# Let’s Talk About Launch Angle Generally

**Edit:** Further investigation has brought to my attention that the results presented below are slightly askew, although not incorrect. All discussion below regarding hit frequency (BABIP) and contact quality (expected wOBA on contact, or xwOBAcon) should have been framed specifically in the context of non-home run batted ball events. This is significant, because home runs are a big deal, but it’s also insignificant. Allow me to explain.

When we re-include home runs, the relationship between launch angle tightness (stdev[LA]) and contact quality weakens dramatically. I think it comes down to the graph shown in the middle of the post below. Removing home runs narrows the range of productive launch angles, thus making a tighter range of launch angles (confined primarily to line drives) more appealing. When you include home runs, it expands the range of productive launch angles to include productive fly balls in addition to productive line drives. There’s literally more margin for error when we reconsider home runs, making a tighter range of launch angles was valuable.

That doesn’t mean launch angle tightness isn’t important! If anything, removing home runs was a nifty way to demonstrate this fact.

Anyway, I have updated this post with red text to clarify that references to contact quality exclude home runs — and that the findings from this post are technically correct, just through a certain lens.

* * *

Last week, I published some work regarding launch angle “tightness,” aka a hitter’s ability to replicate his average angle as closely as possible as often as possible. Effectively a measure of consistency, I found launch angle tightness (consistency, variance, whatever you want to call it) bore a moderately strong relationship with batting average on balls in play (BABIP).

Truth be told, I began to question my finding almost immediately for reasons I’ll discuss shortly. After inquiries from The Athletic’s Eno Sarris, FantasyPros/PitcherList’s Nick Gerli, and even Cody Asche (this is the mildest of brags) that echoed my internal self-doubting dialogue, I dove into the question further.

Ultimately, the best explanation for the importance of launch angle consistency is to simply elaborate upon launch angle generally. So, consider this a de facto primer on launch angle. It’s probably not the first and certainly won’t (or shouldn’t) be the last. But in the context of my post from last week, it simply makes sense to bring the conversation full circle and wrap it up nicely with a bow. And the final result is gratifying, I hope.

Enjoy (or not, I’m not your dad):

### More consistent launch angle → higher BABIP.

This is the conclusion I drew after observing a moderately strong relationship (r² = 0.25) between launch angle consistency (measured in terms of standard deviations from the mean) and BABIP. As noted, I began to question this outcome as soon as Joey Votto’s name rose to the top of the list of most-consistent launch angles. Votto is the King of Never Popping Up. Pop-ups are automatic outs. If you prevent automatic outs, your BABIP will undoubtedly be higher.

So, I pursued Sarris’, Gerli’s, Asche’s, and my brain’s separate-but-identical hypothesis: how strong is the relationship between launch angle consistency and *specifically* pop-up percentage (PU%)?

Extremely strong.

### Clarification: More consistent launch angle → __lower PU%__ → higher BABIP.

Launch angle tightness explains half of the variance in a hitter’s pop-up rate (r² = 0.50), and pop-up rate explains almost 40% of the variance in a hitter’s BABIP (r² = 0.39). If you calculate a BABIP that excludes pop-ups and measure its relationship with launch angle tightness, the relationship is incredibly weak (r² = 0.05).

The finding begs a chicken-and-egg question of the causal relationship of launch angle and pop-ups. Which one explains the other? Pop-ups and steep launch angles are one in the same. Does launch angle tightness simply restate another metric that already exists (namely, pop-up rate)? Am I wasting my time here?

Yes and no. Because launch angle tightness bears such a strong relationship to pop-ups, it’s probably not worth using it in lieu of pop-ups to measure the skill and/or luck in a hitter’s BABIP. However, in the absence of data that captures a hitter’s swing plane, I think launch angle consistency is the best proxy we have for bat control.

Moreover, launch angle consistency clearly begets a low pop-up rate. But a low pop-up rate does not necessarily beget a consistent launch angle — it could also simply denote a shallow launch angle.

### Steep average launch angle → higher PU%.

This one is pretty intuitive: a hitter with a steeper average launch angle hits more fly balls, and a hitter who hits more fly balls will inevitably hit more pop-ups than a ground ball-oriented hitter. The relationship between average launch angle and PU% is also quite strong (r² = 0.37). That means a hitter whose launch angle is steep *and* inconsistent might pop-up very frequently. Meanwhile, a hitter whose launch angle is steep *but also* consistent might have more of a tug-of-war between the positive and negative effects of launch angle as it related to pop-ups (and, thus, BABIP).

Which brings us to perhaps the most important question: which launch angle(s) is (are) best?

### It’s complicated (but the answer, in a vacuum, might be 19°).

For BABIP, the sweet spot for launch angle is roughly 12° or 13°. Roughly 79% of balls in play (remember, BABIP excludes home runs) at these angles turn into hits (~.790 BABIP), making them highly effective. This effectiveness drops off precipitously the farther you stray from the peak. Add or subtract 6° and you lose nearly 250 points of BABIP.

The average batted ball hit between the launch angles of –4° and 26° will typically run a BABIP north of .300, the usual league average. That means a hitter who can maximize the number of batted balls hit between these angles will probably have an above-average or elite BABIP.

That doesn’t mean this is the best approach, though. Whereas BABIP measures frequency of hits, expected weighted on-base average (xwOBA) on contact (xwOBAcon, for short) measures *quality* of hits. And the highest quality of contact on non-home runs occurs between the launch angles of 26° and 31°, and slowly widens as exit velocity increases.

The graph below plots launch angle against BABIP and xwOBAcon (on all batted balls, including home runs). The measurements account for all exit velocities, effectively showing the average outcome for the average batted ball at each launch angle, rounded to the nearest degree.

You can see how BABIP and xwOBAcon peak together at roughly 12°–13°, as aforementioned. You can also see how xwOBAcon experiences a *second* peak as BABIP drops off precipitously, also as aforementioned. This is fundamentally the difference between a productive line drive and a productive fly ball. At the perfect angle, each one can be productive as the other. But they will show up quite differently on the stat sheet — one in the form of more hits but less power (BABIP), the other in the form of more power but fewer hits (xwOBAcon).

Having given the image above a thorough ocular pat-down (and having been sufficiently spoiled by my annotations), it seems the most ideal average launch angle might be around the 19° mark. A swing plane that caters specifically to this magic number would afford itself a margin for error (6° or 7° in either direction) that would create a lot of good mistakes in the the form of optimized line drives and fly balls. This is the perfect marriage of swing plane and bat control: finding the perfect launch angle and replicating it as closely as possible as often as possible. Twenty-five degrees might also work — a ~.775 xwOBAcon and ~.350 BABIP with play, y’all — but the margin for error north of 25° is much slimmer, and no hitter is truly special enough to tighten up their launch angle enough to avoid the dire consequences of too-steep angles.

Hitters with average launch angles closest to 19° in 2019, in ascending order: Anthony Rendon, Mookie Betts, Kris Bryant, Hunter Renfroe (maybe the Rays, who traded away Tommy Pham to acquire Renfroe, are playing 4D Chess???), Alex Bregman, José Ramírez, Matt Olson, Eduardo Escobar, Gary Sánchez, Max Kepler, Eugenio Suárez, Jorge Polanco, Cavan Biggio, Omar Narváez, Andrew Benintendi, Willie Calhoun, Cody Bellinger…

### Some hitters, regardless of their natural launch angle (swing plane), are better able to limit pop-ups than others.

Remember, while launch consistency relates strongly to BABIP and pop-up rate, they don’t explain each other entirely. There are other variables at play, suggesting two things: (1) that some variables remain unaccounted for, which makes sense, given I only accounted for one; and, (2) that some hitters are naturally superior.

### Is launch angle consistency predictive?

Yes and no. It is incredibly sticky year to year (r² = 0.47) — it is strongly predictive of itself — which suggests a big negative change in a hitter’s launch angle consistency (such as the one José Altuve suffered in 2019) might be a foreboding sign of decline. Or! It might be an indicator of injury. Or! It might be noise. There are a lot of possibilities. Sometimes we don’t know the actual answer until after the fact.

Launch angle consistency is weakly predictive of next-year BABIP (r² = 0.09), which is OK, except that both BABIP and PU% are more predictive, even if also weakly (r² = 0.16 and r² = 0.14, respectively), which makes launch angle consistency *specifically as a leading indicator of BABIP* not necessarily a good one. It doesn’t make it worthless, especially if we consider all the moving parts to hitter performance.

In fact, __maybe the lens through which we need to evaluate launch angle tightness is through not BABIP but xwOBAcon (on non-home runs)__. Launch angle consistency correlates better with both current-year and next-year xwOBAcon on non-home runs (r² = 0.33 and r² = 0.16, respectively) than it does with current-year and next-year BABIP (r² = 0.25 and r² = 0.09). It also correlates better with xwOBAcon on non-home runs than either BABIP or PU% do, both current-year (r² = 0.23 and r² = 0.15) and next-year (r² = 0.04 and r² = 0.06).

### There’s so much info here, Alex. Just tell me what you want me to know!!!!!

Sorry! Sorry.

Launch angle tightness strongly describes and predicts BABIP. However, launch angle tightness correlates strongly with pop-up percentage, and pop-ups describe and predict BABIP even better than launch angle tightness does (even if only slightly better). It feels redundant to use one in lieu of the other.

However, lots of pop-ups does not necessarily tell us a hitter has an inconsistent launch angle. It could simply mean he has a steep launch angle. Both correlate strongly with pop-ups, so saying a hitter pops up does not clearly communicate the details of his launch angle. Is it steep? Inconsistent? Both? Neither?

Ultimately, it turns out the true focus of this analysis should have been contact quality, not hit frequency. Launch angle consistency tells us a lot about a hitter’s productivity on non-home run batted ball events (BBEs) — way more than BABIB or PU% do, both for descriptive and predictive purposes. A tight launch angle typically produces a higher BABIP, yes, but it also has a larger positive impact on contact quality.

So, launch angle tightness: it’s good!

Currently investigating the relationship between pitcher effectiveness and beard density. Two-time FSWA award winner, including 2018 Baseball Writer of the Year, and 8-time award finalist. Featured in Lindy's magazine (2018, 2019), Rotowire magazine (2021), and Baseball Prospectus (2022). Tout Wars competitor. Biased toward a nicely rolled baseball pant.

What happens if you split that graph of BABIP vs wOBAcon into separate graphs for pulled, middle, and opposite-field balls?

I have two comments (yours and another) related to different permutations of that graph, so maybe I’ll make a dynamic chart people can use to toggle spray angle and EV, just to watch the graph change shape. Putting it on the to-do list.