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August 2, 2022

Why YOU Should Hate the Word “Efficiency” – Part 2

Last week we talked about why I hate the word “efficiency” in describing pitching mechanics and how the true meaning of pitching efficiency can be obscured and at times, disconnected from its true meaning—throwing less pitches per inning.

In my mind, this means pitchers are throwing deeper into games, displaying command, and able to induce weak contact to convert on outs.

Whatever way you look at it, the pitcher would be doing more with less, which is the essence of the word. However, as it relates to describing mechanics, my goal this week is to get you to hate the word “efficiency” like I do and demand more evidence.


So now we get to the important part – what do you think when someone mentions that a pitcher has “efficient” mechanics? There are too many places our minds can race when we hear this descriptor, as people tend to lean on qualitative over quantitative insights.

I will admit that I trusted my eyes before I entered the world of biomechanics to quantify movement. Initially, when I thought of “efficient” mechanics, I associated my perception around a delivery with low deception.

After studying biomechanics, I matched my visual impression to mathematics and broke it down, which looked like this:


  • the ball can be seen longer coming out of the glove in milliseconds,
  • throwing shoulder externally rotated at least 45 degrees at foot contact,
  • hand is above the elbow at weight-bearing foot plant,
  • arm raised to the vicinity of 90 degrees and scap-loaded 10 degrees,
  • and the time window that the ball is behind the body and obstructed is less, meaning shorter time, and almost negligible.

Generally, sidearmers and crossfire pitchers were typically considered inefficient, coupled with opening the trunk before foot contact.

Essentially, I confused “efficiency” with being injury-resistant. If you subscribe to that definition, you will likely cringe when you see a hurky-jerky, disrupted, and quote-unquote “funky” delivery.

I have a 3D capture below at stadium scale by the game’s leader in 3D tracking in Major League Baseball – Kinatrax. After watching the video, you can decide if they look efficient or inefficient in your eyes.





In my first year with the Angels in 2017, we created a predictive data engine built by a rocket scientist and some incredibly smart quantitative analysts to determine what “efficient mechanics” meant to prospect selection and future performance.

What was interesting was how many athletes were regressing to the mean, few outliers were found, and many had common features with joint positions only off by an average of 5 degrees.

This made it challenging to identify what was inefficient versus efficient over a model with 300+ pitchers. For that year, our model was based on fastball velocity capacity and creating parallels to successful professional pitchers in our biomechanical database.



In my second year, being 2018, we became more interested in predicting health, as we were officially the most injured team for pitchers in 2017.

Our model shifted from predicting high octane velo to abstaining from the “funky” pitcher who we identified had deception features that we felt were less “efficient” or more injury provoking.

Here’s the spoiler alert—our pitching health worsened after the draft, and we were dying by the cure —more treatment needed, more surgeries.

We took a biomechanical solution to a strength problem.

We grew an extensive list of “efficient” pitchers on the injured list, not one who had an inverted-W, an elbow hike, or any of the classic ticking time bomb signs that have been indoctrinated into baseball.



After we introduced strength testing for the throwing arm and created individualized training and workload strategies, we moved ourselves from the basement to the middle of the pack in 2019 and then in the top 10 in 2020 for health.

We did not experience a surgical injury to the active roster in both years.

Strength evaluation was a critical piece to throwing less per inning with greater fatigue resilience. We could not deny that our doing more with less was amplified by our acquisition of Max Stassi, an elite MLB defender.

We solved some things around pitching efficiency, but we still could not predict efficient mechanics through projecting pitchers’ future ability to throw hard, connecting dots to previous high performers, or being clear of deceptive elements that could be considered injury-provoking.

This left a gaping hole in my consciousness, and I have been living in the present with many more questions than answers in identifying what “efficient” mechanics mean until this year.



I recently was invited to work with Dr. Glenn Fleisig, and his crew at ASMI with the added stats help from Dr. Gene Brewer at ASU. Dr. Fleisig is a Hall of Fame Baseball Biomechanist to search for meaning in describing efficient mechanics.

After a series of statistical tests and predictive analytics with a large dataset, we arrived at what we call “Biomechanical Efficiency Grades” (BEG).

BEG encompasses velocity performance and injury risk susceptibility into one metric, a ratio that could go up or down with velocity or a change in normalized medial elbow joint loading.

It’s a dynamic measure that can be impacted by anatomical and physiologic elements, coordination, and psychological aspects.

The numerator is throwing velocity, and the denominator is normalized elbow varus torque, which is the eccentric rotational force we discussed in Part 1 to close the inner elbow and shield the UCL from Tommy John Surgery risk.

Essentially in our more with less definition of efficiency, we consider athletes with high biomechanical efficiency grades to produce higher velocities with lower relative elbow joint torque.

Normalization means we expressed elbow varus torque as a percentage of athletes’ height and body weight. This was an important step, as when we translate torque relative to body weight and height, all athletes can be compared on the same scale. It doesn’t matter if you are an 18-year-old first-rounder, a 40-year-old, a 12-year MLB veteran, or anyone player in-between.

This is very similar to how we created our ArmScore, a raw score representing total arm strength divided by athletes’ body weights. It gives us a true definition of strength, as you could be a huge athlete with a relatively weak arm compared to a smaller athlete with huge arm strength. Relative measures are important for health. Since we wanted to compare professional and collegiate pitchers, normalization was the only way to investigate BEG differences between the two groups.

Our first hypothesis is likely not different than yours in that we believed pro pitchers would be much more efficient. It was not a leap of faith, as by enlarge, pro pitchers on average throw harder than the college pitchers and that means we expected greater velocity per normalized elbow torque.

Although our hypothesis was confirmed, when we ran statistical testing on normalized elbow torque, and low and behold, college pitchers and pro pitchers were almost identical at 6% of body weight x height.

The identical loading but different velocity attributes confirm a definite efficiency effect. This peeked our curiosity, as although college players have identical relative elbow torques, something is holding them back from achieving pro-level BEG and may be considered an important clue in scouting.

You will have to hold on for next week’s Strength and Numbers, where I will indicate what biomechanical variables we found to influence BEG between low and high BEG populations.

I BEG for you to stay tuned for more, as after next week, when someone says a pitcher’s delivery is “efficient,” you won’t cringe as I do.

Instead, you can share quantitative insights with others’ qualitative perceptions and provide more detailed context that can be analyzed.

If you combine throwing arm strength testing and can be at the intersection of supporting what you see with what you measure, your road will be paved with yellow bricks, championships, and no elbow chips.


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