling around in my head. I tend to think too much about the relationship between umpires and catchers. It doesn’t seem possible that they could spend every night doing what they do in the proximity that they do it in without developing a bond. Read the rest of this entry »

In August, the Phillies hit 59 home runs, which is the highest total for a month in franchise history and tied for the third-highest total in any single month by any team in history. It was a remarkable performance, but perhaps not a particularly surprising one given how this roster was constructed; by design, Rob Thomson’s charges are large, strong, and (of late) increasingly shirtless. They were born to mash.

Last week, I had the good fortune to be present at Citizens Bank Park as five of those 59 home runs took flight in a single evening, off the bats of five different Phillies. This was one of those close, muggy summer nights that define the mid-Atlantic summer; with a pleasant, gentle breeze blowing out to left field, the ball was roaring out of the park. It wasn’t just the Phillies; the Angels dingered three times themselves. Two of those came off the bat of Luis Rengifo, hardly a man whose public stomps and chants are included in the Home Run Derby every year.

But as the Phillies laid 12 runs on their opponents, the play that stuck in my mind was the opposite of a home run. In the sixth inning, the Phillies batted around and scored six runs to turn a 4–2 deficit into an 8–4 lead; one of those came on a squeeze bunt by Johan Rojas. It was a lovely push bunt by a speedy right-handed hitter, the baseball equivalent of spreading room temperature compound butter on a slice of crusty bread. “Man, we should see that more often,” I thought to myself. Read the rest of this entry »

Some of the most frustrating arguments involving baseball statistics revolve around the use of expected stats. Perhaps the most frequently cited of these metrics are Statcast’s xStats, which use Statcast data for hitters to estimate the batting average, on-base percentage, slugging percentage, and wOBA you’d “expect” a hitter to achieve. Investigating how predictive xStats are compared to their corresponding actual stats has been a common research exercise over the last few years. While it depends on the exact dataset used, xStats by themselves generally aren’t much better than the actual stats at predicting the next year’s actual stats. But that doesn’t mean we should simply discard expected stats when trying to evaluate players.

While I’m not going spend too much time talking about how predictive xStats are versus the actual ones, I do want to briefly touch on some of the existing work on the subject. Jonathan Judge at Baseball Prospectus examined many of the expected metrics back in 2018. He also spoke with MLBAM’s Tom Tango about the nature of expected stats and their usage:

Earlier this week, we reached out to BAM with our findings, asking if they had any comment.

MLBAM Senior Database Architect of Stats Tom Tango promptly responded, asking that we ensure we had the most recent version of the data, due to some recent changes being made. We refreshed our data sets, found some small changes, and retested. The results were the same.

Tango then stressed that the expected metrics were only ever intended to be descriptive, that they were not designed to be predictive, and that if they had been intended to be predictive, they could have been designed differently or other metrics could be used.

Read the rest of this entry »

The .300 hitter is dying, Ian Crouch wrote in The New Yorker in 2014. And Bradford Doolittle on ESPN.com in 2019. And Barry Svrluga in the Washington Post just last month. If the .300 hitter is dying, it’s dying the same way you and I are, a little bit each day. Maybe the .300 hitter is just sick.

Why do these stories keep getting written? Well, last week I was checking in on Luis Arraez (come on, dude, I thought you were going to make a serious run at .400!) and came to the startling realization that only nine qualified hitters are on pace to hit .300. Nine! I can’t imagine being a baseball writer, seeing that fact, and not being freaked out enough to write about it.

Baseball is a sport that got its tentacles into the American popular vernacular something like 100 years ago, dropping idioms like eggs. “Three strikes,” “home run,” “lost his fastball,” and dozens of others. “Batting 1.000” is probably a more popular phrase than “batting .300” or “hitting .300,” but the latter is still legible to people who think Christian Walker is what you call pilgrims on the Camino de Santiago. Read the rest of this entry »

Look, I know that isn’t the line. It’s a chicken in every pot. But I came up with a good lobster pun last week, and I’m writing more about the ins and outs of teams driving home runners from third base, so I decided to go back to the well. You’ll just have to live with it; I’m the one driving the boat here, and as it turns out, it’s a lobster boat.

With the puns are now settled, let’s get down to business. Last week, I chopped up the 2023 season into halves to see how well various statistical indicators correlated with a team’s future ability to cash in their runners. As a recap, strikeout rate had a fairly strong correlation, and not much else did. Quite frankly, though, I wasn’t particularly convinced by that. There just wasn’t enough data. With only 30 observations, it’s too easy for one team to skew things, or at least that’s how it feels in my head.

There’s an easy solution: more data. So I used the same split-half methodology from last week and started chopping past seasons in two. More specifically, I picked the years from 2012-22, excluding the shortened 2020 season. In each case, I followed the same procedure: I split the season in two and noted each team’s offensive statistics in the first half. Then I looked at how efficient each team was at scoring when a runner reached third with less than two outs. I got a much bigger sample this time; 300 observations, which makes it a lot harder for a single outlier to mess things up. Read the rest of this entry »

We’re in a tiny lull in the baseball season, and honestly, I’m happy about it. July is jam packed with draft and trade talk, September and October are for the stretch run and the postseason, but the middle of August is when everyone catches their breath. There’s no divisional race poised on a razor’s edge, no nightly drama that everyone in baseball tunes in for; it’s just a good few weeks to get your energy back and relax.

For me, that means getting a head start on some things I won’t have time to do in September, and there’s one article in particular that I always want to write but never get around to. I’m not a BBWAA member, and I’ll probably never vote for MVP awards, but I spend a lot of time thinking about them every year nonetheless. When I’m looking at who would get my vote, I take Win Probability Added into account. Every time I mention it, however, there’s an issue to tackle. Plenty of readers and analysts think of WPA as “just a storytelling statistic” and don’t like using it as a measure of player value. So today, I’m going to explain why I think it has merit.

First, a quick refresher: Win Probability Added is a straightforward statistic. After every plate appearance, WPA looks at the change in a team’s chances of winning the game. We use our win expectancy measure, which takes historical data to see how often teams win from a given position, to assign each team a chance of winning after every discrete event. Then the pitcher and hitter involved in that plate appearance get credited (or debited, depending) for the change in their team’s chances of winning the game. Since every game starts with each team 50% likely to win and ends with one team winning, the credit for each win (and blame for each loss) gets apportioned out as the game unfolds. The winning team will always produce an aggregate of 0.5 WPA, and the losing team will always produce -0.5, spread out among all of their players. Read the rest of this entry »

Last week over at Pinstripe Alley, I investigated DJ LeMahieu’s recent hot streak. Naturally, he got injured as soon as I finished writing, but I went through with the piece nonetheless because I felt like I was onto something. Specifically, I noticed that LeMahieu’s struggles this year came when pitchers were challenging him more; as a result, he was swinging more, but proportionally, more of those swings happened to come on balls than when pitchers were being stingy with their strikes.

When attempting to contextualize LeMahieu’s hot stretch, I noticed another hitter who’s been on fire lately thanks to some improved discipline: Ha-Seong Kim. Over the past 30 days, he’s tied for the major league lead in WAR with Freddie Freeman at 2.1. Some of that production has come from his typically excellent defense, but Kim has been no slouch with the bat either; in that span, he’s posted a 189 wRC+, eighth-highest among 167 qualifiers. Perhaps most notably, he’s also tied (with Lars Nootbaar and Alex Bregman) for the second-best BB-K rate, behind only Marcus Semien.

Prior to that 30-day stretch, Kim’s swing rate was already a career-low, and his BB-K rate near a career-best. But his swing rate has dropped even further in the last 30 days, ranking second-lowest at 34.2% to Nootbaar’s 34.1%, and his BB-K rate has gone from negative to positive; now it’s definitely a career-best. Nootbaar has followed a similar trajectory: his swing rate was already a career-low and has sunk even further, and his BB-K rate is now approaching a career-best thanks to his own torrid month. Read the rest of this entry »

Monday night, my wife posed a baseball question I couldn’t immediately answer. As the Angels and Giants went to the eighth inning with the Halos up by a run, she had a simple question: How often does a team that’s losing after seven innings come back and win? I guess I could have gone to our wonderful WPA Inquirer, a fun little tool for hypotheticals. That tells me that the Giants had around a 25% chance to win heading into the eighth. But I took her question as a broader one, concerned not just with that specific game, but with all games. How likely is a comeback?

I didn’t know the answer offhand, and I couldn’t find it on Google either (secret professional writer tip: use Google). So I did what anyone in my situation would do: I said “I don’t know, but now I’m going to write an article about this.” Two days later, here we are.

I’m hardly the first person to do research on comebacks. Russell Carleton has been looking into comebacks for a while. Rob Mains has too. Chet Gutwein investigated comeback wins and blown saves here at FanGraphs in 2021. Everyone loves to write about comebacks. Baseball Reference even keeps a list of the biggest comeback wins. They’re memorable games, and fertile ground for investigation. Read the rest of this entry »