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Arm Stress Comparisons Between Common Types

Erin Bristow1, Alex Caravan1, Kyle J. Boddy1, Michael E. O’Connell1, Sam J. Briend2

1Research and Development, Driveline Baseball, Inc, Kent, WA, USA 2High Performance, Driveline Baseball, Inc, Kent, WA, USA

Corresponding Authors:

Alex Caravan 19612 70th Avenue South, Unit 4-3 Kent, WA 98032

Email address: [email protected]

Abstract

The purpose of this study was to examine differences in varus arm stress between baseball pitch types — versus a breaking of choice—with MotusBASEBALL’s motion capture arm sleeve. Twenty-eight males between the ages of 18 and 36 (21.4 ± 4.3) were asked to throw ten pitches of each pitch type — fastballs (n = 28), (n = 14), sliders (n = 14), and (n = 18). Every subject threw fastballs and a of their choice, and some subjects threw additional changeups. Sliders had the highest arm stress (54.6 ± 12.9 N·m) while curveballs had the lowest (46.8 ± 16.3 N·m). arm stress was 50.1 ± 16.8 N·m and arm stress was 51.3 ± 15.5 N·m. There was no statistically significant difference between pitch types and arm stress (p-value range 0.08-0.92), although the proportion of outlier readings for arm stress was significant for sliders (proportion of outliers: 34%, p-value: 0.009 versus change-ups; p-value: 0.014 versus curveballs). In addition, pitch type was significant only in determining the velocity reading from the Motus App (p-value <.0001), and was not significant in determining arm speed, arm slot, or shoulder rotation.

Keywords Motion capture, arm stress, pitching, biomechanics, IMU

DOI http://dx.doi.org/XXXX/osf.io

Citation Bristow E, Caravan A, O’Connell ME, Briend SJ (2019). Arm Stress Comparisons Between Common Baseball Pitch Types. SportRxiv. doi: .XXXX/osf.io/

Corresponding author: Alex Caravan [email protected] Author agreement statement: We the authors agree to the sharing of this preprint on SportRχiv. Twitter handles: @Alex_Caravan 1. Introduction

Since the first ulnar collateral ligament reconstruction (UCLR) surgery by Dr. Frank Jobe on in 1974, elbow surgeries have been on the rise. Between 2007 and 2011, the incidence of UCLR surgery rose by 4.2% per year in data obtained from a private-payer database (Erickson, Nwachukwu, et al., 2015). A particularly notable finding from the database is the 9.12% average rate of increase per year in UCLR surgery among the 15 to 19 year old’s. In fact, elbow surgeries have also been on the rise in the Major Leagues: the years from 1986 to 1995, saw a maximum of two MLB undergo UCLR surgery per year, thirty-two pitchers underwent it in 2012 alone. (Erickson, Gupta, et al., 2013).

In an endeavor to determine factors relating to elbow and other arm injuries, many studies have sought to understand the relationship between pitch type and arm stress. Nissen et al. (2009) compared fastballs and curveballs with pitchers between the ages of 14 and 18. Dun et al. (2008) compared fastballs, curveballs, and changeups in youth pitchers. Escamilla et al. (2017) is the only known study to quantify pitching biomechanics for sliders thrown by professional pitchers. Fleisig, Kingsley, et al. (2006) used collegiate pitchers to compare the fastball, changeup, , and , though with a smaller sample size than the Escamilla et al. study (18 pitchers).

Previously, marker-based motion capture was the only option capable of measuring the kinematics and kinetics of a baseball pitch (Richards, 1999). Advances in technology have allowed practitioners and coaches to bring biomechanics to the field through inertial measurement units (IMU).

IMU sensors have previously been validated in joint angle measurements in both the lower (Leardini et al., 2014) and upper body (Morrow et al., 2017). IMUs have also been used in research on throwing sports such as (Spratford et al., 2014) and in baseball, specifically the MotusBASEBALL sensor used in this study (Camp et al., 2017).

The MotusBASEBALL sensor has been used in previous research to investigate differences between pitch types (Makhni et al., 2018), elbow torque in youth and adolescent pitchers (Okoroha, Lizzio et al., 2018), effects of fatigue (Okoroha, Meldau et al., 2018), as well as arm mechanics during long toss (Dowling et al., 2018). In addition, the specific reliability and validity of using MOTUS metrics to measure variables like arm stress, arm slot, shoulder rotation, and arm speed was investigated and confirmed as having high reliability in a recent study using the gold standard of motion capture as a measuring tool (Boddy et al., 2019).

The purpose of this study was to compare varus arm stress between the various pitch types: the fastball (n = 28), curveball (n = 14), slider (n = 14), and changeup (n = 18) using an IMU sensor. Varus arm stress along with arm speed, pitch velocity, arm slot position, and shoulder rotation were all captured by the MotusBASEBALL motion-capture arm sleeve (Motus Global; Rockville Centre, NY). The hypothesis was that there would be no noticeable differences in arm stress for pitchers between different types of pitches.

2. Methods

2.1 Subjects

Hummingbird IRB (#2018-62) approved this study to be conducted at the author’s facilities — the Driveline Baseball facility in Kent, Washington. Prior to participation, each subject had the study verbally explained to them. Subjects then read and signed an informed consent document. The subjects of the study were healthy baseball players training at Driveline Baseball (age = 21.4 ± 4.3 years; height = 74 ± 2.9 inches, weight = 208.4 ± 24.5 pounds) who all had previous or current collegiate, professional, and/or adult-league baseball experience. Initially, 32 subjects were selected to participate in the study, but failure of 4 subjects to follow data collection instructions appropriately reduced the total to 28. Subjects were required to be males between 18 and 40 years of age and were instructed to report any pain or discomfort experienced during participation.

2.2 Procedures

After completing their pre-throwing warm-up routine (a structured routine with sports bands, shoulder tube, and wrist weights) subjects were asked to throw pitches off a standard pitcher’s mound to a stationary target placed behind a plate 60’6” away, using a 5oz baseball.

Subjects threw at a rate of self-regulated 70% perceived exertion, as befit their training program. A study found that when throwing at 60% effort, pitchers’ humeral internal rotation torques and elbow valgus torques were at 75% of a full-effort throw; when throwing at 80% effort, those loads were at 86% of a full-effort throw (Slenker et al., 2014). The elbow torque measured in this study is likely consistent with those ranges and seems to conclusively correspond to a greater than perceived exertion percentage of a pitcher’s full-effort throw.

Subjects were asked to throw ten pitches of each pitch type — fastballs and a breaking ball of their choice (curveball or slider). For the breaking pitch, 14 of the subjects chose to throw a curveball while the other 14 threw a slider; the pitch type was intentionally not standardized so as to allow each individual subject to choose whatever pitch they’re most comfortable and experienced with. In addition, 18 subjects also threw a changeup.

A few pitch type samples had only nine pitches recorded, instead of ten, while a few also had more than ten pitches in them. As such, in order to standardize the sample sizes per subject, only the five fastest pitches of each person’s distinct pitch time were included in the data set and measured with the aforementioned Motus IMU.

The subjects wore the MotusBASEBALL motion-capture arm sleeve while throwing their pitches. The sensor was placed on the ulnar collateral ligament of the athlete, two-finger widths below the medial epicondyle. Subjects were instructed to alert the investigator if the sensor moved so that proper placement could be ensured. The investigator also checked on the placement of the sensor several times throughout each study. The placement of the Motus sleeve, with the sensor in it, is demonstrated in Figure 1.

Figure 1: One of the authors places the Motus arm sleeve on a subject prior to the subject throwing a baseball. The arm sleeve keeps the Motus sensor in place as the athlete prepares to throw.

Following each pitch, data was immediately synced via Bluetooth to an iPhone’s (Apple Inc.; Cupertino, CA) MotusBASEBALL iOS application. Velocity was recorded by the Stalker Pro II and Stalker Sport 2 radar guns (Applied Concepts, Inc. /Stalker Radar; Richardson, TX).

Height and weight of subjects were recorded in the MotusBASEBALL application prior to each subject throwing their pitches. The application normalizes the arm stress (Nm), arm slot (deg.), arm speed (rpm), and shoulder rotation (deg.) of subjects for their height and weight.

Subjects were allowed to choose the order in which they would throw their pitches. Some subjects chose to alternate through the three pitch types while others threw ten pitches of the same type in a row and then changed pitch type.

2.3 Statistical analyses

The data was collected and analyzed in the statistical program R (www.r-project.org). First, descriptive statistics were assessed for all four pitch type sub-populations. Second, precision metrics for each pitch-type was taken by deducing their outlier rate via Grubbs Analysis. The critical Grubbs’ test statistic was set at respective values for each pitch type population based on a t-distribution with N-2 degrees of freedom and an alpha level of 0.05. These outlier rates were then compared across each six pairwise comparisons using a two-tailed Z test to deduce if there was a significant difference between any pitch type combinations, where the critical value of Z< - 1.960 or Z> 1.960 indicates statistical significance at a 0.05 alpha level.

Then, pitch type differences among metrics were analyzed both as respective pairwise comparisons between individual averages, and through the lenses of a mixed model regression with the specific subject serving the role of the random effect and the nested pitch type within each pitcher serving as the fixed effect. For the first form of analysis, paired T-tests were used across the segmented means for the sub-groups of the subject population that threw a) fastballs and change-ups b) fastballs and curveballs c) fastballs and sliders d) change-ups and curveballs and e) change-ups and sliders. For the second form of the main analysis, Wald Chi-Square tests were subsequently used to deduce the significance of pitch type for arm stress and Motus’s other app-generated metrics (as well as pitch velocity) after creating generalized linear models for each of the five metrics: the individual pitchers served as the random effect and the individual pitch types served as the fixed effect.

3. Results

Means and standard deviations for the four separate pitches were calculated across all of Motus’s four generated values (arm stress, arm slot, arm speed, and shoulder rotation) along with the fifth value, velocity, which was measured by the radar gun. Notably for the focus on arm stress initially hypothesized in this study, sliders had the highest arm stress (54.6 ± 12.9 N·m) compared to curveballs which had the lowest (46.8 ± 16.3 N·m).

[ TABLE 1]

Table 1: Descriptive Statistics by Pitch Type

Velocity Arm Stress Arm Slot Arm Speed Shoulder Rot (mph) (N-m) (Deg) (rpm) (Deg) Pitch StDe StDe StDe Type Mean v Mean v Mean v Mean StDev Mean StDev FB (N=288 ) 76.99 6.74 50.69 16.95 42.32 15.46 853.41 112.72 152.27 11.57 CH 106.2 (N=178) 72.74 6.54 51.72 15.84 39.67 15.72 841.36 1 152.04 13.25 CU (N=139 136.6 ) 65.30 5.59 47.55 16.57 46.60 14.07 869.88 6 152.99 9.73 SL (N=142 ) 70.03 5.82 54.92 12.09 37.75 15.05 853.06 79.97 149.80 15.95 15.9 15.4 111.1 All 72.48 7.65 51.16 6 41.62 8 853.54 9 151.88 12.67 Next, the number of outliers for each population of pitch types were set as a proportion of the total number of pitches, so as to measure arm stress precision across pitch types. The whole slider population had a statistically significant 34% outliers (24/70 total pitches) when compared to the change-up and curveball populations; significance was measured via pairwise proportion comparisons, with the largest difference coming against the change-up’s population’s outlier rate (15.56%). Table 3 below shows the proportion rate and the respective p-value of the resulting pairwise proportion z-tests of

[ TABLE 2 ]

Table 2: Outlier Rates Among Different Pitch Types

Proportion Pitch Type of Outliers N FB vs CH vs CU SL

FB 17.71% 288

CH 16.29% 178 0.397

CU 13.67% 139 1.097 0.653

SL 30.99% 142 -2.960 -3.083 -3.568

For direct comparisons of arm stress figures across pitch type, arm stress averages were computed across all nested pitch type groups for each respective pitcher. None of the paired t- test comparison of the means yielded a statistically significant result, as denoted below in Table 3, where N refers to the number of pitchers that pitched both combinations of pitches.

[ TABLE 3 ]

Table 3: Paired Subject T Test Comparison: Arm Stress

Group Pitch Type Combo P-Value N A fb.ch 0.315 18 B fb.cu 0.582 14 C fb.sl 0.662 14 D ch.cu 0.178 8 E ch.sl 0.812 10

Arm stress remained a non-significant predictor when looking at the data on a pitch-level basis after performing a mixed model analysis with the 28 individual pitchers serving as the random effect and the 4 different pitch types serving as the fixed effect. After computing Wald Chi- Square tests on the significance of the fixed effects in the model, only the somewhat intuitive metric of velocity was found to be statistically significant.

[ TABLE 4]

Table 4: Significance of Pitch Type on All Motus Metrics

Pr(>Chis Metric q) Velocity <.0001 ArmStress 0.727 ArmSlot 0.466 ArmSpeed 0.090 ShoulderR ot 0.864

4. Discussion

The purpose of this investigation was to compare varus arm stress between the baseball pitch types of the fastball, curveball, slider, and changeup. During analysis, means and standard deviations as well as the proportion of outliers were calculated for each pitch type. A paired T Test comparison was across subject means, and the significance of pitch type on velocity (mph) and Motus metrics (arm stress (N·m), arm slot (deg.), arm speed (rpm), and shoulder rotation (deg.) was calculated.

Sliders had the highest arm stress (54.9 ± 12 N·m) compared to curveballs which had the lowest arm stress (47.6 ± 17 N·m), although no paired difference was found to be significant. Fastball arm stress was 50.1 ± 16.8 N·m and changeup arm stress was 51.3 ± 15.5 N·

A previous study using the Motus sleeve found the fastball to be the highest torque pitch (Makhni et al., 2018). It also found fastballs to have statistically significant higher elbow torque than curveballs and changeups, although sliders were not included in the study. That finding was not replicated in these results, as the proxy for torque, arm stress, was not significantly higher across any pitch type. Differences in the findings can likely be attributed at least in part to a combination of differences in exertion level (the Makhni study subjects were instructed to throw at maximum exertion level compared to the instructed 70% in this study), subject experience level (the Makhni study subjects were all within the relatively narrow band of 16-20 years old, compared to the larger range of ages of 18-36 from this study), and other alterations in the procedures like the number of pitches thrown per pitch type and the order in which pitches were thrown.

On the other hand, sliders and fastballs have been found to have comparable arm stress by several studies. In a study done with eighteen professional baseball players (Escamilla et al., 2017), maximum elbow varus torques between different pitch types were compared. There was no significant difference (P < .01) found between fastball (96 ± 17 N·m) and slider (95 ±14 N·m) arm stress, as well as between slider and curveball (92 ± 18 N·m) arm stress, but there was a significant difference found between the changeup (88 ± 11 N·m) and slider, and changeup and fastball. Interestingly, varus torque levels were much lower in this study compared to the Escamilla study which again, can most likely be at least somewhat explained by this study’s exertion level being much lower (70% in this study vs maximum exertion) and differences in subject experience level (an amalgamation of high school, college, and professional pitchers in this study vs only professional pitchers).

A kinetic difference study of twenty-one college pitchers also found the elbow varus torque for the slider (81 ± 5 N·m) comparable to that of the fastball (82 ± 13 N·m) (Fleisig, Kingsley, et al., 2006). Further, it found a significantly higher (P < .01) shoulder horizontal adduction torque (130 ± 35 N·m and 111 ± 29 N·m, respectively) between the slider and the fastball. Unlike other studies, there was no significant difference found between fastball and curveball pitch types.

A study including youth, high school, collegiate, minor, and major league level players (Fleisig et al., 2016) found that elbow varus torque increased with competition level and saw no difference in torque between curveballs and other pitch types (fastballs and change-ups). The slider was not a pitch that was included in that analysis.

Among youth pitchers, relationships between pitch type and arm pain were determined with a 1.14 odds ratio for pitchers that threw curveballs (P = .54) and a 1.86 odds ratio for pitchers that threw sliders (P = .03) (Lyman et al., 2002.). It is likely that pitchers that throw curveballs and sliders are more effective than pitchers that only throw fastballs or fastballs and changeups, and therefore throw more per season and pitches per game. The same study shows a significant association between per season and pitches pitched per game, and the risk of joint pain (shoulder and elbow). Though the relationship between pitch type and arm pain is confounded by this, the difference between the odds ratio between curveballs and sliders is clear — youth pitchers that throw sliders seem to experience more arm pain than those that throw curveballs.

Despite the common belief that curveball arm stress is higher than fastball arm stress, no known study has found this to be true (Pennington, 2012). Some have found it to be not significantly different from fastball arm stress, though, including the Escamilla et al., Fleisig et al., and Kingsley et al. studies. Studies done on youth pitchers have found a significant difference, however. Nissen et al. (2009) recorded an average maximum varus elbow moment of 59.6 ± 16.3 N·m for fastballs and 54.1 ± 16.1 N·m for curveballs (P < .001) with pitchers between the ages of 14 and 18. Dun et al. (2008), a study involving youth pitchers around 11 to 14 years of age found significant differences (P < .01) in elbow varus torque for all three pitch types studied; fastballs had the highest torque, then curveballs, then changeups.

It is unknown why this difference in elbow torque existed between different pitch types, specifically in youth subject. Previous research has suggested that forearm rotation does not significantly affect UCL strain, although that study was performed on cadavers’ movements rather than live pitching (Bernas et al., 2009).

On the other hand, a biomechanical study (Solomito et al., 2018) found no association between elbow varus moment and supination position but did find that increasing supination moments were associated with increasing elbow varus moments for the fastball and the curveball (P = .002 and P < .001). A 1-N·m increase in supination moment corresponded with a 1-N·m increase in elbow varus moment for the fastball and a 1.1-N·m increase for the curveball. Despite non-significant arm stress differences between pitches found in this study, it is likely still worth investigating the differences between supination position, supination moment and elbow torques among different pitch types.

It is of interest to replicate similar studies in tighter bands of similarly-aged subjects to attempt to see if there are specific demographic parameters under which there are significant differences in torque levels for pitch types. It is highly possible that as pitchers age and mature they become more comfortable and capable of throwing their off-speed pitches, thus more closely producing the lack of significant differences that has been observed in some of the studies dealing with professional pitchers, like this study and the Fleisig study.

In addition, the significant finding of the study--the significant proportion of outliers calculated for sliders--could be due to poor precision for that pitch with the IMU. It is also possible that the subjects were less consistent with their mechanics, possibly resulting in differing supination torques, when throwing sliders. Loads on the elbow and shoulder are significantly decreased when pitchers throw at sub-maximal effort (Slenker et al., 2014), so the elbow torques collected in this study are not what they would be if the pitchers had been throwing at full-effort. Additionally, considering that one subject’s perception of 70% effort may vary from that of another subject’s, effort levels were likely varied across all subjects. The Slenker at al. study showed that when asked to throw at 80% effort, the pitchers were approximately at 90% of the velocity of a maximum-effort pitch and the loads on the shoulder and elbow were at 86% of a maximum-effort pitch.

The subjects also threw at varying velocities (76.8 ± 6.6 mph across all fastballs). It is possible that the difference between pitch type and arm stress would have been significant if the athletes were throwing at higher or more similar velocities.

Based on these findings and the findings of similar studies, performing another study in the future with a larger sample size could return statistically significant results. Pitch type and its relation to arm stress should continue to be investigated, particularly for sliders. Few studies have included sliders, and the results have been varied.

5. Conclusion

Pitch type seemed to affect velocity, while arm stress was not affected by different pitch types in the confines of this study. It did not affect any of the other metrics: arm stress, arm slot, arm speed, and shoulder rotation. Additionally, there was a significant proportion of outliers in arm stress recordings calculated for sliders (34% of all sliders), potentially implying that this pitch is much less reliably read by the Motus sleeve.

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