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Variability in baseball pitching biomechanics amongvarious levels of competitionGlenn Fleisig a , Yungchien Chu a , Adam Weber a & James Andrews aa American Sports Medicine Institute , Birmingham, Alabama, USAPublished online: 13 Feb 2009.

To cite this article: Glenn Fleisig , Yungchien Chu , Adam Weber & James Andrews (2009) Variability in baseball pitchingbiomechanics among various levels of competition, Sports Biomechanics, 8:1, 10-21, DOI: 10.1080/14763140802629958

To link to this article: http://dx.doi.org/10.1080/14763140802629958

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Variability in baseball pitching biomechanics amongvarious levels of competition

GLENN FLEISIG, YUNGCHIEN CHU, ADAM WEBER, & JAMES ANDREWS

American Sports Medicine Institute, Birmingham, Alabama, USA

(Received 7 November 2007; revised 30 August 2008; accepted 10 September 2008)

AbstractThe aim of this study was to compare within-individual variability in baseball pitching among variouslevels of competition. It was hypothesized that variability decreases as level of competition increases.Five fastballs were analysed for 93 healthy male baseball pitchers (20 youth, 19 high school, 20 college,20 Minor League, and 14 Major League level pitchers). Eleven kinematic, four temporal, and sixkinetic parameters were quantified with a 240-Hz automated digitizing system. Three multiple analysesof variance were used to compare individual standard deviations for kinematic, temporal, and kineticparameters among the five competition levels. There was a significant overall difference in kinematicsand in six of the eleven kinematic parameters analysed: foot placement, knee flexion, pelvis angularvelocity, elbow flexion, shoulder external rotation, and trunk forward tilt. Individual standarddeviations tended to be greatest for youth pitchers, and decreased for higher levels of competition. Thuspitchers who advanced to higher levels exhibited less variability in their motions. Differences intemporal variation were non-significant; thus variability in pitching coordination was not improved athigher levels. Differences in kinetic variation were non-significant, implying no particular skill level hasincreased risk of injury due to variation in joint kinetics.

Keywords: Consistency, shoulder injury, elbow injury, kinematics, kinetics, timing, variation

Introduction

Throwing a baseball into the strike zone requires that every segment involved works in a

concerted and coordinated fashion. Any unintentional variability in pitching biomechanics

may affect the accuracy, velocity or spin of the baseball. Pitchers who throw hard but lack

control and consistency often do not perform well enough to advance to higher levels.

Variability in pitching biomechanics may also affect risk of injury. Baseball pitching places

large loads on the shoulder and elbow joints, as measured by peak net forces and torques

(Fleisig et al., 1995), which are thought with repetition to cause injury (Fleisig et al., 1996a).

Hypothetically, variability in mechanics may cause disruptions and compensations during

pitching, creating extra and unexpected loads that may increase the risk of injury.

While variability in throwing is hypothesized to affect a pitcher’s performance and safety,

previous research addressing this issue is limited. Most early biomechanics studies of sports

ISSN 1476-3141 print/ISSN 1752-6116 online q 2009 Taylor & Francis

DOI: 10.1080/14763140802629958

Correspondence: G. Fleisig, American Sports Medicine Institute, 833 St. Vincent’s Drive, Birmingham, AL 35205, USA.

E-mail: glennf@asmi.org

Sports Biomechanics

March 2009; 8(1): 10–21

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performance analysed only one trial per individual. This included baseball pitching, where

biomechanical studies examined one pitch per individual (Feltner and Dapena, 1986;

Murray et al., 2001; Pappas et al., 1985). Researchers explained that the motions of the

pitchers seemed consistent, but we believe that the workload on the researchers to manually

digitize extra trials may have been a factor in some of these studies.

With the advent of automatic marker tracking, it is now easier to track multiple trials per

individual, opening up new opportunities to explore intra-individual variability in

biomechanics. Stodden et al. (2005) investigated the relationship between pitching

biomechanics and fastball velocity within individual athletes. They analysed a total of 166

fastball pitches thrown by 19 healthy, adult pitchers. Three separate mixed models were used

to analyse the relationship of kinematic, kinetic, and temporal parameters to ball velocity.

They found that variability in three kinematic, three kinetic, and two temporal parameters

within an individual correlated with ball velocity. Escamilla et al. (2007) digitized ten college

pitchers during 7–9 innings of a simulated game. They reported that kinematic and kinetic

variability for a pitcher from start to end of a game was relatively low, compared with

variability between pitchers. For example, for maximum elbow flexion, the range in mean

values among their ten participants was 318 (from 918 to 1228), but the standard deviation

within each participant was about 58.

Matsuo et al. (2001) found that the variability of timing among pitchers decreased from

early to late parameters in the throwing motion, and argued that timing early in the throw

may be the key to ball velocity. Pitching is a process that proceeds from the ground up, and

energy is transferred from the larger leg and trunk segments to the quicker, lighter upper-

extremity segments. The implication is that pitchers can, to some extent, adjust in response

to early inconsistencies in their pitching timing to produce a more consistent end result.

Other researchers have suggested that variability in timing may actually be desirable for

improved performance or lower risk of injury. Bartlett et al. (2007) pointed out that previous

studies on running biomechanics found more variability in inter-segment coordination for

healthy runners than for runners with patellofemoral pain. While one explanation might be

that variability protects against injury from repetition, the researchers point out another

plausible explanation is that the low variability in the injured runners is a compensation for

their pain. Bartlett et al. (2007) cautioned that these retrospective studies did not determine

any cause and effect between coordination variability and knee pain.

The aim of the current study was to fill this knowledge gap by analysing within-individual

variability of baseball pitchers at different levels of competition. It was hypothesized that

variability in pitching kinematics, timing, and kinetics decrease with level of development.

Methods

Ninety-three healthy male baseball pitchers were divided into five groups, based on their

level of competition: youth (n ¼ 20), high school (n ¼ 19), college (n ¼ 20), Minor League

(n ¼ 20), and Major League (n ¼ 14) pitchers (Table I). In general, there was a progression

in height, body mass, age, and experience from the lower to higher levels, except in the

comparison between college and Minor League pitchers (Table I). The college and Minor

League pitchers had similar anthropometric characteristics; this reflects the fact that college

and Minor League baseball are not a sequence, but typically the two choices for

advancement after high school baseball. There was a progression of ball speed during testing

with competition level, except for the Major League group (Table I).

All participants, or their parents, provided informed consent, medical history, and

physical information prior to analysis. Tests were performed in an indoor laboratory

Variability in baseball pitching biomechanics 11

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following the procedure described by Fleisig et al. (2006). Reflective markers were attached

to 15 bony landmarks, including 12 markers placed bilaterally on the distal end of the third

metatarsal, lateral malleolus, lateral femoral epicondyle, greater femoral trochanter, lateral

superior tip of the acromion, and lateral humeral epicondyle. Markers on the hands were

placed asymmetrically: for the glove hand, a marker was placed on the ulnar styloid; for the

throwing hand, markers were attached to the ulnar styloid and radial styloid.

Participants were allowed to warm up as they would prior to a practice or competition until

they felt ready. They were instructed to pitch 10–15 fastball pitches at full effort off an

artificial indoor pitching mound (Athletic Training Equipment Company, Inc., Sparks, NV)

to a strike zone ribbon suspended over a home plate. The distance from the pitching rubber

to the home plate was set to the league distance for each youth player, and 18.4 m for all other

pitchers.

Motion data were collected with a six- or eight-camera digital three-dimensional motion

analysis system (Motion Analysis Corporation, Santa Rosa, CA) working at a frame rate of

240 Hz. Raw coordinate data were filtered through a fourth-order Butterworth low-pass

filter with a cut-off frequency of 13.4 Hz. For each frame, the positions of throwing shoulder

and elbow joints centres were translated from the respective reflective markers (Fleisig et al.,

1996b; Zheng et al., 2004). Ball velocity was recorded with a Tribar Sports radar gun

(Jugs Pitching Machine Company, Tualatin, OR) from behind the target zone. The gun was

accurate within 0.2 m/s.

For each participant, the five fastest pitches thrown for strikes were analysed. Eleven

kinematic, four temporal, and six kinetic parameters were calculated, based upon methods

previously described (Feltner and Dapena, 1986; Fleisig et al., 1995, 1996b). Figure 1 shows

critical events and phases defined for pitching.

Four of the kinematic parameters were measured at the instant of foot contact: stride

length, front foot placement, shoulder external rotation, and front knee flexion (Figure 2).

Stride length was defined as the distance between the front edge of the pitching rubber and

the ankle of the stride foot. Front foot placement was the distance between the ankles in the

“lateral” (i.e. parallel to the pitching rubber) direction. Four kinematic parameters

occurred during the arm cocking phase: peak values of pelvis angular velocity, upper torso

angular velocity, shoulder external rotation, and elbow flexion. The final three kinematic

parameters – trunk forward tilt, trunk lateral tilt, and front knee flexion – were measured at

the time of ball release. Trunk forward tilt was the angle between the spine (measured as the

line from the mid-hips to the mid-shoulders) and vertical, projected into the global plane

defined by vertical and the direction from the rubber to home plate. Trunk lateral tilt was

the angle between the spine and vertical, projected into the global plane defined by vertical

and lateral.

The four temporal parameters were the time of maximum pelvis angular velocity, time

of maximum upper torso angular velocity, time of maximum shoulder external rotation,

Table I. Anthropometric characteristics and pitch speed (mean ^ s by group).

Youth

(n ¼ 20)

High school

(n ¼ 19)

College

(n ¼ 20)

Minor League

(n ¼ 20)

Major League

(n ¼ 14)

Height (m) 1.68 ^ 0.09 1.83 ^ 0.11 1.88 ^ 0.07 1.93 ^ 0.05 1.92 ^ 0.07

Mass (kg) 58.6 ^ 12.0 79.1 ^ 10.8 92.1 ^ 8.5 96.0 ^ 11.1 97.9 ^ 12.8

Age (years) 13.6 ^ 1.1 16.8 ^ 1.1 20.5 ^ 1.1 20.8 ^ 1.6 27.6 ^ 3.4

Pitching experience (years) 4.9 ^ 1.8 6.3 ^ 2.4 10.1 ^ 3.4 9.1 ^ 4.1 15.9 ^ 5.6

Ball speed (m/s) 28.9 ^ 2.1 33.1 ^ 2.9 36.6 ^ 1.2 39.4 ^ 0.7 37.9 ^ 1.2

G. Fleisig et al.12

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and total time from when the front foot contacted the mound to when the ball was released.

Foot contact was computed as the time when the velocity of the front ankle decreased to less

than 1.5 m/s, and ball release was defined as the second frame after the throwing wrist moved

in front of (i.e. closer to home plate) the throwing elbow (Escamilla et al., 1998). The total

time parameter was measured in seconds, while the other temporal parameters were scaled

as percent time. For scaling the time for each pitch, “0%” was defined as the instant the front

foot contacted the mound, and “100%” was defined as when the ball was released.

Kinetic parameters of the shoulder included maximum values for internal rotation torque,

adduction torque, and proximal force; kinetic parameters of the elbow included maximum

values for varus torque, flexion torque, and proximal force (Figure 3). Previous research has

shown few differences in mean values for kinematic and temporal parameters among

pitching competition levels, but significant increases in kinetic mean values with increasing

level (Fleisig et al., 1999). Therefore, forces were normalized by body weight and torques

normalized by the product of body weight and height (Escamilla et al., 2002; Stodden et al.,

2005).

For each parameter, the standard deviation of the five pitches of each participant was derived.

Three multiple analyses of variance (MANOVAs) were then conducted on these standard

deviation values to identify differences among the five levels (youth, high school, college, Minor

League, and Major League). The three MANOVAs tested for significant differences (P, 0.05)

in (1) kinematic, (2) temporal, and (3) kinetic parameters separately (Dun et al., 2007). When a

significant difference was observed, analyses of variance (ANOVAs) were used to identify which

Figure 1. The six phases of throwing: wind-up, stride, arm cocking, arm acceleration, arm deceleration, and follow-

through. Images represent the critical events separating the phases: initial motion, balance point, foot contact,

maximum shoulder external rotation (Max ER), ball release, maximum shoulder internal rotation (Max IR), and

fielding position.

Variability in baseball pitching biomechanics 13

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parameters in the MANOVA had significant differences. For each ANOVA with significant

differences, Fisher’s least significance difference test (LSD) was performed post hoc to identify

which pairs of competition levels were different (P , 0.05).

Standard deviation in pitch speeds was also calculated for each participant. Analysis of

variance (P , 0.05) was used to test these differences among the five levels.

Results

There was a significant difference in kinematic standard deviations among pitchers of the five

levels (F44,300.36 ¼ 2.10, P , 0.001). The means and standard deviations of these data are

shown in Table II. Six of the eleven kinematic variables included in the MANOVA showed

significant differences. This included two variables at the instant of foot contact (front foot

placement and front knee flexion), three variables during the arm cocking phase (maximum

upper torso angular velocity, maximum elbow flexion, and maximum shoulder external

rotation), and one variable at ball release (trunk forward tilt). In general, individual standard

Figure 2. Definition of kinematic variables.

G. Fleisig et al.14

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deviations tended to decrease for higher levels of competition (Figure 4). Post-hoc

comparisons showed that most of the significant differences were between the youth level

and higher levels.

Standard deviations for temporal parameters did not show significant differences among

skill levels (F16,260.32 ¼ 0.99, P ¼ 0.467). Therefore, the results for all participants were

combined in Table III. The duration of the pitch (from the instant of front foot contact to

ball release) for each participant had an average standard deviation of 9 ms. Individual

standard deviations in the other timing parameters ranged from 1.2% to 5.9% of the pitch

duration.

Differences in standard deviations for kinetic parameters were also non-significant

(F24,290.76 ¼ 1.060, P ¼ 0.390). Therefore, the results for all participants were combined in

Table IV. Standard deviation in proximal force was approximately 3% of body weight for

each pitcher, for both the shoulder and elbow. Individual standard deviations for elbow and

shoulder torques were less than 0.5% of the product of body weight and height.

Differences in standard deviations for ball speed were not significant (P ¼ 0.195).

Figure 3. Definition of kinetic variables: (a) forces applied by the trunk to the upper arm at the shoulder; (b) torques

applied by the trunk to the upper arm about the shoulder; (c) forces applied by the upper arm to the forearm at the

elbow; (d) torques applied by the upper arm to the forearm about the elbow.

Variability in baseball pitching biomechanics 15

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Table II. Standard deviation of kinematic parameters for individual pitchers (mean ^ s by group).

Youth

(n ¼ 20)

High school

(n ¼ 19)

College

(n ¼ 20)

Minor League

(n ¼ 20)

Major League

(n ¼ 14)

ANOVA P-value

(and pairwise differences)

Foot contact

Stride length (% height) 1.61 ^ 0.59 1.56 ^ 0.66 1.32 ^ 0.93 1.24 ^ 0.37 1.06 ^ 0.49 0.083

Foot placement (cm) 3.2 ^ 1.3 2.8 ^ 1.2 2.5 ^ 1.5 2.5 ^ 0.9 1.9 ^ 0.8 0.032* b,c,d,g

Knee flexion (8) 3.3 ^ 1.6 3.2 ^ 2.1 2.1 ^ 1.1 2.6 ^ 1.2 2.2 ^ 1.6 0.049* b,d,e

Shoulder external rotation (8) 8.8 ^ 6.7 5.8 ^ 5.2 6.0 ^ 2.6 7.7 ^ 4.8 6.4 ^ 3.6 0.247

Arm cocking phase

Maximum pelvis angular velocity (8/s) 24 ^ 9 21 ^ 9 24 ^ 11 19 ^ 9 17 ^ 9 0.270

Maximum upper torso angular velocity (8/s) 19 ^ 6 16 ^ 9 20 ^ 6 13 ^ 5 16 ^ 6 0.020* c,h

Maximum elbow flexion (8) 1.9 ^ 0.7 1.8 ^ 0.8 1.5 ^ 0.7 1.4 ^ 0.7 1.1 ^ 0.4 0.003* c,d,f,g,i

Maximum shoulder external rotation (8) 2.1 ^ 1.0 1.1 ^ 0.5 1.1 ^ 0.6 1.2 ^ 0.5 1.0 ^ 0.4 ,0.001* a,b,c,d

Ball release

Trunk forward tilt (8) 2.4 ^ 0.8 1.5 ^ 0.6 1.4 ^ 0.6 1.4 ^ 0.5 1.2 ^ 0.6 ,0.001* a,b,c,d

Trunk lateral tilt (8) 2.2 ^ 1.0 1.8 ^ 0.7 1.7 ^ 0.6 1.6 ^ 0.6 1.5 ^ 0.8 0.102

Knee flexion (8) 4.0 ^ 2.0 4.7 ^ 2.2 3.3 ^ 2.0 3.8 ^ 1.8 3.4 ^ 1.5 0.218

*Significant difference (P , 0.05) among the competition levels.

Post-hoc comparisons: significant differences (P , 0.05) between ayouth and high school, byouth and college, cyouth and Minor League, dyouth and Major League, ehigh

school and college, fhigh school and Minor League, ghigh school and Major League, hcollege and Minor League, icollege and Major League, and jMinor League and Major

League.

G.Fleisig

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Discussion and implications

The fact that ball velocity was not fastest for the Major League pitchers was unexpected.

One possible explanation may be that the Major League pitchers tested cannot pitch

faster than the Minor League pitchers tested. Another possible explanation may be that the

Table III. Standard deviation of temporal parameters for individual pitchers (mean ^ s among all participants).

All pitchers (n ¼ 93)

Timing of maximum pelvis angular velocity (% pitch complete) 5.9 ^ 6.2

Timing of maximum upper torso angular velocity (% pitch complete) 3.7 ^ 2.5

Timing of maximum external rotation (% pitch complete) 1.8 ^ 0.9

Total time elapsed (s) 0.009 ^ 0.008

Figure 4. Comparison of standard deviations for individual pitchers of different levels. Mean value of each

group shown for kinematic parameters with significant differences: front foot placement (“Foot”), front knee flexion

at instant of foot contact (“Knee”), maximum flexion of throwing elbow (“Elbow”), maximum external rotation of

throwing shoulder (“Shoulder”), forward tilt of trunk at instant of ball release (“Trunk”), and maximum angular

velocity of upper torso (“Upper Torso”). For visual comparison, values for each variable normalized by standard

deviation for youth group.

Table IV. Standard deviation for normalized kinetic parameters in individual pitchers (mean ^ s among all

participants).

All pitchers (n ¼ 93)

Arm cocking phase

Elbow varus torque (% body weight £ height) 0.16 ^ 0.10

Shoulder internal rotation torque (% body weight £ height) 0.17 ^ 0.11

Arm acceleration phase

Elbow flexion torque (% body weight £ height) 0.21 ^ 0.21

Arm deceleration phase

Elbow proximal force (% body weight) 3.11 ^ 1.70

Shoulder proximal force (% body weight) 3.55 ^ 1.37

Shoulder adduction torque (% body weight £ height) 0.46 ^ 0.31

Variability in baseball pitching biomechanics 17

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Minor League pitchers gave their best efforts during the laboratory testing, while the Major

League pitchers “held back” to some extent. If true, a sub-maximal effort from the Major

League pitchers during testing would be a limitation of the study.

The decreased variation in front leg kinematics at the instant of foot contact with increased

skill level is encouraging for potential observation and correction by coaches. Youth pitchers

showed the greatest variability in front foot placement and front knee flexion at this instant.

Body motion during windup and stride, and landing of the front leg, are common areas

for pitchers and coaches to work on, as it is felt that early flaws may lead to low ball velocity

or high joint loads later in the kinetic chain. Also, the early phases of the pitch consist

of relatively slow motions that are easier to evaluate and change than the rapid, dynamic

sequence of motions later in the pitch. It appears that practice and/or instruction at the

youth level do help, leading to improved consistency (i.e. decreased variability) of front leg

mechanics.

Other improvements in kinematic consistency occurred during the arm cocking and arm

acceleration phases. Teaching consistency in these rapid motions is a much more challenging

task. Therefore, the decreased variation in these variables is most likely due to

neuromuscular development from repetition of pitching.

The final kinematic differences were in trunk position at ball release. Trunk forward tilt

had significant differences, particularly between the youth level and the other levels.

Decreased variability in trunk forward tilt at higher levels is not surprising; since trunk

forward tilt has been shown to correlate with fastball velocity (Stodden et al., 2005), a pitcher

with variable trunk tilt may produce inconsistent ball velocity. Trunk lateral tilt showed a

trend for decreased variation with increased competition level, but the differences were not

statistically significant. Variability in trunk tilt can affect not only ball speed, but also pitch

location. A change in trunk forward tilt at the time of ball release might change the trajectory

of the ball and therefore the ball may cross the home plate at a different height. A change in

trunk lateral tilt might change the angle of the release (called the “arm slot” in baseball) and

may affect the ball’s horizontal position (“inside” or “outside”) as it crosses the plate.

The decreased trunk variation at higher levels was most likely a combination of some

individuals improving their consistency and natural selection of pitchers with good control

achieving success and advancing.

Previous research has shown that the time from foot contact to ball release is quite brief,

averaging 0.15 s for each competition level (Fleisig et al., 1999). A skilled baseball pitcher

produces a kinetic chain of events during this time to generate pitch velocity. According to

previous research, the coordinated sequence includes maximum pelvis angular velocity

(when approximately 35% of the time from foot contact to ball release has been completed),

maximum upper torso angular velocity (50% time), maximum shoulder external rotation

(80% time), and maximum elbow angular velocity (90% time) (Escamilla et al., 2002;

Fleisig et al., 1996c, 1999; Stodden et al., 2001).

However, slight differences in timing in the kinetic chain of an athletic motion can lead to

significant differences in energy and velocity produced. For instance, it has been shown that

pitchers with higher ball velocities show a greater delay between the times of maximum pelvis

angular velocity and upper torso angular velocity, while pitchers throwing slower show less

delay (Matsuo et al., 2001; Takahashi et al., 2002). Fleisig et al. (1999) observed that peak

pelvis and upper torso velocities were usually separated by 10–15% of the total foot contact-

to-ball release time. In the current study, the differences in temporal variation within an

athlete were quite small (only 1–3% of the 0.15 s), and were not statistically different among

skill levels. Furthermore, such small variations were most likely smaller than the 240-Hz data

capture system could measure with accuracy.

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For kinetics, the average variability of forces and torques was almost identical among

levels. Thus, there is no evidence that greater variability in kinematics for lower-level pitchers

correlated with greater variability (and possibly greater risk of injury) in joint loads. As with

previous studies of pitching kinetics, the current study quantified joint net force and torque.

It would be valuable to calculate the loads on individual hard tissue and soft tissue, but this is

beyond the current study.

It is worth noting that some previous studies of variability within an athlete analysed

coefficients of variation (Bradshaw et al., 2007; Queen et al., 2006; Salo and Grimshaw,

1998), whereas the current study analysed standard deviations. The coefficient of variation

(standard deviation divided by mean, multiplied by 100%) would be a good approach for

some parameters with clear, true “zero” values – such as velocity, force, and torque

parameters – in the current study. However, it would not work well for linear and angular

position parameters, because the value of the denominator of coefficient of variation depends

on the position arbitrarily chosen as “zero”. Furthermore, reporting position variability in

degrees or centimetres might be more meaningful to most readers than percent of position.

The data show that high school pitchers have less variation than youth pitchers. It is hard

to say why this progression occurred, since such factors as body development with age,

greater pitching experience, and talent selection of high school teams all come into play. But

after high school, the most talented pitchers are generally drafted into the Minor Leagues,

while others play at the collegiate level. This is supported by Table I, which shows that the

ages and pitching background of the Minor League and college groups were comparable,

while the Minor League pitchers generated greater ball velocity. There were almost no

kinematic differences between these two groups (Table II), implying that consistency most

likely increases with pitching experience and body development.

A limitation of the current study was that only five pitches were analysed per participant.

Future research involving more pitches per athlete may generate more information. Such

future research might include a wider range of pitch velocity and location for each pitcher.

Also, the current study included only fastballs. A pair of previous studies – one with

collegiate pitchers and the other with youth pitchers – compared biomechanics among the

fastball, curveball, change-up, and slider (Dun et al., 2008; Fleisig et al., 2006). Although

both studies found kinematic and kinetic differences among the various pitch types,

variability within individuals was not reported. It is possible that variability is an issue for

particular pitch types. Finally, the current study analysed only data from foot contact to ball

release. Since there were kinematic differences at the time of foot contact, it would be

valuable to collect and compare the kinematics and timing in the windup and stride phases

preceding foot contact.

Results from the current study also provide some insight regarding the use of a sample trial

from three-dimensional automatic digitization. For instance, Table II shows that individual

standard deviation was typically 68 to 88 for shoulder external rotation at foot contact and

18 to 58 for other angles. (This deviation is a combination of actual variation in the pitcher’s

mechanics and the error in the digitizing hardware and software.) Thus analysis of a single

trial for a pitcher may produce 18 to 88 of sampling error in joint angle. Furthermore, recent

research has shown accuracy concerns in three-dimensional measures of shoulder internal

rotation near full elbow extension, which may contribute to errors in this variable (Elliott and

Alderson, 2007; Gordon and Dapena, 2006). Analysis of a single fastball trial also implies

potential sampling error of angular velocity (such as 20 8/s for the pelvis or upper trunk;

Table II), timing (e.g. 1% to 6% of the pitch cycle for time of maximum angular velocity;

Table III), joint force (e.g. 3% body weight; Table IV), and joint torque (e.g. 0.1% to 0.5%

body weight £ height; Table IV).

Variability in baseball pitching biomechanics 19

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Conclusion

The current study showed a trend of decreased variation in kinematics with development

level. Most improvement in kinematic consistency (i.e. decreased variability) appeared to

occur from the youth to high school level. To help increase consistency in the younger

pitcher, coaches may focus on a more consistent and stable windup and stride. Particular

attention can be given to the positioning of the front leg as it lands on the front of the mound.

Decreased variability with higher levels is most likely acquired from experience and physical

development. Furthermore, young pitchers who do not achieve consistent mechanics may

not perform well enough to advance to higher levels.

Somewhat surprisingly, no significant differences in timing variation were found among

the competition levels. Thus, either timing variability is similar among all levels or the

current study was not strong enough to detect subtle differences. Differences in kinetic

variations among levels were non-significant.

While variation for some parameters did not differ among competition levels, it does not

mean that there was no variation. All kinematic, temporal, and kinetic parameters showed

variations within each pitcher. If biomechanists choose to use a sample trial when

analysing a baseball pitcher, they must accept potential variability between this one trial

and the athlete’s biomechanics during other pitches. To reduce this risk of error, an

analysis of multiple pitches per individual is recommended for biomechanical research and

diagnosis.

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