More than anything else, I’ll remember Carlos Rodón’s no-hitter for how it ended. Not when he hit Roberto Pérez in the foot — that was no fun, but perfect games end on nonsense all the time — but because he threw harder as the game went on, topping out at 99 mph on his 110th pitch of the game. It’s all the more impressive when you consider that he started the game in the low 90s.

Pitchers losing velocity as the game goes on is a phenomenon as old as baseball itself. That’s just how it works; throwing a pitch requires a ton of physical effort, and doing it 100 times will wear you down. If you’ve ever done repetitions of anything in your life, you can empathize. Rodón laughs at that fact of life, in a way that I think of as Justin Verlander-esque, and I was curious whether other pitchers follow the same pattern, particularly after Jacob deGrom popped a casual 101 mph fastball in the seventh inning of his latest start.

Using deGrom as evidence of anything is an iffy idea at best — the man is a unicorn, a pitching deity descended to earth. But Rodón is mortal, and he does it, so it’s hardly some unobtainable goal. I set out to see whether pitchers are adding velocity in later innings these days, and whether that addition has changed over time. Read the rest of this entry »

The strike zone doesn’t exist. Not physically, at least; it’s a rough boundary that varies based on how each umpire looks at it and how each batter stands. Catchers influence the shape, too; smooth hands can turn balls to called strikes, while cross-ups tend to do the opposite.

This year, the zone seems particularly amorphous — maybe it’s just my imagination, but I feel like I can’t turn on a broadcast without hearing about an inconsistent zone. Of course, hearing isn’t believing, and there are botched calls every year. Just because there have been some memorable ones this year doesn’t necessarily mean the overall rate of missed calls has changed. Let’s find out if it has, or if it’s merely imaginations running wild with the backdrop of fan noise.

For a rough idea of ball/strike accuracy, I went to Statcast data. For every pitch, Statcast records a top and bottom of the strike zone, as well as where the pitch crossed the plate. Armed with that data as well as some constants like the size of a baseball and the width of home plate, I measured how far out of (or into) the strike zone each pitch of the 2021 season was when it crossed the plate.

This data isn’t perfect. The top and bottom of the strike zone are approximated, and the plate isn’t a two-dimensional object, despite the fact that our data on it is represented that way. We aren’t considering framing. But we have previous years of the same data, which is great news. We can use the previous years to form a baseline, then see if this year’s data represents a meaningful change. And because we have a huge chunk of data, we can at least hope that framing comes out in the wash. Read the rest of this entry »

It is still early in the season, but one of the aspects of hitting that stabilizes relatively quickly is changes to approach. Swings are a more common occurrence, so the sample for these statistics grows faster than those that rely on an accumulation of plate appearances. So who seems to have made some changes in the early going?

To get an idea, I took all players who accumulated 250 plate appearances combined in the 2019 and ’20 seasons (I chose to group these seasons together because of the brevity of the pandemic-shortened campaign), then filtered by those who meet the qualified criteria in 2021. This leaves a sample of 159 hitters; each table includes the top and bottom ten players for each metric.

Read the rest of this entry »

I would imagine that one of the most jarring pitches for a major league batter to face is an extremely slow breaking pitch. Conventional wisdom might suggest the opposite — something like triple-digit heat. But at least a batter knows to expect high-end velocity when he steps to the plate against a given pitcher. A pitch under 70 mph, on the other hand, is rare enough that it can freeze you. Not familiar with the types of pitches I am talking about? Here are a select few.

Since 2015 (i.e., the Statcast era), just 0.3% of all pitches thrown in MLB have been under 70 mph; pitchers today generally live in velocity bands from 10 to 30 mph higher. Being able to slow the ball down to such an extreme degree without tipping off the batter to what is coming is not trivial, and being able to drop these pitches in for strikes takes practice. Taking time in a throwing session to lob lollipops into the strike zone probably seems foolish to many pitchers, especially if they can just throw 95 mph instead.

I understand the roadblocks to throwing slow looping curveballs. But whenever I see a pitcher throw them, they often seem to disarm the batter, who usually doesn’t swing. In that scenario, the worst-case result is often a ball, and if the pitcher can locate the pitch, he can nab a strike with little resistance. And as fastball velocity continues to increase across the league both this year and in seasons past, pitchers are increasingly leaning on breaking balls and offspeed pitches to fool hitters who are geared up for heat. With that in mind, a super-slow curveball could be a useful weapon. Read the rest of this entry »

If you felt like you hadn’t gotten enough fastball velocity analysis at FanGraphs in the past week, do I have a treat for you! Last week, Kevin Goldstein expounded on the importance of the shape of a fastball in determining its effectiveness, making it clear that velocity is the driving factor in evaluating a fastball, but that deviating from a “normal shape” (interpreted as an inch of ride for every inch of run) can lead to missing more barrels. Devan Fink, meanwhile, showed that fastball velocities have increased across the league to start the year, which is especially striking since fastball velocities are usually at their nadir in April. Devan also highlighted pitchers who have seen an especially large bump. Finally, on Friday, Jake Mailhot took a look at Chris Paddack’s first start with a focus on the righty’s fastball after a disappointing 2020 season.

I recommend reading all those pieces, if you haven’t already. Kevin and Jake give credence to the idea that fastball shape is an essential factor in a good fastball. But I want to focus on Devan’s article on fastball velocity and how it seems to be increasing again in 2021, as it has every season since 2008. One can surmise that this is a product of pitchers acknowledging the importance of velocity (thus training with gains in mind) and teams giving more innings to pitchers who, by and large, throw harder. Velocity obviously matters, but how much? Read the rest of this entry »

Last week, Justin Choi published an examination of the new ball. The results were — well, you should read it for yourself, but they were muddled, to say the least. Home runs are down! Exit velocity is up! Liners got better, fly balls got worse. It’s enough to make you wonder whether we’ll ever know the answer. It’s also catnip to analysts, and so today I’d like to present some supplemental evidence that only makes me more confused.

There were two key conflicting findings in Justin’s research. First: home runs are down, and fly balls aren’t carrying as far, on average, as they did last year. Second, overall exit velocity is up league-wide, whether you care about broad averages or the hardest-struck balls. The two effects — harder hits, less carry — benefit line drives over fly balls, because line drives both spend less time in the air and depend less on distance for their value.

I wasn’t really sure what to make of the fact that fly balls are carrying less. There are so many confounding factors — weather, new humidors, angle, stadiums, the list goes on and on — that I don’t think I’ll ever be able to disambiguate them all, but I took a crack at it. Read the rest of this entry »

As part of my exhausting shtick, I like to respond “April!” to questions in my chats involving player performances in the season’s early going. This is effective shorthand when someone wants to know if, say, George Springer is a bust because he’s put up a .480 OPS in his first two weeks in the majors. It’s also dead wrong. April stats, in their proper context, are meaningful.

“But Dan, a few weeks of baseball is a tiny sample!” That’s correct, but you have to take into consideration the underlying reasons projections can prove to be inaccurate. It’s not just that things change, though they do — pitcher X learns a sweet knuckle-curve or batter Y realizes that not hitting everything into the ground might be good — it’s that it’s challenging to gauge where players stand in the first place. Players’ stats themselves aren’t even perfect at this. Tim Anderson hit .322 in 2020, but that doesn’t actually mean his mean batting average projection should have been .322. We don’t actually know if a theoretical player was “truly” a .322 hitter, a .312 hitter who got lucky, a very unlucky .342 hitter, or a .252 hitter who made a deal with a supernatural or extraterrestrial entity. A .300 hitter isn’t observed, they’re inferred.

The way most, if not all, in-season projections (or any projections, really) function is by applying what we call Bayesian inference. We won’t get into a full-blown math class, but in essence, it simply means that we update our hypotheses to take new data into account. And for players, data comes in all the time: every pitch or swing of the bat is new information about a player. It’s valuable information, too, as only the last handful of seasons have much predictive value and recent performance is the most useful. Read the rest of this entry »

In the weirdest year of baseball history so far, 2020 featured a gigantic playoff field introduced right as the season began, turning a 10-team postseason into a 16-team format. Changing the basic structure of awarding the sport’s championship with no advance notice would have been an odd choice in a normal season. But given the 102-game reduction in the league’s schedule and its resulting small sample size season, it kind of made sense. When the decision was made, it wasn’t a surety that there would even be a season, to the point that people would have been happy if extra-inning games were decided by closers riding ostriches and jousting.

Before the World Series was even completed, commissioner Rob Manfred expressed the league’s desire to keep the new format in a normal season. The players need to agree to changes like this, of course, and that permission wasn’t granted after all MLB offered in exchange was a universal designated hitter. One of the concerns, not officially made public, is that a playoff system that is more of crapshoot will further reduce the already eroded incentives for teams to spend money to improve their rosters. That’s hardly a shock; at the 2020 trade deadline, 10 teams already had projected playoff probabilities above 97%. Combine that with the absence of the normal advantages afforded to higher seeds, and you had a trade deadline that saw only a single team, the San Diego Padres, aggressively improve, and even their moves were almost certainly made with an eye toward 2021 and beyond.

So what is the ideal playoff system? That’s a difficult question, one that’s impossible to answer to everyone’s satisfaction. I can only answer for myself, and for me, there are a few requirements that are particularly important. Basically, I want a system in which regular-season performance matters, thus maintaining one of the core aspects of the game. I also want a playoff system that more heavily awards quality over randomness without making the result a preordained one. The more a championship is decided by randomness, the less incentive there is for teams to innovate and invest. Read the rest of this entry »

This story starts, as all good stories do, with me recounting the time one of my coworkers and I discussed something. Okay, fine, very few good stories start that way — almost none, in fact — but bear with me. This (non-baseball) coworker, someone who I consider very bright and very interested in baseball, told me he didn’t really believe in wRC+, even after I’d shown him some articles describing it.

Why, I wondered, didn’t he believe in it? It’s so elegant! The math is right there! How can you not like something that wraps up performance at the plate in a single number? No need to compare apples to oranges — you can juice everything to a pulp and simply count calories. His answer was simple: it doesn’t consider batting order.

“You’re telling me,” he said, “that you’d rather have Mitch Moreland as a leadoff hitter than Xander Bogaerts?” It was 2017, and we were working in the Northeast, which explains why both players were Red Sox and why this question was even close. “His wRC+ is higher, but he’d be worse at leadoff. He doesn’t get on base enough.”

To be honest, it’s a compelling argument. I didn’t really have the intellectual tools or the time to counter it. I went with the old tried and true method: I vaguely mentioned something about context-neutrality in the long run, said I had some bonds to arbitrage or whatnot, and went back to work, ending the conversation without conceding defeat.

Fast forward to today, and I still don’t have a wonderful answer to my former co-worker’s point. I do have a computer program that simulates games, though, so I decided to come up with a quick and dirty check. What if we plugged real hitters with similar one-number batting statistics but who get there in wildly different ways into the lineup? Would we learn anything? Would I be able to write 1,500 words about it and entertain the masses? I guess we’ll find out! Read the rest of this entry »

You know it’s almost time for baseball season when all of the major projection systems forecast Kyle Hendricks‘ ERA one run per nine innings too high.

As much as this sounds like a knock on those who develop projections, it’s not. What Jared Cross (Steamer), Dan Szymborski (ZiPS), Derek Carty (THE BAT), and the folks at Baseball Prospectus (PECOTA) do is no small feat. If I weren’t too cowardly to even try to create my own projection system, I would be too stupid to design one that is half as effective as theirs. Glass houses and all that.

That said, I am just smart enough to know that projected ERAs ranging from 3.84 to 4.42 for Hendricks, who boasts a career ERA of 3.12 and has never finished a season with an ERA above 3.46 (except that dastardly 3.95 ERA in 2015), are too high. It’s easy to poke holes in the obvious outliers, but projections succeed by describing and then predicting the talents of most pitchers, not the ones whose talents deviate dramatically from expectation. Hendricks is every projection system’s known blind spot.

It’s not just projections that struggle with Hendricks, either. We, the sabermetric community, frequently use ERA estimators as shorthand to characterize a pitcher’s talent level. If you frequent FanGraphs, you’re familiar with Fielding Independent Pitching (FIP), expected FIP (xFIP), and Skill-Interactive ERA (SIERA). By virtue of how they’re constructed, each metric makes assumptions about the skills a pitcher theoretically “owns”:

• FIP: strikeouts, walks, and home runs allowed
• xFIP: strikeouts, walks, and fly balls induced
• SIERA: a complicated combination of strikeouts, walks, net groundballs (groundballs minus fly balls), and their squared terms and interactions with one another

While each estimator features a batted ball component, they focus on trajectory (launch angle), not on authority (exit velocity). This is a fair assumption, frankly. I have illustrated how a pitcher can influence hitter launch angle, operating under the assumption they bear little to no influence over hitter exit velocity. It’s not quite that bleak; certified baseball genius Rob Arthur found that the average pitcher’s effect on a baseball’s exit velocity: roughly five parts hitter, one part pitcher. Read the rest of this entry »