Author Archive

2017-19 Hitter Launch Angles, Revised

Recently I outlined how the installation of Hawk-Eye as Major League Baseball’s tracking and data collection system has shed light on the issue of untracked batted ball events (BBE) in prior years. The issue was first broached by Connor Kurcon, who uses launch angle for his various research and analytical endeavors, including classified run average (CRA), dynamic hard hit rate (DHH%), and TrueHit percentage.

If you’re too lazy to click through, I’ll recap: Because Hawk-Eye tracks more than 99% of BBE, we can use the distribution of launch angles in 2020 to identify the possible launch angles of untracked BBE in previous years. Most likely, untracked BBE converge on the most extreme angles — think -90° and 90°, but with a margin for error such that some BBE as shallow as -40° (for ground balls) or 50° (for pop-ups) might have still gone untracked.

Absent the information available to us now, Tom Tango and the Statcast team devised a method that would impute exit velocity (EV) and launch angle (LA) values that most closely mimic the untracked BBE’s observed outcome by measure of weighted on-base average on contact (wOBAcon). From my observation, Statcast applied roughly half a dozen different launch angle estimates for this purpose, with two in particular used disproportionately: -21° or -20.7° (for ground balls) and 69° (for pop-ups).

Again, absent the data we now have, this was as good an approach as one could reasonably expect. But now we know untracked BBE cluster around the extremes. An imputation of 69° for pop-ups is reasonable, but -21° for grounders might not be extreme enough.

To correct for this issue in the seasons preceding 2020, I adopted an approach I recommended in my original post.

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A Needed Update on Launch Angle Tightness

As the de facto purveyor of launch angle tightness (or launch angle consistency, both terms that I use interchangeably), it is important I relay to you significant developments related to launch angles in general in 2020. Let the record show I am merely the messenger and Connor Kurcon, whose name graces these pages (or at least my pages) quite often these days, is forever my muse.

In 2020, Major League Baseball instituted its new pitch-tracking (and also ball- and player-tracking) system, Hawk-Eye. You can read about its merits here, among them being its alleged ability to “more comprehensively [track] the full flight of the ball”:

Furthermore, if the ball leaves the field of view of all 12 cameras (as can happen on high pop-ups and fly balls), the system can then reacquire the ball later in its trajectory as gravity pulls it back into the view of one or more cameras.

Hawk-Eye was expected to track more than 99% of all BBE, a significant upgrade from the previous system. Many approached the claim with skepticism. Turns out, the claim may be legit.

Kurcon noticed Hawk-Eye all but ruined the year-to-year consistency of launch angle tightness. Consistency is now inconsistent! Specifically, launch angle consistency values (calculated as the standard deviation of launch angle) have nearly universally grown larger in 2020. For the purposes of launch angle consistency, higher is worse, so it gives the appearance (if you’re looking at players individually and not at the larger picture) that a lot of players cratered a bit during the spring season. And it’s not only because of the shortened season, although the season’s length does contribute partly to the discrepancy:

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The Near-Immediate Usefulness of Max EV

Maximum exit velocity (max EV) measures a player’s hardest-hit ball, typically measured within a single season and compared against other players. Our Mike Podhorzer has documented its leaders and laggards. Rob Arthur, one of baseball’s best public analysts and whom I admire greatly, wrote intelligently on the importance of max EV as a projection-buster back in 2018. Max Freeze (real name) blends extremely hard hits (114+ mph) with launch angle to look for possible power breakouts ahead of 2020.

It has been established (by Al Melchior and me, in fact) that max EV, while an effective indicator, is not the or even a superior indicator of hitter power.

That’s not to say max EV is useless, by any means. It is altogether a different breed of metric than, say, barrel rate (Barrel%, either per plate appearance [PA] or per batted ball event [BBE]) or average exit velocity (EV), both to which fantasy baseball analysts refer much more often. The latter two, and many others, are rate metrics that need large sample sizes to become reliable — or, in common parlance, to “stabilize.” (More on that here, from our former and beloved Eno Sarris.)

Meanwhile, max EV is not a rate or average but a singular data point. It can happen at any moment in time — including the very first batted ball of a hitter’s season. This makes it an intriguing addition to the ol’ tool belt insofar as it could become “reliable” (not necessarily in the statistical sense) much sooner than would barrels or EV. Potentially, we could use max EV loosely as a leading indicator of where a hitter’s barrel rate, average EV, or even weighted on-base average on contact (wOBAcon) might eventually settle.

So: what are the merits of max EV?

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Alex Chamberlain’s Five Bold Predictions for 2020 – A Review

At this point, when it comes to bold predictions, you should know the drill. Yet it feels increasingly cliché to lead with, “you know the drill.” Nevertheless: you know the drill. We make bold predictions before the season and we review them after the season.

One thing I make a point of highlighting I try to make my predictions sufficiently bold while also actionable. “David Fletcher will hit 50 home runs” is a certifiably insane prediction, but it is not actionable because what do you do with this information? You over-draft him, sure, but by how much?

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Kyle Hendricks and Location-Based Contact Management

This month last year, Connor Kurcon of Six Man Rotation set out to quantify the location aspect of command (or “LRP”). By establishing an accounting system that credited and debited pitchers for changes in ball-strike counts based on the attack zone of and hitter’s disposition (take? swing? ball in play?) for every pitch, he effectively created an alternative to Pitch Value (PVal) that rewards optimal movement through ball-strike counts but with much more pitcher and hitter context.

His findings are as you’d expect: Jacob deGrom and Justin Verlander lead the pack, with Gerrit Cole, Max Scherzer, and Clayton Kershaw not far behind. Other budding aces like Jack Flaherty and Mike Clevinger pepper the list, and some pleasant surprises (such as Brendan McKay, Caleb Smith, and, for those still thirsting, Jake Odorizzi) are scattered throughout as well. Out of the bullpen, newly anointed relief ace Nick Anderson led the pack followed by the underrated Emilio Pagán, breakout reliever Giovanny Gallegos, and others.

Near the end of his post, Kurcon includes a subhead dedicated to Kyle Hendricks where he highlights how Hendricks, widely respected as a command artist, fares lukewarmly by measure of LRP. He then reminds us “LRP doesn’t paint the full picture of command.” True that.

Fortunately, Kurcon has left the door open for me to tie up loose ends with find Gs I’ve been meaning to write up for a couple of months now. Never fear, Hendricks is the command artist we know and love — it’s just that he relies heavily on incurring contact in optimal pitch locations. It is a needle very few pitchers can thread, but Hendricks does it masterfully.

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Jose Altuve and the Point of No Return(?)

Ominous title, I know, but in all fairness: Jose Altuve sports a paltry .207/.267/.322 (65 wRC+) line. The former consensus 2nd-overall pick who hit .298 with a career-high 31 home runs last year may seem like an unlikely collapse candidate on the surface.

Unfortunately, the cracks began to show last year. For one, Altuve all but stopped running; when he did run, he fared poorly, succeeding in only six of 11 attempts. Moreover, his .298 average, while excellent, was a far cry from his best (.346) and post-breakout five-year peak from 2014 through 2018 (.331). These are the obvious signs of wear.

A lightly critical evaluation might have concluded Altuve would still be a valuable commodity in 2020. Average draft position (ADP) data confirms this suspicion; a post-pandemic-onset ADP of 40.12 (37th overall), per the National Fantasy Baseball Championship (NFBC), ain’t nothing to sneeze at.

Yet my work on launch angle tightness in December, while illuminating and fun to research, shined a spotlight on an interesting and very specific data point: Altuve.

A tight launch angle (small standard deviation) is not always good, and a loose launch angle (large) is not always bad, but by and large the overall trend holds. Perhaps a more effective way to use tightness is to compare it historically for each player. While Altuve never had elite tightness, it was consistent, and he was an elite hitter, and that’s all that mattered. So it alarmed me to see his launch angle loosen up in 2019:

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Randy Dobnak, Probable Great American Hero

It’s easy to dismiss Randy Dobnak, to turn him into a punchline. When 99.99% of baseball fans were introduced to Dobby last fall, they learned two things:

  1. When he wasn’t pitching, he worked part-time as a ride-share driver to help pay the bills (an altogether separate indictment of MLB and its broad moral shortcomings), and
  2. He has a handlebar mustache.

That’s just enough, but also plenty, to undercut a grown man’s legitimacy. It’s this very illegitimizing, I hypothesize, that has allowed Dobnak to fly under fantasy radars, even as he demonstrates nonzero aptitude on the mound.

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Alex Chamberlain’s Five Bold Predictions for 2020

These hallowed pages have borne (bore? beared? how am I even a writer?) witness to many bold predictions — some good, most bad. Last year’s hits and near-hits include Kirby Yates, Jeff McNeil, Mike Tauchman, and Domingo German; previous hits include Jose Ramirez, Madison Bumgarner (not being an ace), Matt Chapman, and Miles Mikolas, among others, as well as other near-hits not worth repeating.

Sometimes, bold predictions aren’t entirely so. I try to make my predictions legitimately bold (bordering on impossible), actionable, and strategic. It’s not helpful for someone to boldly predict Giancarlo Stanton will hit 25 homers in a 60-game season, however fun a prediction that may be.

It’s (less than) half a season, so you get half the predictions, although I’ll include some less-bold low-hanging fruit at the end, for posterity.

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ERA Estimators, Pt. III: Future

I semi-recently had the honor of presenting at PitcherList’s PitchCon online conference to help raise money for Feeding America. My presentation, “ERA Estimators: Past, Present, and Future,” discussed, well, exactly what it sounds like it discussed. Over three posts, I will recap and elaborate upon points made in my presentation.

In the first two parts of this series (1) (2), I reviewed every manner of estimator, from the classics (FIP, xFIP, SIERA) to new-fangled doohickeys (Baseball Prospectus’ DRA, Statcast’s xERA, Connor Kurcon’s pCRA, Dan Richards‘ FRA). Today, we march forward, envisioning a future that may already be upon us.

ERA Estimators, Part III: Future

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Launch Angle, Pitch Location, and What Pitchers Can(not) Control

I spend a lot of time bothering Connor Kurcon. He’s a smart dude with a certain intuition about baseball and a certain ability to apply that intuition to produce tangible results that invariably reflect his hypotheses. He devised Predictive Classified Run Average (pCRA), an ERA estimator that outperforms the big three (FIP, xFIP, and SIERA). He also created a dynamic hard-hit rate which, to me, was astoundingly clever and a superior accomplishment to pCRA (although maybe he disagrees).

Anyway, like I said, I bother him a lot, he tolerates me, we bounce ideas off each other. The journey starts there, with my incessant annoyance of him, but also it starts here, with this Tom Tango axiom: exit velocity (EV) is the primary predictive element of hitter performance (as measured by weighted on-base average on contact, aka wOBAcon) — significantly more so than launch angle (LA). Some of the inner machinations of Tango’s mind:

I won’t speak for Kurcon, but I think this finding helped guide his work on the dynamic hard-hit rate. I also think it inspired his foray into replicating this effort for pitchers or, at the very least, his attempts to determine the most predictive element of pitcher performance. Which leads us to this tweet that (spoiler alert) is actually not stupid at all:

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