Does Pitch Tunneling Actually Work?

Field tunneling is one of the many hot terms thrown around the baseball space. Analysts, players and coaches, commentators and fans all seem to have differing opinions on its effectiveness as well as its legality as a whole, but what is field tunneling anyway? Although it sometimes seems like a dark art or an advanced scientific concept, pitch tunneling is actually not that complicated and is just another way for pitchers to fool hitters. In this article, I’ll explore whether lightweight tunneling actually works, and if so, how much.

Pitch tunneling is the concept of matching the flight paths of balls closely enough to make them appear to be the same pitch, long enough to fool the decoy before they travel in different directions. This can be confusing to figure out on your own, so here’s one video Shane Bieber doing some pitching by Pitching Ninja. There are several factors that put the 2 pitch tunnel together. the most important is the release point, the trajectory of the step and the location of the plate or where the pitch ends. Since tunneling is based on 2 pitches traveling the same path and then splitting in different directions, it would be impossible to tunnel 2 pitches released from 2 different wing openings. However, even if 2 pitches are thrown from the exact same spot, it doesn’t do any good if one is a sharp curveball and the other is a fastball that sails over the catcher’s head, so the 2 pitches should also be relatively similar. ways so long. as much as possible to deceive the hitter. Furthermore, if the 2 pitches don’t end up doing anything else motion-wise, that also defeats the purpose of tunnel pitches, since the ball ends up in the same spot no matter which pitch is thrown.

All of this sounds pretty awesome at first glance. Throw 2 pitches the same way and the hitter is completely screwed. Maybe if all pitchers were robots and able to do it every time, then yes, pitch tunneling would be pretty foolproof. However, even in the big leagues, no pitcher hits his spot anywhere near every time, and even if they do, many times hitters just sit on certain pitches based on that pitcher’s tendencies and pick up anything that isn’t theirs. are looking for. for Also, 2 pitches can tunnel perfectly but be balls, which again defeats the purpose of practice. So pitch tunneling actually works beyond theory. Let’s answer that question with a little statistical analysis.

First, we need a metric to measure how well 2 given pitches are tunnelled. As I said before, pitch tunneling basically comes down to 3 factors: launch point, flight path and plate location. A great example of a basic measure that combines these 3 factors is the Tunnel Score, which is outlined in this volume. article:. The tunnel score takes into account the difference in release point between 2 pitches by calculating the Euclidean distance between the 2 release points. A greater distance will result in a lower score and vice versa. The tunnel score then uses the ratio of the position difference between the 2 pitches with motion and the difference between the 2 pitches without motion to see how similar they were at the start of their flight and how different they were at the end of their trajectories. This means that a lower difference position without movement and a higher difference with movement will result in a higher Tunnel score and vice versa. Taking each factor into account, the overall formula for measuring the Tunnel Score is:

There are 2 changes I made from the original formula. The first is that I chose to measure the actual distance and measure the tunnel distance in inches instead of feet. This is because I believe that a smaller change in movement should be scaled up in the tunnel unit calculation, while the release distance should still be measured in feet, as a small change would have minimal effect on the tunnel effect of the pitch. The second change I’m going to make is that I’m going to increase the Tunnel score to 100 to make it a Tunnel score +, which means the average score will become 100, a score of 115 will be 15% above average, and the score is 85. % will be 15% below average. Not only will this make it easier to understand what is a good or bad score, but it will also make future calculations easier during analysis.

Next, we need a metric to evaluate the quality of each step from a non-tunneling perspective. For this we will simply use the run values ​​of each step as intended A baseball savant. By doing this, we’re measuring how good each of a pitcher’s pitches are on their own, not in sequence. I’m also going to increase the run values ​​to 100 for each step type to put them on the same scale as Tunnel Score+.

To use these 2 metrics to assess the effectiveness of tunneling to add value to back-to-back pitches, I will first randomly select 100 pitchers with at least 3 pitches thrown and 200 pitches thrown this season. This would give me enough different combinations of pitching sequences, and a pool of pitchers selected without bias, that I would theoretically have some pitchers who tunnel very well and some who don’t, as well as some who have great individual pitches and some who don’t. I will then calculate Tunnel’s score for every 2 pitch sequence they have thrown throughout the season and get the value of every pitch they have thrown this season. Next, to test the effect of tunneling on the cost of underpasses, I’ll check the correlation between the sets of values, looking for a pattern that shows an increase in run cost as the Tunnel score increases, or vice versa. Now it’s time to look at my results and see if tunneling has had a positive effect on the value of the pitches.

My random selection of pitchers worked as intended, as I had some names like Jack Leiter and Kenta Maeda who have abysmal values ​​for their fastballs, as well as some names like Zack Wheeler and Cade Smith who had very high mileage values ​​on them. The most common pitch sequences were Fastball-Changeup, Sinker-Slider, Fastball-Curveball, and any reverse of that pair, with Tunnel’s highest scores coming from Sinker-Slider and Fastball-Curveball combinations. This makes sense because each of those pitch type pairs (except Fastball-Changeup) contains Fastballs and Breaking Balls that move in completely different directions. The surprise, however, was in the final results of my analysis. Correlation test of tunnel scores and mileage values. While I expected there to be a somewhat strong correlation between the 2, meaning that I expected successful tunneling to increase the values ​​of tunneled pitches, I found that there is actually almost no correlation between the 2, because the ratio between them is simply. 0.07. This means that whether the pitch sequence was tunneled very well or very poorly, the trigger values ​​remained largely the same. So why is this?

There are a number of reasons why tunneling has not contributed much to the change in startup cost. For example, it is very possible that tunneling worked in some cases and not in others, thus balancing the relationship. Because the tunnel requires such good mastery of both motion and throwing off the arm, I find it hard to believe that even the best arms in MLB can do it consistently enough for it to have much of an impact. Another problem with tunneling is that often multiple pitches are thrown in the same spot multiple times, giving the hitter an advantage, especially if they can figure out the order in which the pitcher is trying to tunnel his pitches. However, the biggest reason in my opinion is that tunneling will ultimately never surpass the quality of the pitch itself. Even if 2 pitches follow the same trajectory and then cut off from each other, perfectly tunnelled, if the pitches are slow, poorly positioned or have poor individual motion profiles, the pitch values ​​will still be low.

In conclusion, I believe that while the concept of tunneling sounds great, it is simply not a feasible cheat practice in terms of executing it at a consistently high level and, even if improved, will never be more important than quality. individual pitches themselves. Obviously, more research will be done on tunnels by both fans and professional organizations, but at this point there is no clear benefit to trying to do so, and when it is successfully done, it is more likely to be a fluke than a recurring pattern.