The Overshooters

Last week I touched on a few misconceptions about launch angles and exit velocity. This article is a Part II, so you may be interested in going back and reading Part I if you haven’t already. Otherwise, allow me to summarize:

The value of batted balls drops rapidly with higher launch angles. In a sense this goes without saying, everyone knows pop ups are bad.  However, the ideal launch angle may be lower than you might expect. You’ll hear many people claim 25-30 degrees is the best range to shoot for, but even this is too high. The best angles are hit between 19 and 26 degrees. These batted balls can be referred to as fliners, somewhere between a line drive and a fly ball.

This week, I want to address the concept of the “Flyball Revolution”, why I think this is a misnomer, and which players may be suffering from this mindset.

The “Flyball Revolution”

When reading about the uptick in home runs I have seen many references to flyball rate. Meaning, you have groundballs (GB%) hit on the ground and Flyballs (FB%) hit in the air.  Pop ups and line drives may or may not be included, depending on the source. This is a pretty simple system, and we’re all well accustomed to looking at the game through this lens.  So what is the problem? 

Allow me to explain using a few examples. In scenario A, the batter has hit 15.9% of his balls between 19 and 26 degrees, 4.5% between 26 and 39 degrees, and 13.6% above 39 degrees. In scenario B, the batter has 9.4% between 19 and 26 degrees, 8.2% between 26 and 39 degrees, and 18.8% above 39 degrees.  You can see the breakdown in the table below.  Important to note, in both scenarios the batter has about 52% ground balls and 48% fly balls, in the traditional sense.

(Read my article about the DB, GB, LD, HD, FB, and PU categories)

Equal Traditional GB% and FB%
DB% GB% LD% HD% FB% PU%
A 30.7% 21.6% 13.6% 15.9% 4.5% 13.6%
B 37.6% 14.1% 11.8% 9.4% 8.2% 18.8%

In scenario A, the batter has a .390 wOBAcon (weighted on base average on contact).  In scenario B, the batter has a .332 wOBAcon.  A gigantic difference.

Alright, but that’s a big difference in pop ups, right?  So let’s control for that, too.  In scenario C and D, the batters have the same number of DB+GB (the traditional ground balls) and pop ups.

Equal PU% and Traditional GB%
DB% GB% LD% HD% FB% PU%
C 29.3% 14.1% 19.9% 9.8% 10.9% 16.0%
D 39.0% 4.4% 8.5% 6.5% 25.6% 16.0%

In this case, C has a wOBAcon of .389 and D .332.  Again, a gigantic difference, even when you control for ground balls and pop ups. Furthermore, both have an average launch angle of 12.4 degrees.

The flyball rate, groundball rate, and infield flyball rate are insufficient for understanding the type of contact a batter is creating. All three of these numbers, even when combined, fail to give you a full picture of what the batter is doing on the field.

When we refer to this as a flyball revolution, and use traditional definitions of flyballs to describe it, we lose sight of what players are (or at least should be) attempting to accomplish:  Fliners. High Drives. Whatever you want to call them. Balls hit on a moderately high angle, but not too high. Not quite high enough to optimize home runs, but still high enough to hit a few. You want batters who hit plenty of doubles in addition to their home runs, and you accomplish this by hitting the ball between 10 and 26 degrees.  Preferably between 19 and 26.

Players Who May Have Taken “Flyball” Too Literally

I don’t know why the following players have increased their (bad versions) of flyballs this season.  Some may be attempting to join the “flyball revolution”.  Others may have introduced unrelated mechanical problems to their swing.  Still others may be facing different sorts of pitching, or fighting through injury.  I don’t have an explanation for why these particular batters have increased their rates this season, but it is interesting to see which players have, and to what extent.

The Worst Offenders   

These batters have increased their high flyballs (39+ degrees) at the expense of their lower angle flyballs. This is a very bad group to find yourself in, as your batted ball quality is suffering greatly from last season.

The Worst Offenders
Name ΔDB% ΔGB% ΔLD% ΔHD% ΔFB% ΔPU%
Derek Dietrich -1.5% 1.8% -8.5% -4.7% 7.3% 5.6%
Rougned Odor -6.1% 6.1% -5.1% -2.3% -0.4% 7.6%
Trevor Story -11.1% -1.2% -6.1% -0.9% 4.4% 14.8%
Tim Anderson -11.9% 3.6% -2.3% -4.7% 4.9% 10.4%
Christian Yelich 3.0% -1.3% -4.6% -2.4% -2.6% 7.8%
Jose Peraza 3.7% -3.6% -1.7% -4.8% 0.6% 5.8%
Alcides Escobar -3.2% -4.2% -4.1% -2.2% 3.6% 9.9%
Danny Valencia -1.8% -1.6% -0.7% -4.4% 3.2% 5.3%
Lorenzo Cain -4.2% 6.3% -2.0% -3.0% -4.1% 7.0%
Matt Carpenter -9.3% 6.1% -0.2% -4.3% -2.0% 9.5%
SOURCE: xStats.org

This is not an exhaustive list, but it does grab a certain cross section of batters.

There are obvious offenders like Trevor Story, who has very dramatically increased his number of high fly balls at the expense of just about everything.  He has fewer ground balls, fewer line drives and fliners, and significantly more fly balls and pop ups.  This is just about worst case scenario, and he had a rough patch this season prior to going down with a shoulder injury.

Christian Yelich made this list due to an across the board decrease in low angle fly balls along with a large increase in high flyballs and pop ups. He finished last season with one of the highest rates of what I label GB%. You might call these glinders? A bit like line drives, but mixed with ground balls. We don’t have a true category for these, but they have a pretty good .476 batting average. However, this season Yelich is hitting fewer of them as well. 

Swapping Weaker Grounders For Pop Ups

This group may not have the same impact to overall offensive production as the prior group, but it is still quite bad. These guys have traded their weak ground balls, which I call DB% or dribble balls, for pop ups. These two types of batted ball carry little value, but Dribble Balls are roughly 3-4 times as valuable as Pop Ups.

Trading Dribblers For Pop Ups
Name ΔDB% ΔGB% ΔLD% ΔHD% ΔFB% ΔPU%
Tim Anderson -11.9% 3.6% -2.3% -4.7% 4.9% 10.4%
Matt Carpenter -9.3% 6.1% -0.2% -4.3% -2.0% 9.5%
Orlando Arcia -10.4% -0.9% 2.7% -4.6% 3.7% 9.5%
Nomar Mazara -5.0% -3.0% 2.5% -1.8% -1.6% 8.9%
Rougned Odor -6.1% 6.1% -5.1% -2.3% -0.4% 7.6%
Lorenzo Cain -4.2% 6.3% -2.0% -3.0% -4.1% 7.0%
Josh Bell -7.4% 2.6% 4.0% -3.6% -1.5% 6.0%
Miguel Cabrera -3.9% -0.8% 3.0% -1.4% -2.0% 5.2%
SOURCE: xStats.org

It is especially bad that Rougned Odor has landed on each of the two lists thus far. His batted balls have decreased in value significantly from last season, which you can see in his stats.

Year AVG OBP SLG BABIP wOBA
2016 Stats .271 .296 .502 .297 .336
2016 xStats .253 .280 .447 .281 .310
2017 Stats .200 .256 .363 .217 .267
2017 xStats .223 .277 .396 .241 .289
SOURCE: xStats.org

His xStats are suggesting he may have gotten a little lucky last year and a little unlucky this year. But no matter how you cut it, he has been struggling due to his dramatic increase in high fly balls.

Granted, you didn’t need these stats to identify the problem with Odor, due to his large increase in infield fly balls. Lorenzo Cain is a different story. His groundball, flyball, and infield fly ball rates are within normal bounds from last season. He hasn’t had a significant drop in his batting average, either. In fact, looking at his stats, you may not see much of a change at all.  But, alas, there is a change lurking beneath the surface.

Lorenzo Cain has traded his weak ground balls for glinders (half ground ball, half line drives). He’s also traded line drives and fliners for high fly balls. In the long run, if he continues to hit the ball in this manner, his batting average may stay roughly the same, but his slugging percentage will drop precipitously. Right now his slugging is sitting around .396, which, while below his career average is still somewhat respectable. If this trend continues, expect his slugging to drop towards .360 or .370.

Conclusion

There is a great need for more research into the changes we have seen in baseball over the past two or three seasons. Calling this an increase in flyballs, I think, obscures what is actually going on. It allows you to lean too heavily on the traditional flyball and infield flyball rates, which are insufficient and deceptive. The new statcast technology is fueling the changes we see in the game, and as a result you will need this technology to fully understand the ramifications. Statcast has created an arms race in baseball.





Andrew Perpetua is the creator of CitiFieldHR.com and xStats.org, and plays around with Statcast data for fun. Follow him on Twitter @AndrewPerpetua.

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RonnieDobbs
6 years ago

I don’t think you understand how insulting it is to credit Statcast for player improvement in this context. The idea that players are “discovering” that hard hit balls and optimal launch angles lead to better outcomes is absurd. What do you think they have been doing over the past 100 years? Just a bunch of neanderthals picking up sticks, shutting their eyes and hoping something good happens, then never reflecting on what just happened?

One thing that I think people don’t understand is that this is not a video game – you don’t tap X and hold L-trigger to adjust launch angle. There have probably never been more people without real baseball experience that are now following the outcomes. With the new industry of baseball data and the rise of fantasy sports there is a new generation of fans that don’t have any meaningful knowledge of the game. These people are probably very fascinated by launch angles and exit velocity – I can’t imagine many baseball players really gaining much from it. You might have some players that want to find the answer in the data, but these guys also piss on their hands and butcher chickens in the clubhouse (OK, maybe not) if it helps. Everyone loves the idea of finding easy answers, but you rarely do… It is entirely possible that there are other factors influencing the HR surge as well.

Mark_Weston
6 years ago
Reply to  RonnieDobbs

Yeah you’re right. The fly ball revolution is just an internet blogger thing. Nothing real to it. Spot on…

RonnieDobbs
6 years ago
Reply to  Mark_Weston

It is not as far from this as you think.

RonnieDobbs
6 years ago

I question the value of this data. You think that players need a data feed to determine that a ball was hit too high and landed on the warning track? Trust me, everyone knows when they hit a ball with optimal launch angle – you don’t even need to see where it lands.

There is the other point of, what kind of swing adjustment leads to a 3 degree increase in launch angle? Players are lucky if they can even put the bat on the ball. Most “adjustments” are very superficial like leg-kicks and changing where their hands start. Real changes to the swing are very difficult.

A player would have so many problems if they tried to adjust their swing plane frequently. Players get to MLB by being good at what they do. There is really no reason to assume that any attempted swing changes will work for a given player. To put it another way, how often do we hear about the player who had his swing ruined by some coach messing with him? Again, this isn’t a video-game where all they need to do is hold down triangle as they tilt the right analog stick.

Bottom line, I appreciate the reply.

Ender
6 years ago
Reply to  RonnieDobbs

One of the players with a changed approach actually came out and said that the team showed him the data as to how poorly his results were when he hits the ball on the ground. They broke it all down to him using the data and he changed his approach because of it. So having the data gives very easy to see metrics on the subject that just playing can’t really do for you. That player was Jay Bruce. Here is an article about it if you want to read it.

https://www.nytimes.com/2017/03/21/sports/baseball/jay-bruce-mets-hitting-data.html

RonnieDobbs
6 years ago
Reply to  Ender

Thanks. I read the article and that is a reasonable case of me being wrong. I am pretty sure that this article was really just saying that Jay Bruce is a deal-pull hitter and he struggled when he was not pulling the ball. I don’t know if that is really Statcast revolution stuff – that is pretty standard data. Jay Bruce has has bad years let alone bad months. Jay says in the article that he learned that hitting the ball the other way is not his strength from the data. I can’t fathom that he learned that fact recently, but maybe he is one of those neanderthals that I mentioned. I am sure they exists – they also would be the players that experienced early success and never had to adjust as they were coming up. He seems to me like the kind of player that I outlined as a guy who would be looking for answers to his struggles, because he always spends chunks of the season struggling. Guys who attribute data to their adjustments/success get praised in communities such as this. There is incentive for them to attribute their success to data if for no reason other than positive press.

Again, thanks for the article. It is good to get some insight when available. The details are not really there, so I kind of have to infer them, but I think this was a simple as, Jay see baseball, Jay pull baseball, Jay swing hard.