Opening Day is tomorrow, but not everyone has their legs under them just yet. Take Miguel Vargas, whom I wrote about a couple of weeks ago — he wasn’t even allowed to swing for a quarter of his spring training plate appearances. While he’s swatted three doubles and a homer since taking the bat off his shoulder, he probably wouldn’t have minded at least a handful of extra reps.
And it seems like he isn’t alone. Teams have dealt with the usual rash of injuries this spring, and a sizable portion of Opening Day bats will take the field without the benefit of a full slate of spring training plate appearances. For his part, when Vargas broke his finger, the Dodgers were able to get him some semblance of in-game experience by having him track pitches without swinging. Read the rest of this entry »
This is Kiri’s first piece as a FanGraphs contributor. She lives in the Pacific Northwest while contributing part-time to FanGraphs and working full-time as a data scientist. She spent five years working as an analyst for multiple MLB organizations.
By this point, you’ve undoubtedly consumed considerable content regarding the rule changes arriving in the majors for the upcoming season. You know all about the pitch clock dictating when hitters must ready themselves in the box and when pitchers must start their deliveries, as well as the wrinkle this introduces to pickoff attempts. You’ve also heard about the bigger bases and the limits on defensive shifting. Analysts have projected which players stand to be impacted most by the changes, while players who feel the changes make their jobs more difficult have voiced their concerns, and early spring training action has showcased the growing pains of adoption. With much of the existing commentary zooming in on the micro effects for particular players and game situations, let’s take some time to zoom out and ponder the macro effect on the game as a whole. More specifically, let’s ruminate on what makes a game or sport objectively appealing and how the rules — and subsequent changes to them — influence the appeal of a game.
At the most basic level, games are defined by rules dictating play. For those of us who struggle with authority, rules often feel restrictive. It’s no wonder, since rules come across as real haters, with all their “Don’t do this,” and “Don’t do that,” and “You can do this, but no, no, not like that.” That said, we needn’t have such an adversarial relationship with rules. In his book exploring the game of basketball, Nick Greene notes, “Games are peculiar. They are the only pursuit in which rules are used to facilitate fun.” To better understand the dynamic between rules and fun, Greene interviews a game design professor, Eric Zimmerman, who explains, “One of the paradoxes of game design is that the creativity of play is made possible by play’s opposite, which are rules. Rules are in essence constraints, but games don’t feel that way. […] When the rules are activated, what follows is fluid, unpredictable magic.” The rules of any game are finite, but the universe is infinite, implying that infinitely many possibilities exist in the space not covered by the defined rules. The fun in any game lies in the creativity used to explore the infinite space outside the boundaries set forth by the rules. Read the rest of this entry »
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):
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:
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 twoarticles. 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%.
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:
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 »
