No one can deny that baseball has undergone a drastic change in the last few years. An increase in technology and the ability to measure things we previously couldn’t has turned things on their heads.
While it can sometimes be hard to separate the exact effects of different technologies and their effects on players from randomness (hello, juiced balls), there is no doubt that the information new technology produces is here to stay.
You can get a good look at how teams are valuing this new information by the positions they are creating and who they are hiring. Whether it’s the Diamondbacks hiring Dan Haren last year as a pitching strategist or the Rays creating a process and analytics coach, teams are looking to shrink the gap between what the front office sees and what makes its way to the players.
There has also been an increase in hires from the college ranks, in part because the good college coach often has to learn the language of the tech and numbers while successfully communicating those finding to the players, which are main traits front offices are looking for.
But introducing more technology and analytics inherently gets at the source of the old-school vs new-school debate, which amounts to whether analytics and tech have a place in the game. This, in reality, is not an either-or proposition, and you need pieces from both sides to effectively help your athletes.
Regardless of which position you take, we need to admit a couple things.
- Baseball, especially player development, is difficult and still has a lot of unknowns.
- The new information we have available (via tech) helps fill in specific gaps.
- Filling in gaps of what was previously unknown can help players develop and end up performing better on the field.
Since these new changes aren’t going away, we’re going to look at some aspects of how they’re changing the game and what coaches can do to stay ahead. Let’s look at the following areas:
- What gets defined as truth has changed.
- Why coaches need to go deeper into the data, using launch angle and spin rate as examples.
- How technology may change how coaches communicate.
The “Truth” Has Changed
It’s very simple to see how the “truth” of the swing or pitching motion was applied not too long ago (and to be honest, often still is applied today). Previously, much of the “truth” in baseball instruction could be repeated verbatim: a famous player says a specific cue or feel put him over the top, so that’s the truth.
- “Famous player says he does X move.”
- “Coaches hear famous player’s description of X.”
- “Coaches reiterate that description verbatim to instruct their players.”
However, an increase in technology and information has changed how we define “real” compared to “feel” along with how we communicate those concepts.
In the past, if a hitter said the key to his success was staying down to the ball, then that feel was not only accepted as the feel that made him best but also as the truth of how he was moving. New technology is driving a wedge between what feels are and the actual measurements of how a player moves.
At some point, objective measurement came in conflict with strongly held beliefs.
If a player is struggling to hit, he usually defaults to focusing on the cues and actions that he thinks are important. For example, if a player is in a power slump, this may mean that he spends more time working on staying down to the ball, or whatever he believes is the best cue for him.
An analyst may describe this player as having difficulty with his exit velocity and launch angle, which is likely a fair statement if the player is struggling with power. But a coach and player may get upset when they hear that he needs to hit the ball hard in the air, because that wasn’t the feel he thought helped him before. This creates conflict because the measurements (launch angle, exit velocity) are overlapped with feels (staying down to the ball).
It should be expected, then, to hear that some players don’t like the word “launch angle,” likely in part because it’s being communicated to them as a feel they should have instead of a descriptive measure.
The key here is that exit velocity and launch angle are descriptive terms, like many of the “new” terms that technology and analytics have created. They are not the cues or feels, and making this distinction is vital.
Coaches are going to be expected to know the measurements (exit velocity and launch angle) and then guide the player to the drills and cues that he needs to get back to a high level of performance.
The conflict is coming because we can’t separate the cues and feels of an athlete with the new descriptive measures that describe his performance.
Not defining or separating the fact that a player can say he doesn’t focus on launch angle is missing the key point. It’s stuck in the time when cues and feels are descriptive and accurate because they are the “truth.” But since cues and feels aren’t descriptive measures, we now have better ways to measure the previously unknowable, and it hurts both coaches and players when we can’t accurately distinguish between the two.
Exit velocity, launch angle, and spin rate are the truth because they are descriptive measurements, just like pitching velocity and a player’s 60 time.
Distinguishing the two allows us to admit what is actually happening. A player can have a consistent launch angle with his “truth” (i.e. “feel”), being that he things he swings down, because we’re in a place where both are true. The measurements are accurate, and the player holds on to the feeling of the movements he needs to be successful.
However, both can’t be accepted as true if we can’t first draw a line between measurements and feels.
Going Beyond the Surface to Fill the Gaps
The goal in coaching and player development is always to help players improve. Technology and analytics contribute to this goal by simply helping fill in the gaps.
We can take a look at how some of these new stats—launch angle and spin rate—can help coaches and at how diving just below the surface can help coaches even more.
So, if we divide the line between what an athlete feels and what the measurements are, we can start to see the value in the measurements.
As mentioned before, a player can struggle by not hitting the ball well. This can be divided into what he feels and how he moves (some of which can be measured by technology such as a bat sensor or KVest).
Hitting Example: Launch Angle
New metrics like launch angle can help fill in the gaps of how a player is performing and what he does well when he’s on and where he is when struggling. Launch angle can fit right in as a descriptive measure, along with other things that coaches regularly talk about. Just because launch angle might not be every players favorite term, doesn’t mean it can’t benefit a coach:
- Beyond average launch angle, a coach can look at the standard deviation, or distribution of hits, to see how players get to that average.
- Launch angle can also be affected by the types of pitches a player is swinging at; a decrease in LA can come from expanding the strike zone and swinging at a pitcher’s pitches. Similarly, an increase in LA can come from a player swinging at pitches he hits best.
- A mechanical adjustment may be needed (and can be measured by a bat sensor), but point of contact can also have an effect on launch angle. We know that home runs are more likely to be hit out in front of the plate, so when a player is struggling, you might see that he’s taking a cue like “let the ball get deep” too far.
Measurements like launch angle provide more context and can be used with other technology to get a more accurate representation of how a player is performing. This means the cues a coach says should depend on what the measurements show.
Pitching Example: Spin Rate
It isn’t uncommon for pitching coaches to intuitively suggest that a player may be cutting his fastball. Using technology such as Trackman, Rapsodo, the Diamond Kinetics ball, and a camera, coaches can actually see if that’s happening.
- A pitcher may be cutting his fastball, which may be seen in spin rate but is more likely to be seen in spin-axis changes.
- You can also look at ball-tracking information to see how that has changed the pitch movement, which is going to be more reliable than a coach’s eye.
- A camera can give the pitcher a visual of how he is releasing the ball, and a coach can use that to make more specific changes.
Now, this doesn’t mean that the term “spin rate” or “spin axis” is what the player needs to be told. But knowing what those are and how they are relevant means you are in a better position to make changes faster. This is especially true when you are comparing using technology versus just using your eyes.
Using technology can help shorten the feedback loops players and coaches go through in order to make adjustments faster. Video and spin-rate data can change someone’s perspective, especially compared to just verbal cues, but video, spin-rate data, and cues all work together in the end.
Coaches need to be able to find the change and then figure out, find, or piece together the reason behind the change.
All that involves communication with a player. The role of future coaches is to use information and technology to give more context and drive more specific adjustments. As you can tell, this moves past the “hear cue, repeat cue” that coaches have relied on for so long.
Communicating, or Not Communicating, Data to Players
One of the new things with data and technology is that what you learn may be best communicated directly or indirectly. This means that not everything known or learned about numbers or technology needs to be directly stated to players.
Some of the data serves as more background data justifying the “why” you want to do something instead of something you would repeat word for word to your athletes.
All of these new metrics describe how a player has performed but you need coaching to help maintain a high performance or turn around a poor performance.
There is a good chance that athletes will also be split on whether they want to receive more information or not. Some will want to have everything thrown at them; others just want to be pointed in the right direction.
The beauty of understanding what new technology and analytics can do is knowing that you can deploy it whenever necessary to fit the needs of your athletes and not simply to cater to those who work best with a more non-technical approach.
The point of the data and technology is to know more of the “why” and get a player to an improved state faster. Whether a coach explains all of the background knowledge on spin rate, or any other metric, depends on the topic and the athlete.
The Coach of the Future (Starting Now)
There is now more information available than ever before on the best athletes in the world and what they do. If we want to help improve our players, looking at what information is available is a good start.
Of course, intangibles such as being a good teammate, high character, having good grades, always hustling, and being baseball smart are still important. But those things aren’t going to be your ticket to the next level alone. You need those, plus numbers that are good enough or show promise.
This is why there will always be a role for traditional scouting to go along with the measurements that are now available.
However, the coaches of the future will be judged on the metrics and if the can make positive changes in their athletes.
These new coaches don’t need to know everything about a specific technology or metric, but they need to know what it is and how to ask good questions.
So, what we have to do is be honest with what we don’t know and realize there are more tools available now to fill in our knowledge gaps.
Much of this either-or debate of whether analytics or technology has a place in the game comes down to a misunderstanding of the coaching process and the prevalence of confusing descriptive measurements with player feels or cues.
In the end, technology will simply supplement the best coaches. It’ll help fill in the gaps and create better feedback loops for players. But the style, or translation, that the data will be communicated to the players will likely be the most desired trait of all.
This article was written by Project Manager Michael O’Connell