Here are three studies the R&D department at Driveline read this week:
The relationship between pitch velocity and shoulder distraction force and elbow valgus torque in collegiate and high school pitchers
One of the most common applications of biomechanics in pitching is finding metrics that are related to various arm joint kinetics (joint loads). Kinetics in the context of the throwing arm often refers to the forces and torques placed upon the shoulder and elbow joints during the throw.
Often this research is aimed at finding the effect of “performance” increases which is often described as increases in pitch velocity. In this study, Nicholson et al. at the Wake Forest pitching biomechanics lab investigated a relatively large sample of high school and college pitchers to explore the relationship between pitch velocity and two kinetic measurements on the throwing arm:
- Shoulder distraction force (imagine a force pulling the upper arm out of the “shoulder socket”)
- Elbow valgus torque (imagine a torque trying to pull your shoulder into external rotation if your arms were in a goal post position).
After using correlational analysis to determine the relationship between pitch velocity and these two measurements of joint load, they found they are both positively correlated to velocity. However, the correlations are weak (r2 = 0.32, r2 = 0.44).
The relationships were stronger in the high school sample than the college sample and were also stronger with slower throwing pitchers than harder throwing pitchers. This means that at lower velocities, an athlete who exhibits larger joint loads in their throwing arm is also likely going to throw harder than another pitcher who exhibits lower throwing arm joint loads, but this relationship doesn’t hold up in harder throwing populations.
Graphics created from Nicholson et al. 2020
This is similar to what Slowik et al. found in 2019 when they looked at the relationship between elbow valgus torque in professional-level pitchers. The relationship between pitch velocity and elbow valgus torque between pitchers in their case was even lower than the present study (r2 = 0.076) which follows a similar trend showing weaker relationships between velocity and joint loads as the level of play and velocity increases.
Additionally, the within-pitcher relationship between pitch velocity and elbow valgus torque is very strong (r2 = 0.957). This means that when comparing harder throwing pitchers to slower throwing pitchers, the relationship between the difference in velocity and the difference in joint loads will be weaker than when comparing the joint loads between a single pitcher’s hardest thrown fastball to their own slower thrown fastball.
As we know, there is a lot involved in being able to throw a baseball at high velocities. These studies suggest that:
- Throwing hard does, in fact, require the throwing arm to experience more substantial loads, as shown by the consistent, but weak, correlation of pitch velocity and arm joint loads between pitchers as well as a strong correlation within pitchers
- Further, when comparing the average pitch velocity of two different pitchers, that difference in velocity is explained by a lot of unmeasured variables outside of just joint loads as shown by the weak correlation between pitchers
- Last but not least, what separates the hardest throwing pitchers from each other does not seem to be the loads they place on their arm joints, but other unmeasured factors as shown by the degradation of the pitch velocity-joint load relationship as velocity and level of play increases.
Throwing is a very complex movement.
Faster visual reaction times in elite athletes are not linked to better gaze stability
Hitting is a very tough visual task that requires fast and accurate reactions. A study published in the UK looked into the relationship between visual reaction times and gaze stability (how many blinks and saccades the participant executes during a specified time period) to determine if a more stable gaze behavior (less blinks and fast eye movements) can explain the ability to react quickly and accurately.
Barrett et al. investigated a sample of 44 cricketers, 21 rugby players, and 50 non-sporting controls and found a few different relationships worth noting including:
- Cricketers have faster visual reaction times than the non-sporting control group
- Blinks and saccades (less stable gaze behaviors) are associated with slower visual reaction times regardless of level of play
- Female cricketers had on average a more stable gaze behavior (less blinks and saccades) than the female control group
- When the presence of blinks and saccades were accounted for, group comparisons of visual reaction times were not changed. Essentially, when comparing only athletes and controls who had a saccade or blink present, there was still a significant difference between groups in visual reaction time. This suggests that the difference in visual reaction times between the athletes and the non-sporting controls is more likely due to skill level or level of play than the incidence of a blink or saccade
Graphic created with data from Barrett et al. 2020
The study is an interesting look into gaze patterns of elite athletes because it doesn’t use the quiet eye method—common in much of the existing gaze behavior research of elite athletes. includes the use of a quiet eye measurement
Although gaze stability was not measured using this definition of a quiet eye, the gaze stability in the present study still provides a similar description of gaze behavior. Since a longer quiet eye fixation is often associated with better performance, it would seem that a quiet eye will cause better visual perception, which isn’t necessarily supported with the present study from Barrett et al.
This is shown when they controlled for their measure of gaze stability and the visual reaction times did not change between groups. This is a long way of saying that if you have a very stable, and even potentially use a quiet eye strategy, it may not improve your visual reaction times.
The main limitation of this study is that the visual reaction time test was not sport-specific. Visual reaction times were measured using a generic test in which the participants were required to respond to an object appearing on a screen in front of them. This is a limitation because it doesn’t represent the task required by the sports in which the subjects participated in. However, since the athlete groups still performed better than the control groups despite the non-specificity of the task, we can assume that the task at least partially describes the reaction time that would be seen in a sport-specific task.
There is still a lot to learn about the role of vision and perception in baseball and cricket hitting, but this study and many others (including the quiet eye publications mentioned above) slowly contribute to our deeper understanding of how to train this part of hitting. If you want to read more into some of the pre-pitch visual approach research we have done with our gaze tracking system so far, check out our blog here.
Changes in Movement Coordination Associated With Skill Acquisition in Baseball Batting: Freezing/Freeing Degrees of Freedom and Functional Variability
Skill acquisition. Without getting too into the weeds here, there is a really cool study from Rob Gray at Arizona State University about a theory of how participants innately approach the learning of a new skill.
There is a theory that when somebody is learning a new movement, one approach is to restrict certain individual movements and movement directions to make the task easier to accomplish. For example, would it be easier to learn how to drive a car if you had to control all four wheels independently or if you could control the speed and direction of all of them with one pedal and one steering wheel? Probably the latter.
The same thing can be done when swinging a bat—if you can move your shoulder in three directions, elbow in two directions, and wrist in two or three directions, that is a lot of joints and movements to control. Conversely, if you limit the movement (freeze them) in any of those directions of movement in your elbow, wrist, or shoulder joint, there is less to control and could potentially make it easier to accomplish the task of hitting a baseball; similar to how controlling all four wheels at once instead of each one independently would make it easier to drive a car.
The important thing to note, however, is when you limit directions of movement, you limit the flexibility (and variability) of the movement. If becoming proficient in a task requires flexibility in movement, and adapting to unique circumstances such as hitting a high pitch instead of a pitch down the middle, or hitting a curveball instead of a fastball, limiting these movements can negatively impact your performance.
So, the theory is that when learning a task, we can limit movements to accomplish a base level of performance (i.e. hitting the ball) and then start to free up these movements as we get more comfortable with the task to accomplish higher levels of performance (i.e. hitting the ball harder or farther).
In this study, Gray looked into the process of unfreezing (freeing) these directions as participants became more proficient in a task. He looked at timing aspects of the swing rather than movement but found evidence that variability in timing increased after a training period, with an associated increase in task performance.
Graphic created with data from Gray, 2020
You can see from pre- to post-training period, as proficiency with the task increases from the six-week training program, their measure of “good variability” increases. This suggests that they unfroze or freed up variability, and different movement solutions as they became better at the test task.
There are many more nuances to this study, but the main takeaway is that the theory of freezing, or limiting the different types of movement that can be used to learn a task and then slowly re-incorporating those movements to help increase task proficiency is supported.
This study is limited to only timing analysis with force plates, but this work can be built upon with other biomechanical measurements to see if movement variability in body segments follows a similar trend to the timing aspects seen in this study.
By Kyle Lindley (@kylelindley_)