Here Is Your Fly-Ball Revolution
My sense is that the fly-ball revolution isn’t something I even need to explain. You know the argument, you know the theory, and you know about some of the most successful cases. Ground balls are mostly unhelpful, right? So why not…not…hit ground balls? Francisco Lindor has attempted to stop hitting ground balls. He’s doubled his home-run total, from 15 to 30. Good luck finding someone who scouted him in the minors who thought he’d hit for that kind of pop.
Yet, largely, the fly-ball revolution’s very existence feels anecdotal. One can’t help but notice the league-wide numbers, and how little they’ve shifted. Compared to last year, this year’s average ground-ball rate is down half a percentage point. The league has hit 44% ground balls. A decade ago, the league hit 44% ground balls. Who cares? Is anything actually going on?
It is. It’s just a little bit hidden. Thanks to the wonders of Statcast, we can see where the league has been actively changing.
As is always the case, Statcast information has been pulled from Baseball Savant. Information exists for the better part of three years, and although three years isn’t very much, we can still put the data set to use. Let’s begin with simplicities. Here are the league-average launch angles, by season.
- 2015: 10.1 degrees
- 2016: 10.8
- 2017: 11.1
Slightest hint of a trend there. The fact of the matter is that launch angle has increased by one degree from a couple years ago. But this isn’t the kind of thing you’d notice if you didn’t go looking for it. It’s subtle. And to go with the above, here are the league-average exit velocities, by season.
- 2015: 87.3 miles per hour
- 2016: 87.7
- 2017: 86.7
Pretty weird, right? Between 2015 and 2016, league-wide isolated power increased, and league-wide exit velocity increased. Between 2016 and 2017, league-wide isolated power has increased again, yet league-wide exit velocity has decreased, by a full tick. A full tick feels substantial. If the numbers are to be believed, this year’s hitters are hitting the ball more weakly than they used to. Suffice to say I found that surprising.
Yet, that trend can be analyzed further. Let’s take it as granted that exit velocity is down, overall. Exactly where is it down? Is it down by a similar amount across all launch angles? In the following plot, I’ve gone with the bucketing method. I’ve combined 2015 and 2016, and compared those years against 2017. Here is exit velocity by launch angle.
At the lowest angles, EV is down more than two ticks. To be precise, it’s down 2.4. Between the angles of -30 and -20 degrees, EV is down 2.0. Then, going left to right, down 1.5, then down 0.3. Then on and on, until eventually it’s down just 0.1, then up 0.3, then up 0.5. At the very highest angles, batters have hit the ball slightly harder. It’s very slight, but the trend is consistent. Moving left to right in the plot, the differences get decreasingly negative, and eventually positive.
It’s worth taking a look at frequencies, as well. How have batted balls been distributed, by launch angle? This plot does the same as above.
At the lowest angles, you see an increase in frequency in 2017. But then there’s a pretty significant decrease between -20 and 0 degrees. At all positive angles, there’s been some kind of increase. The way I interpret this is that hitters are indeed trying to hit more balls in the air. I think the increases at the lowest angles reflect mis-hits. If you try to hit a ball in the air but get your timing wrong, you’re likely to hit a weak grounder, and a weak grounder frequently goes almost straight down. This is a theory of mine, and it’s far from being anything proven, but we’re seeing more air-ball contact and lousy ground-ball contact, while also seeing less decent-grounder contact. I doubt that’s a coincidence.
In case you’re curious, here’s how wOBA on batted balls has changed, again by launch angle.
I don’t know how to explain the increase between -20 and -10 degrees. I’m open to your interpretations. Otherwise, everything looks stable, until you get to 20 degrees or so. This is true even if you compare 2017 against just 2016, when the home-run spike truly blossomed. Production is up significantly between 20 and 30 degrees, and it’s also up significantly between 30 and 40 degrees. These are the home-run angles, the extra-base-hit angles. Therefore, there’s more damage to chase at higher angles, and this is why batters want to hit more balls in the air in the first place. In part, I think this reflects intentionality — batters are doing better at those high angles because they’re trying to do better at those high angles. And, in part, I think this reflects why the high angles are even increasingly desirable. The ball’s taking off like never before. Anyone who used to have even middling power is now far more of a home-run threat. Recall, again, the 30 home runs by Francisco Lindor. He wouldn’t even be trying to do this if there weren’t something substantial for him to gain.
The fly-ball revolution is happening. It’s just in the earlier stages, and you have to work in order to find it. It’s not like the league can ever just completely stop hitting balls on the ground; pitchers have a say, too, and they want the hitters to not be productive. There are opposing forces at play. But, remember how the league-wide average launch angle is up 0.3 degrees, compared to last year? Looking only at balls hit at least 90 miles per hour, the league-wide average launch angle, compared to last year, is up 1.5 degrees. The good contact is finding more air, which is the whole point. Bad contact can stay on the ground. If it’s bad enough, it can even go all the way back around to good. Batters, increasingly, are chasing liners and flies. It’s happening, and it’s probably far from finding its own equilibrium.
Jeff made Lookout Landing a thing, but he does not still write there about the Mariners. He does write here, sometimes about the Mariners, but usually not.



Angle uber alles!
It’s the data prior to the juiced ball appearance in 2015 or so that would extend this analysis into really revealing territory. One also ought to see some evidence of the effect in the weighting coefficients that go into the calculation of wOBA.
Ground ball pitchers like Clayton Richard should clean up this winter in free agency!
This is the type of study that will begin to get more players to try to change their approach. The numbers are conclusive in regards to the limited value of ground balls. There can be no reason not to attempt to increase launch angle when evidence is beginning to build up in support of what Daniel Murphy, J.D. Martinez, Francisco Lindor and an increasing group of other players have shown to be effective. I watched Lindor play about a dozen games at Double-A and Triple-A and I would have taken a bet that he wouldn’t hit 30 HR’s in his career, much less in a single season.
30-HR Lindor isn’t a better hitter than the guy of 2015-16. Same value by a different route. It’s interesting that he’s hit 30, but it’s not meaningful to this topic.
There are enough guys who truly are better from elevating that we don’t need to cite false positives.
There are also guys who’ve gotten worse by this route. The gains outnumber the losses, but we’ve got to keep it all in perspective. It’s not a magic path to success for all hitters.
Swinging for more flies also gets more whiffs for most players. The batted balls are better, but there’s fewer batted balls.
Also, a player needs at least average batted ball speed to take advantage of higher angles. Guys who don’t hit the ball hard enough but despite that try to hit more in the air will more likely end up hitting a lot of easy flies.
It’s not for everyone.
In my opinion, one of the reasons why there is an increase in frequency in 2017 at the lowest angles is that pitchers have thrown less and less fastballs, which also lead to mis-bat and grounders. and that gives rise to an increase at low angles stages.
Someday, 2005-2014 will be remembered affectionately as the “unjuiced decade”: after steroids and before the juiced ball.
Could the decreased ev be an artifact from the system picking up a larger percentage of weakly hit balls that it missed previously?
So if you slice the data a hundred different ways, eventually you find five that support your hypothesis? That’s called “Type I” error.