Revisiting the Kirby Index | FanGraphs Baseball

Proper after FanGraphs printed my piece on the Kirby Index, the metric’s namesake misplaced his contact. George Kirby’s trademark command — so dependable that I felt snug naming a statistic after him — fell off a cliff. Whereas the stroll fee remained beneath management, the house run fee spiked; he allowed seven dwelling runs in Might, all on pitches the place he missed his goal by a major margin.

Watching the namesake of my new metric flip mediocre instantly following publication was among the many many humbling experiences of publishing this story. However, I needed to revisit the piece. For one, it’s December. And writing the story led me down a captivating rabbit gap: Whereas I realized that the Kirby Index has its flaws, I additionally realized a ton about up to date efforts to quantify pitcher command.

However first, what’s the Kirby Index? I discovered that launch angles, in live performance with launch peak and width, virtually completely predicted the situation of a pitch. If these two variables advised you virtually all the things concerning the location of a pitch, then a measurement of their variation for particular person pitchers might theoretically present novel details about pitcher command.

This obtained a number of folks mad on Twitter, together with baseball’s eminent physicist Alan Nathan and Greg Rybarczyk, the creator of the “Hit Tracker” and a former member of the Crimson Sox entrance workplace. These two — significantly Rybarczyk — took challenge with my use of machine studying to make these predictions, arguing that my use of machine studying prompt I didn’t perceive the precise mechanics of why a pitch goes the place it goes.

“You’re spot on, Alan,” wrote Rybarczyk. “The amazement that trajectory and launch parameters are strongly related to the place the ball finally ends up can solely come from individuals who see monitoring knowledge as columns of digits moderately than measurements of actuality that mirror the underlying physics.”

Whereas the tone was a bit a lot, Rybarczyk had a degree. My “amazement” would have been tempered with a extra thorough understanding of how Statcast calculates the situation the place a pitch crosses dwelling plate. After publication, I realized that the nine-parameter match explains why pitch location might be so powerfully predicted by launch angles.

The situation of a pitch is derived from the preliminary velocity, preliminary launch level, and preliminary acceleration of the pitch in three dimensions. (These are the 9 parameters.) Launch angles are calculated utilizing preliminary velocity and preliminary launch level. As a result of the situation of the pitch and the discharge angle are each derived from the 9P match, it is sensible that they’d be virtually completely correlated.

This led to an affordable critique: If launch angles are location data in a distinct type, why not simply apply the identical strategy of measuring variation on the pitch places themselves? This can be a truthful query. However utilizing places would have undermined the conclusion of that Kirby Index piece — that biomechanical knowledge like launch angles might enhance the precision of command measurements.

Groups, with their entry to KinaTrax knowledge, might create their very own model of the Kirby Index, not with implied launch angles derived from the nine-parameter match, however with the place of wrists and arms captured in the intervening time of launch. The Kirby Index piece wasn’t nearly creating a brand new strategy to measure command; I needed it to level towards one particular method that the brand new knowledge revolution in baseball would unfold.

However sufficient about that. It’s time for the leaderboards. I eliminated all pitchers with fewer than 500 fastballs. Listed here are the highest 20 within the Kirby Index for the 2024 season:

And listed below are the underside 20:

A number of takeaways for me: First, I’m so grateful Kirby obtained it collectively and completed within the prime three. Demise, taxes, and George Kirby throwing fastballs the place he needs. Second, the highest and backside of the leaderboards are satisfying. Cody Bradford throws 89 and lives off his elite command, and Joe Boyle — properly, there’s a motive the A’s threw him in as a bit within the Jeffrey Springs commerce regardless of his otherworldly stuff. Third, there are guys on the laggard checklist — Seth Lugo and Miles Mikolas, particularly — who look misplaced.

Mikolas lingered across the backside of the leaderboards all yr, which I discovered curious. Mikolas, in any case, averages simply 93 mph on his four-seam fastball; one would think about such a man would want to have elite command to stay a viable main league starter, and that league-worst command successfully could be a dying sentence. Complicated this additional, Mikolas prevented walks higher than virtually anybody.

Why Mikolas ranked so poorly within the Kirby Index whereas strolling so few hitters might in all probability be the topic of its personal article, however for the needs of this story, it’s in all probability sufficient to say that the Kirby Index misses some issues.

An instance: Mikolas ranked second amongst all pitchers in arm angle variation on four-seam fastballs, suggesting that Mikolas is deliberately altering his arm angle from pitch to pitch, seemingly relying on whether or not the hitter is left-handed or right-handed. This is only one motive why somebody would possibly rank low within the Kirby Index. One other, as I discussed within the unique article, is {that a} pitcher like Lugo is likely to be aiming at so many various targets that it fools a metric just like the Kirby Index.

So: The Kirby Index was a enjoyable train, however there are some flaws. What are the options to measuring pitcher command?

Location+

Location+ is the business commonplace. The FanGraphs Sabermetric library (an unbelievable useful resource, it should be stated) does a fantastic job of describing that metric, so I’d encourage you to click on this hyperlink for the total description. The quick model: Run values are assigned to every location and every pitch kind primarily based on the depend. Every pitch is graded on the stuff-neutral places.

Implied location worth

No person appears significantly happy with Location+, together with the creators of Location+ themselves. As a result of every depend state and every pitch kind makes use of its personal run worth map to distribute run worth grades, it takes a brilliant very long time for the statistic to stabilize, upward of tons of of pitches. It additionally isn’t significantly sticky from yr to yr.

The latest model of Location+, which can debut someday within the close to future, will use an analogous logic to PitchProfiler’s command mannequin. Basically, PitchProfiler calculates a Stuff+ and a Pitching+ for every pitcher, that are set on a run worth scale. By subtracting the Stuff+ run worth from the Pitching+ run worth, the mannequin backs into the worth a pitcher will get from their command alone.

Blobs

Whether or not it’s measuring the usual deviation of launch angle proxies or the precise places of the pitches themselves, this methodology will be outlined because the “blob” methodology, assessing the cluster tightness of the chosen variable.

Max Bay, now a senior quantitative analyst with the Dodgers, superior the Kirby Index methodology by measuring launch angle “confidence ellipses,” permitting for a extra elegant unification of the vertical and horizontal launch angle parts.

Miss distance

The central concern with the Kirby Index and all of the blob strategies, as I acknowledged on the time, is the only goal assumption. Ideally, as an alternative of taking a look at how carefully all pitchers are clustered round a single level, every pitch could be evaluated primarily based on how shut it completed to the precise goal.

However targets are laborious to return by. SportsVision began monitoring these targets within the mid-2010s, as Eno Sarris outlined in his piece on the state of command analysis in 2018. Nowadays, Driveline Baseball measures this working alongside Inside Edge. Inside Edge deploys human beings to manually tag the goal location for each single pitch. With these knowledge in hand, Driveline can do a few issues. First, they created a Command+ mannequin, modifying the imply miss distances by accounting for the issue of the goal and the form of a pitch.

Utilizing meant zone knowledge, Driveline additionally reveals pitchers the place precisely they need to purpose to account for his or her miss tendencies. I’m advised they are going to be producing this technique in a public submit quickly.

Catcher Targets (Pc Imaginative and prescient)

In an ideal world, computer systems would substitute human beings — wait, let me attempt that sentence once more. It’s costly and time-intensive to manually monitor targets by way of video, and so for good motive, miss goal knowledge belong to those that are keen to pay the value. Pc imaginative and prescient strategies current the potential to supply the information cheaply and (due to this fact) democratically.

Carlos Marcano and Dylan Drummey launched their BaseballCV challenge in September. (Drummey was employed by the Cubs shortly thereafter.) Joseph Dattoli, the director of participant improvement on the College of Missouri, provided a contribution to the challenge by demonstrating how laptop imaginative and prescient might be used to tag catcher targets. The one limitation, Joseph identified, is the computing energy required to comb by way of video of each single pitch.

There are some potential issues with any command measurement depending on goal monitoring. Targets aren’t at all times actual targets, extra like cues for the pitcher to throw towards that common course. However Joseph will get round this concern by monitoring the catcher’s glove in addition to his middle of mass, which is much less prone to those kinds of dekes. Nonetheless, there’s a strategy to go earlier than this methodology scales right into a type the place day by day leaderboards are accessible.

The Powers methodology

Absent a raft of public details about precise pitcher targets, there as an alternative will be an effort to simulate them. In his 2023 presentation, “Pitch trajectory density estimation for predicting future outcomes,” Rice professor Scott Powers proposed a way to account for the random variation in pitch trajectories, within the course of providing a framework for simulating one thing like a goal. (I’ll seemingly butcher his strategies if I attempt to summarize them, so I’d encourage you to look at the total presentation should you’re .)

The Powers methodology was modified by Stephen Sutton-Brown at Baseball Prospectus, who used Blake Snell for example of the way in which these concentrating on fashions will be utilized at scale to evaluate particular person pitchers. First, Sutton-Brown match a mannequin that created a world goal for every pitch kind, adjusting for the depend and handedness of every batter. Then, for every pitcher, this international goal was tweaked to account for that pitcher’s tendencies. Utilizing these simulated targets, he calculated their common miss distance, permitting for a separation of the run worth of a pitcher’s targets from the run worth of their command means.

“Nothing”

On Twitter, I requested Lance Brozdowski what he noticed because the gold commonplace command metric. He answered “Nothing,” which sums up the issue properly. This can be a difficult query, and all the present strategies have their flaws.

There are methods that the Kirby Index might be improved, however so far as I can inform, the easiest way ahead for public command metrics is a few form of mixture of the ultimate two strategies, with lively monitoring of the pc imaginative and prescient developments to see if constant targets will be established.

However one would think about the story is totally completely different on the crew aspect. By marrying the KinaTrax knowledge with miss distance data, these strategies might doubtlessly be mixed to make some form of tremendous metric, one which I think about will get fairly near measuring the true command means of main league pitchers. (In a video from Wednesday, Brozdowski reported on a number of the potential of those knowledge for measuring and enhancing command, in addition to their limitations.) The general public may not be fairly there, however so far as I can inform, we’re not that far off.