Every time a young star signs a contract extension, we all breathlessly mention the total guarantee. Did you hear Corbin Carroll is getting one hundred and ten million dollars? You could buy a pretty nice house with that, or several nice houses, or live comfortably for the rest of your life and set your kids up to succeed in the bargain. It’s natural to focus on something like that. It is, after all, the main part of the deal.

In almost every one of these extensions, there’s an additional feature: one or more years of team options tacked on to the end of the contract. Our collective analytical view of those tends to be more or less a shrug. “Oh, yeah, and two team options, so that’s nice,” we say, or “well, that makes sense.” I wouldn’t call our evaluations of these options particularly nuanced.

I don’t think that’s going to change on the whole, but the Carroll extension spurred me to at least delve a little deeper into the dollars and cents side of those team options. I’ve already done some work on opt outs from the player perspective, and conveniently enough, I can lift a lot of the mathematical methods from that treatment and use them to evaluate things from the team side. Read the rest of this entry »

Before Miguel Vargas doubled in his first plate appearance of the day last Thursday, he hadn’t lifted the bat off his shoulder his first 12 times up. Nursing a pinky fracture, he was just there to track pitches. Yet initially, this “strategy” paid unanticipated dividends: through seven looks, he walked four times and struck out three times, good for a .571 OBP (albeit with a 42.9% K-rate). However, pitchers ultimately adjusted, sending Vargas back to the dugout the next five times.

Apparently, opposing managers were made privy to his no-swing approach before each game. But even if Dave Roberts didn’t tell them about it, it was in the press as early as the morning of February 27, after which three of Vargas’ walks came. My colleague Davy Andrews, recounting this misadventure, posited that some of the pitchers treated Vargas like any other foe because they were just trying to get into regular-season shape.

But Davy also suggested pitchers may have been a bit incredulous that Vargas wouldn’t swing, up there with his batting gloves on and in his crouch. The incredulity slipped away, though, in those last five looks. Zack Greinke even toyed with Vargas, tossing him a pair of eephuses (eephi?) sandwiched by two full-strength heaters (thanks to Davy for doing the GIF work so I didn’t have to):

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Earlier this month, I wrote about the improvements that umpires have made in calling balls and strikes according to the rulebook strike zone. Today, I’d like to focus on the other side of that equation: pitch framing. The consensus around baseball is that pitch framing’s story has followed a very familiar arc. Call it the Competitive Advantage Life Cycle:

• Teams realize the immense value of a skill.
• An arms race ensues as they scramble to cultivate it.
• The skill becomes widespread across the league.
• Since the skill is more evenly distributed, it loses much of its value.

Once everybody got good at pitch framing, nobody was great at it. As Rob Arthur has put it, “Catcher framing felt like it was disappearing almost as soon as it was discovered.” I even have fun graphs to drive the point home. There are definitely more useful ways of presenting the data, but I like how these ones let you watch the entropy dissipate over time in open defiance of the second law of thermodynamics:

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Since joining MLB as an expansion team in 1993, the Rockies have won 46.9% of their games. Among active franchises, that mark stands as the third worst. Granted, most other teams have had a lot more time to establish themselves, and the Rockies have bested their 1993 expansion counterparts in the Marlins (though given the option, they’d probably take the Marlins’ two World Series championships). But they have also been handily outpaced by the 1998 expansion teams, the Diamondbacks and the Rays, who have each posted winning percentages of 48.5%. Further, the Rockies still have the fifth-worst winning percentage even if we limit our scope to 2000 onwards. These results don’t line up with the Rockies’ spending, especially as of late, which has placed them in the middle of the pack in terms of payroll — that is, until we consider the Coors effect.

The Rockies’ pitching has long dragged down the fortunes of the team as a whole. Since 2000, they’ve easily been the worst staff in the majors with a 4.93 ERA. But it isn’t entirely their fault: pitches move sub-optimally and balls fly further in Colorado. The front office has tried various remedies, in particular opting for more groundball-heavy or low-BABIP pitchers. Neither of those strategies has worked all that well, but some proposals carry promise, like the idea of relying more on gyro spin and/or using the lesser impacts of Magnus force in Colorado in an advantageous way.

But the innovation in Denver appears to be at a bit of a standstill, possibly due to unrealistic expectations about the Rockies’ current level of competitiveness. Self-evaluation issues aside, on a recent episode of Effectively Wild, Ben Lindbergh and Meg Rowley described the Rockies as a team that could theoretically be more consistent if they truly figured out how to navigate playing half of their games at Coors. That got me thinking, and while I certainly don’t purport to provide the final answer, I do hope to supply a different perspective on the problem. Read the rest of this entry »

Last week, we published our playoff odds for the 2023 season. Those odds contain a ton of interesting bells and whistles, from win distributions to chances of receiving a playoff bye. At their core, however, they’re based on one number: win totals. Win totals determine who makes the playoffs, so our projections, at their core, are a machine for spitting out win totals and then assigning playoff spots from there.

We’ve been making these projections since 2014, so I thought it would be interesting to see how our win total projections have matched up with reality. After all, win total projections are only useful if they do an acceptable job of anticipating what happens during the season. If we simply projected 113 wins for the Royals every year, to pick a random example, the model wouldn’t be very useful. The Royals have won anywhere from 58 to 95 games in that span.

I’m not exactly sure what data is most useful about our projections, so I decided to run a bunch of different tests. That way, whatever description of them best helps you understand their volatility, you can simply listen to that one and ignore everything else I presented. Or, you know, consider a bunch of them. It’s your brain, after all.

Before I get started on these, I’d like to point out that I’ve already given our playoff odds estimates a similar test in these two articles. If you’re looking for a tl;dr summary of it, I’d go with this: our odds are pretty good, largely because they converge on which teams are either very likely or very unlikely to make the playoffs quickly. The odds are probably a touch too pessimistic on teams at the 5–10% playoff odds part of the distribution, though that’s more observational than provable through data. For the most part, what you see is what you get: projections do a good job of separating the wheat from the chaff.

With that out of the way, let’s get back to projected win totals. Here’s the base level: the average error of our win total projections is 7.5 wins, and the median error is 6.5 wins. In other words, if we say that we think your team is going to win 85.5 games, that means that half the time, they’ll win between 79 and 92 games. Past performance is not a guarantee of future results, but for what it’s worth, that error has been consistent over time. In standard deviation terms, that’s around 9.5 wins. Read the rest of this entry »

Major League Baseball will look significantly different in 2023 due to several new rules, but there’s another change that won’t attract as much attention as a pitch clock or all that steamy base-on-base action. Ten veteran umpires have retired and 10 new ones will be taking their place. I’d like to explore the effect these new umpires might have, but first, let’s look at the state of umpiring right now.

The short version is pretty simple: Since the beginning of the pitch tracking era in 2008, umpires have improved their accuracy in calling balls and strikes every single year. Accuracy has gone from 81.3% to 92.4%. If an improvement of 11.1% in 15 years doesn’t sound particularly big, consider it this way: incorrect calls have been cut by nearly 60%.

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Last week, I wrote about arm angles, Nestor Cortes, and some appearance-based expectations hitters might have about a pitcher’s craftiness. During my data mining, I also noticed that Rich Hill popped up at or near the top of many arm angle rankings. Specifically, among the 473 hurlers who threw at least 500 pitches in 2022, Hill had the broadest range of arm angles and the second-highest arm angle standard deviation. Below are his release points in colorful dot form (via Baseball Savant) and his arm angle frequencies in histogram configuration:

Hill typically comes at hitters from a three-quarters slot, though he does near a completely overhand slot at times. When he drops down, he provides his foes with anything from a sidearm to a fully submarine look. Cortes, for his part, placed second in range (just 0.4 degrees behind Hill) and fourth in standard deviation (2.5 degrees behind). But as you can see below, Cortes’ more significant drop-downs were not only less frequent than Hill’s but also closer to a more typical Cortes look. Whereas Hill has a very obvious gap between his drop-down and standard release, Cortes runs the gamut of angles between the two:

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For the past few weeks, I’ve been delving into exit velocity readings in an attempt to find out what really matters and what’s just noise. I found that 95th-percentile exit velocity and contact rate are the two stickiest metrics from one year to the next, with exit velocity slightly more likely to remain the same from one year to the next.

Of course, that doesn’t mean it can’t change. In fact, players change their top-end power readings by a good amount every year. Sure, any individual player might be unlikely to do it, but there are tons of players in baseball. I found that only 4% of hitters change their 95th-percentile exit velocity (EV95) by one standard deviation from one year to the next, but 408 batters put at least 100 batted balls into play in 2022. Four percent of 408 is a lot more than zero.

With that in mind, I thought I’d take an inventory of those exit velocity changers and see what their improvement meant going forward. To do so, I created two groups: hitters whose EV95 improved by at least half a standard deviation from one year to the next, and the opposite, hitters whose EV95 declined by at least half a standard deviation. I picked half an SD instead of an entire one to bulk up the sample size. Read the rest of this entry »

Last week, pitching prospect Grayson Rodriguez was asked a great question on The Baseball Barb-B-Cast. Rodgriguez is ranked third in an excellent Baltimore system, and as a player who was drafted in 2018, his tenure with the club spans both the Dan Duquette and Mike Elias eras. The question was: How has the organization changed over time?

Rodriguez started his answer with, “Everything about the organization changed but the name.” He touched on technology, pitch development, and the turnover in the coaching staff, but the part I want to focus on came right at the beginning, when he was describing the Duquette era: “Our pitching philosophy was, it was like, ‘Hey, you know, as a starter we’re going to go out in the first three innings and we’re just going to throw nothing but fastballs, and we’re going to see if that works.’ And, like, terrible. Terrible idea.”

Yup. That does indeed sound like a terrible idea. It also made me wonder whether teams are as focused on establishing the fastball as they once were. A reduction in first inning fastball rate would make sense for a couple reasons. First, fastball usage has dropped overall as teams have learned that pitchers should throw their best pitch more often, and fastballs themselves have become less effective:

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Originally a 36th-round pick in the 2013 draft by the Yankees, Nestor Cortes spent time with the Orioles and Mariners before returning to the Bronx and putting it all together toward the end of the 2021 season, his age-26 year. Even upon breaking out, he was dubbed an “everyman” by the New York Post, overlooked by scouts because he didn’t stand as tall as other hurlers and because he lacked overpowering velocity. Yet in 2022, Cortes mowed hitters down to the tune of a 2.44 ERA and 20.3% K-BB rate. Far from an everyman, he was a standout athlete.

The southpaw’s breakout wasn’t a product of a mid-career growth spurt. If anything, his emergence came in spite of his 5-foot-11 height; his 159 ERA+ in 2022 tied him for the 27th-best mark among sub-six-foot hurlers since the Live Ball era began in 1920. Rather, the most concrete reasons for Cortes’ improvements include a velocity jump in both 2021 and ’22 (though his velo is still below average) and the introduction of a cutter paired with a revamped slider. Yet despite the ambiguous impact it has on his game, what perhaps differentiates Cortes the most from other pitchers is his approach on the mound, including but not limited to his varying arm angles.

The hurler’s drop-down moves have been the subject of many an article, including Lucas Kelly’s piece on this very site. The discussion on arm angles more broadly, however, has been rather muted, save for Logan Mottley’s (now of Fanatics, previously of the Texas Rangers) post describing how they can be calculated from Statcast data and Ben Palmer’s piece for Pitcher List digging into the Mottley data.

Even in these articles, there is no mention of how stature might play into the effectiveness of certain arm angles. Instead, there seems to be an implicit assumption that if one arm slot proved more effective on average (which, to be fair, no one has concluded), it should automatically be utilized more, without regard for what might feel most natural for a given pitcher. What would happen if we tried to convert more pitchers to a sidearm slot, or at least push them to vary their arm slots a la Cortes? Using Mottley’s calculations, I took a crack at these questions myself. Read the rest of this entry »