CS #6: Full Analysis on a D-1 Pitching Staff

Introduction

In order to appropriately assess the current culture surrounding the pitching delivery, it’s important to acquire snapshots from all corners of the baseball community. As such, CS #6 centers in on a Division-1 baseball program, and highlights important variables such as throwing efficiency, shoulder range-of-motion (ROM) patterns, and the relationship between each. From this, not only can we assess throwing-related injury risk for the program as a whole, but it allows us to understand the current trends within college baseball, and further illuminate the pivotal role that mechanics play on health and performance. 

HYPOTHESIS

In light of the strong correlational evidence between a DVS Score and injurious shoulder ROM patterns, we predict that this correlation will be further highlighted in this sample group. More specifically, there will be a negative relationship between a DVS Score and injurious shoulder ROM patterns; as DVS Scores decrease, we expect the presence of injurious shoulder ROM patterns to increase. 

METHODS

  • Location: Division-1 University
  • Number of Subjects: 15
  • Average Ball Velocity: 86 mph
  • Max Ball Velocity: 91 mph

In this study, we analyzed 15 pitchers from a collegiate, Division-1 baseball program. All subjects were asymptomatic college-aged males, and at least three-months removed from any type of throwing-related injury. Listed below are the methods used to acquire DVS Scores and Shoulder ROM measurements on each player. In order to eliminate any bias, these analyses were conducted blindly, meaning there was no prior knowledge of a player’s DVS Score or ROM patterns until both were collected.

DVS SCORE ANALYSIS

Video analysis was conducted on all pitchers by the program’s pitching coach. For all video, the camera was set at pelvis-height to ensure consistency, and each pitcher was filmed from both the back and side angles. During the filming process, each pitcher was instructed to throw all fastballs at 100% intensity, and three pitches were captured from both the back and side angles. Once video collection was complete, all video was sent to Delivery Value System, and then uploaded into a video analysis software (PowerChalk) in order to compute each pitcher's DVS Score. 

SHOULDER ROM ANALYSIS

Passive ROM measurements were recorded using a digital inclinometer for shoulder Total Arc Motion (TAM), Internal Rotation (IR), and External Rotation (ER) on both the throwing and non-throwing arms. For each shoulder, the limb was moved passively in each direction until maximal motion occurred. In order to ensure each shoulder achieved its full range of motion, the examiner used a combination of capsular end-feel and visualization of compensatory movement. The humeral head was not stabilized in order to allow for natural shoulder motion to occur. For each measurement of internal rotation and external rotation, the scapula was securely stabilized on the table. All measurements were taken at rest prior to any throwing.

RESULTS

DVS SCORE ANALYSIS

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The graphs above provide insight into the distribution of DVS Scores among the selected pitchers. As you can see, the range was fairly wide with the highest DVS Score being 18 and the lowest being 8. However, the major thing to note here is that the majority of players in this program exemplified a pattern that significantly increased their likelihood of sustaining a throwing related injury with a DVS Score of "12 & Below". Not only that, but there were no pitchers that exemplified a throwing pattern that warranted a DVS Score of 20 or greater, which signifies high efficiency and low injury risk. With that said, there were several pitchers that scored within the "16-19" range, and portrayed a relatively efficient throwing pattern. 

SHOULDER ROM ANALYSIS

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Prior to reading further, if you need to refresh your understanding of what these shoulder ROM patterns are, and the Risk Factors associated with each, read Range-of-Motion: A Pitcher's Best Friend...or Not. This will improve your comprehension of this article, and allow you to grasp the significance of shoulder ROM patterns as they relate to baseball players. 

With that said, the table and chart above show the pitchers' varying levels of injury risk based on their shoulder ROM patterns. As you can see, the distribution is fairly even in regards to the number of Risk Factors portrayed by each player; however, the largest group of pitchers fell within the "High Risk" category by displaying two major Risk Factors. Not only that, but approximately 73% of the pitching staff exemplified at least 1 Risk Factor. This means that the likelihood of these players sustaining a throwing related injury is significantly higher than if no Risk Factors were present.   

DISCUSSION

As we put another case study into the books, we now have some hard data that provides a glimpse into the pitching culture of college baseball. Even though this is an extremely small sample size, it isn't a far stretch to assume that similar trends can be found in other programs across the country. For one, that's how research works. You take a sample, conduct a study, gather your results, and then extrapolate those results to the rest of the population. But there's also something else that allows us to make that assumption. Maybe it isn't as scientific, but it's there for anyone to see, and is just as powerful in my opinion. The culture. The culture represents the mass, which is what people tend to follow, and the mass follows the best. Therefore, in baseball's case (baseball in the U.S. anyway...), the culture is dictated by Major League Baseball, and the rest of the guys that are getting paid to play the game. From one generation to the next, information is subtly transferred into the youth as they try and mimic what they see at the highest level. Coaches and parents are no different. They will teach and facilitate what they know, which in some way or another, is always connected back to the top. Now, there are always exceptions here, as everyone has their own unique experiences; however, for the most part, the players in this study likely grew up with the same stimuli as other players their age. So back to my point, it's not unreasonable by any means to think these trends go far beyond this pitching staff alone. 

With that said, let's dive a little deeper into what these trends are actually telling us. First off, the DVS Score average for this pitching staff was 13.2, which is pretty much in-line with the current averages found in both the youth and professional ranks. Not horrible, but certainly not good either. However, one of the more alarming trends we observed in this case study was the relationship between a DVS Score and history of surgery. Of the players we polled for this study, three of them reported having underwent at least one throwing-related surgery on their throwing arm. The scary part is that all three of these players were in the bottom tier of DVS Scores, with one of them actually having the lowest DVS Score of 8. Although scary, this is certainly not surprising as a DVS Score is a measure of efficiency and stress. Higher scores are indicative of greater efficiency and less stress, and lower scores indicate the opposite. As stress strongly relates to injury, players with lower DVS Scores will have a greater chance of getting injured. This relationship can be further substantiated by observing the trends between a DVS Score and shoulder ROM patterns, which is portrayed in the graph below. Now, despite the dispute surrounding where injurious ROM patterns come from and why they exist, one thing is for certain; they arise due to excess stress. Therefore, because a DVS Score is an indicator of stress, one would expect that as DVS Scores decrease, injurious ROM patterns will increase.

 

DVS Score vs. ROM Correlation

 

Interestingly enough, that's exactly what we found when we looked at the data. Shown above is each player's DVS Score and Dominant Total Arc Motion Deficit (DTAMD). The blue bar on top quantifies the player's DVS Score, as the corresponding green bar reflects their DTAMD. Just in case you didn't click the link above, any DTAMD measurement in the negative is less than ideal, and if a measurement is less than -5, it correlates to significant injury risk; therefore, green bars on top of the blue bars are better. As you can see, the three worst DTAMD measurements came from players that had DVS Scores of 12 and below, which the DVS Scoring System classifies as very high risk. In other words, these players exemplified a throwing pattern that yielded relatively high amounts of stress onto their throwing arm, which was evident by their abnormal ROM deficits. As stated previously, of the 15 pitchers analyzed in this study, approximately 73% of them had a least one ROM Risk Factor, with 64% of those having at least two. This simply serves as further evidence supporting the strong correlations between a DVS Score, injurious shoulder ROM patterns, and excess stress. If you wish to grasp a deeper understanding of these correlations, and why they exist, you can click here to learn more.

CONCLUSION

Based on the results found in this Case Study, we hope that coaches and players will have a greater awareness surrounding the throwing culture in college baseball, particularly as it relates to pitchers. Without awareness, there is no reason to implement solutions and seek change. If you’re a college baseball program, or any other league or organization, and would like a full analysis conducted on your players, you can contact us at info@deliveryvaluesystem.com. Until then, keep your eye out for the next case study!

-Will

Case StudiesWill FoxComment