Last week, I wrote about the Padres and how their usage of the infield shift stands out. To recap: They shift almost exclusively against left-handed hitters to great success, neglecting right-handed ones in the process. This decision is backed up by public research, which casts doubt on the efficacy of shifts against righties.

As a few of the comments noted, though, the Padres aren’t the most interesting subject when it comes to shifts. If anything, they’re conformists! The Dodgers and Rays, in contrast, are the rebels who defy convention by shifting more against righties than against lefties. We still don’t have a clear answer as to why. Leading up to this article, I did take a crack at the problem, and in the process, unearthed something about the Dodgers.

Before that, some context: Much of our discourse regarding the shift is focused on the dynamic between the hitter and team shifting against him. Kole Calhoun has a tendency to pull the ball, so the Dodgers have prepared this alignment. If Calhoun could go the other way, he’d earn himself a free knock, and so on.

But what about a version of the dynamic that includes the pitcher? By the same logic applied to hitters, if a pitcher could alter his approach to induce pulled grounders that are tailor-made for infield shifts, he’d probably be successful. We know pitchers can control the types of batted balls they allow to some extent: Last season, our Alex Chamberlain wrote about the relationship between pitch location and launch angle. As it turns out, a lower pitch will yield a lower launch angle compared to one located higher up, irrespective of pitch type.

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Seemingly in the blink of an eye, a month of baseball is behind us. With nearly 30,000 plate appearances taken and more than 18,000 batted balls put into play, a month of data is plenty to begin examining league-wide trends and to make some predictions for the rest of 2021.

One big question going into this season — and a topic already examined here by both Ben Clemens and Justin Choi — was what the impact of the new baseball would be on the overall offensive environment. As both Ben and Justin found and detailed, the new baseball is bouncier, yielding higher exit velocities than in years past, and also possesses more drag, as it is not traveling as far. I want to focus on that second point. If the ball isn’t traveling as far, we should be seeing fewer home runs hit in 2021 — and we are. But can we pinpoint just how many home runs will be hit this season? That takes a bit more guesswork, but before getting into that, let’s first see how April 2021 stacks up to prior seasons, as well as identify where exactly we lost those home runs.

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Pitchers are relying on their best pitches more and more. And why should they not? It makes all the sense in the world. Throwing a fastball 60% of the time just so that you can “establish it” is an outdated moniker that players and teams alike are reticent to follow. Take a look at the our season stat grid tool if you want proof that the most dominant pitchers in the league are increasingly relying on their breaking pitches. Select curveballs and you will see Julio Urías, Zack Greinke, Brandon Woodruff, Anthony DeSclafani, Dylan Bundy, Walker Buehler, Corbin Burnes, and John Means toward the top of the list. For sliders, that list features Tyler Glasnow, Lance McCullers Jr. (who is also throwing a new slider), Shane Bieber, a new and improved Jeff Hoffman, Freddy Peralta, and even Clayton Kershaw, whose slider is almost 45% of his pitch diet.

These are cherrypicked examples; not every pitcher on this leaderboard has been as productive as those starters thus far. But it does point to the idea that the best pitchers MLB has to offer are increasingly leaning into their best secondary offerings and have either continued to be successful or found another level in their production.

The idea of simply throwing your best pitch has become more in vogue in recent years. Back in 2017, Eno Sarris wrote that pitchers should try making breaking balls 80% of their total pitch mix. Part of the reason is that non-fastball pitches, specifically breaking balls, have gotten increasingly harder to hit; Ben Clemens wrote about this trend a couple of years ago. Even though fastballs have become harder to hit by virtue of increased velocity, pitchers are turning away from them in favor of other offerings.

This decision raises the question: Are pitchers successful with their non-fastball pitches because they use them less? The idea is that the main driver of offspeed or breaking ball success would be that hitters see them less, making them tougher to adjust to in a plate appearance. Theoretically, then, if a pitcher goes primarily to his secondary pitches, those pitches will become less effective on a per pitch basis. Is this true?

To investigate, I took every pitch type that was thrown at least 100 times in a season from 2018 through ’20. I took the year-over-year changes in pitch usage, swinging-strike rate, and run value per 100 pitches thrown for each season pair (where in both seasons the pitch was thrown on 100-plus occasions).

The first thing I wanted to look at was effectiveness based on changes in usage for each individual pitch type. The short answer to this is that there is little relationship between marginal usage change and marginal success in either of the two measures for any pitch type.

If anything, changeups and curveballs actually induce swinging strikes as a higher percentage of all pitches with more usage. That is the strongest relationship in this dataset, and it still consists mostly of noise. Based on the data, there is no evidence that pitchers should be dissuaded from throwing their best pitches more often, and that holds true for breaking balls, offspeed pitches, and fastballs.

Sure, you may argue, throwing any pitch a little more won’t have adverse effects on its effectiveness, but aren’t there diminishing returns? At a certain point, don’t you throw the pitch too often to fool the batter? To answer that, I placed each pitcher and pitch type pair into a bucket based on usage, then separated the bucket into increments of 10% (so the first consisted of pitches thrown between 0 and 10% of the time, the second 10% and 20%, etc.). I then grouped the pitch usages across the three seasons and looked for any potential deviations in effectiveness.

Again, these relationships are mostly noise. Even for pitches thrown upwards of 70% to 80% of the time (beyond which the the data is scarce), they should not lose any per-pitch potency by virtue of increased predictability.

For those of you skeptical that fastballs make up the majority of pitches and that this lack of a relationship may not be evident with breaking balls or offspeed pitches specifically, I have bad news for you:

As with run values, there’s no strong relationship between swinging-strike rate and usage.

As noted above, fastball usage is on the decline throughout the league. But using the data I collected from ’18 through ’20, it’s clear that pitchers aren’t all now throwing breaking pitches all the time.

The vertical lines represent the 50th percentile in that specific distribution. On average, pitchers using a certain breaking ball less than 30% of the time shied away from using the pitch more. On the other hand, breaking ball usage mostly increased for players who used it more than a cursory amount. That all makes sense: If you have a breaking ball you like to use (or are comfortable using), you’re going to throw it more; if you don’t have a strong breaking pitch, then you’re not going to be tossing it all the time even if it could theoretically be more effective.

Throwing a pitch just for the sake of throwing it is not going to fly in MLB in 2021. Pitches are thrown with a purpose: generating whiffs, or at least groundballs. This is one of the fundamental factors in the ever-increasing strikeout rate: Not only are pitchers throwing harder than ever, but they are also leaning on their best stuff even more. That’s while every one of those pitches is being optimized with the help of technology to generate maximum movement and deception. And that trend will not stop until there is evidence that a pitch will perform worse upon increased usage. Barring that, pitchers across the league will rely on the pitches they deem most dominant.

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.

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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 »