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This is to certify that the
thesis entitled

BIOMECHANICAL AND PHYSIOLOGICAL EFFECTS OF
PLYOMETRIC TRAINING ON HIGH SCHOOL
CROSS-COUNTRY RUNNERS

presented by

Mark C. Lathrop

has been accepted towards fulfillment
of the requirements for

M.S. Kinesiology

degree in

 

 

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6/01 cJCIRC/DateDuepss-p. 15

BIOMECHANICAL AND PHYSIOLOGICAL EFFECTS OF
PLYOMETRIC TRAINING ON HIGH SCHOOL

CROSS-COUNTRY RUNNERS

By

Mark C. Lathrop

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE
Department of Kinesiology

2001

ABSTRACT
BIOMECHANICAL AND PHYSIOLOGICAL EFFECTS OF
PLYOMETRIC TRAINING ON HIGH SCHOOL
CROSS-COUNTRY RUNNERS
By

Mark C. Lathrop

The purpose Of this study was to compare the effectiveness Of a traditional cross-
country training regimen with a training program that includes plyometrics. Eighteen
male and female high school cross-country runners were matched according to their
previous running experience and randomly assigned to two groups. Participants followed
a traditional cross-country training program for six weeks, except that two to three times
a week the plyometrics group replaced some of their easy run training with 15-20 minutes
Of plyometric training.

The participants were tested before and after the six-week training period. A
treadmill test was used to determine running economy, lactate threshold, and V0,”. The
participants ran across a force plate in order to determine support time, braking time, and
braking change in velocity. Participants were also timed on a 3200-meter run.

Participants in both groups significantly improved their running economy and

3200-meter time (without a change in V0 ), but there were no significant differences

2m.“
between groups on these variables. The plyometric group significantly decreased their

braking change in velocity over the training period, while there was no change in the

running group.

ACKNOWLEDGMENTS

I would like to briefly acknowledge the numerous individuals who have contributed to

this thesis and my academic progress.

0 Dr. Eugene Brown, my major professor and thesis advisor, for encouraging me to
pursue my interest in exercise science and for his great assistance to me in all stages
of research, including planning, writing, and collecting biomechanics data.

0 Dr. Dianne Ulibarri, for introducing to me and teaching me about the field of
biomechanics and for advice on the use of statistics in exercise science.

0 Dr. Chris Womack, for his assistance on developing the idea for this study, for all of
his advice on the physiological aspects of this study, for his assistance in developing

the V0 test, and for help in collecting the treadmill data.

0 Individuals who recently made it possible to collect biomechanics data by helping
design and build the Biomechanics Research Station

0 Individuals who assisted me at the Biomechanics Research Station, especially David
Wisner, who also aided me greatly by showing me how to set up and use the APAS
system, and Miguel Naravez, Tony Moreno, Ethel Leslie, Sean Cumming, Pete
Osmond, David McCreight, and Uday Vadre, who were an immense help in
collecting the biomechanics data.

0 Individuals who helped with treadmill testing, especially Pete Osmond and Chad

Paton who spent an enormous amount of time at the Human Energy Research

Laboratory collecting data for this study.

iii

Mr. Beatty, my tenth grade biology teacher, who gave me the opportunity to write my
first paper related to exercise science- “The effects of running on the human body.”
David Lathrop (N8LU), my father, who built and helped modify the timing systems
that were used during the biomechanics test.

Betty Lathrop, English instructor at Baker College, my mother and first marathoner in
our family, who helped with editing this paper.

Melinda Lathrop, DVM, my best friend and wife, who always supported me in the
pursuit of my degree, and who devoted a tremendous amount of time as I worked on
this thesis watching our two children, Andrew and Rebecca, while pregnant with our

third child (Luke).

iv

TABLE OF CONTENTS

 

 

 

 

 

 

 

 

 

LIST OF TABLES ................................................................................. viii
LIST OF FIGURES ................................................................................. ix
LIST OF ABBREVIATIONS AND SYMBOLS ................................................ x
CHAPTER ONE
Introduction ................................................................................... I
Overview Of the Problem ............................................................ 1
Need for the Study .................................................................... 2
Statement of the Problem ............................................................ 6
Hypotheses ............................................................................. 7
Overview of the Research Methods ........... . .................................... 7
Definitions of Terms .................................................................. 8
CHAPTER TWO
Literature Review .......................................................................... ll
Physiological Factors of Running Performance ................................. 11
Biomechanical Aspects of Running .............................................. 15
Strength Training .................................................................... 20
Plyometrics ........................................................................... 24
CHAPTER THREE
Methods ...................................................................................... 31
Research Design ..................................................................... 31

 

 

 

 

 

 

 

 

 

 

 

 

Participants ........................................................................... 32
Intervention ........................................................................... 33
Data-Collection Procedures ........................................................ 38
Data Analyses ........................................................................ 43
CHAPTER FOUR
B_e_s_u_lt§ ...................................................................................... 44
Training ............................................................................... 44
Results Of Significance Tests ...................................................... 44
Correlations ........................................................................... 45
Performance Variable ............................................................... 46
Biomechanical Variables ........................................................... 47
Physiological Variables ............................................................ 51
CHAPTER FIVE
Discussion ................................................................................. 53
Cautions in Interpreting Results ................................................... 56
Recommendations for Further Research ......................................... 58
Implications and Conclusions ...................................................... 59
APPENDICES
A. Running History Form ............................................................... 62
B. Plyometric Training Schedule ...................................................... 64
C. Descriptions of Plyometric Exercises .............................................. 68

 

vi

D. Individual Characteristics and Training Data ..................................... 75

 

 

 

 

E. Individual Data for RunningPerformance ......................................... 77
F. Individual Data for Biomechanics Variables (Best Trial) ........................ 79
G. Individual Data for Physiological Variables ....................................... 81
H. Consent Form ......................................................................... 83
REFERENCES ...................................................................................... 86

vii

Table 1.1.
Table 3.1.
Table 3.2.

Table 4.1.

Table 4.2.

Table 4.3.

Table 4.4.

Table 5.1.

LIST OF TABLES

Summary of Strength Training Studies .............................................. 5
Characteristics Of Participants ....................................................... 34
Plyometric Exercises Used in Present Study ....................................... 36

Mean 3200-meter Time Before (Pretest) and After (Posttest)
Six Weeks of Training ................................................................ 47

Ground Reaction Force Pretest Data for Subject Number 1450

Biomechanics Variables Before (Pretest) and After (Posttest)

Six Weeks of Training ............................................................... 51
Physiological Variables Before (Pretest) and After (Posttest)

Six Weeks OfTrarnrng52
Types Of Training for Cross-Country Runners .................................... 61

viii

LIST OF FIGURES

Figure 1.1. Diagram of braking and propulsion phases ....................................... 10
Figure 3.1. Photograph of cross—country runners skipping .................................... 39
Figure 3.2. Photograph of a subject performing hurdle hops (with tires) ................... 39
Figure 3.3. Photograph Of biomechanics testing area .......................................... 41
Figure 3.4. Biomechanics testing area ........................................................... 42
Figure 4.1. Examples Of anteroposterior ground reaction force-time histories ............. 48

ix

Abbreviation/Symbol

AMTI

ANOVA

APAS

BAV

BT

GRF

HR

HV

LT

MANOVA

MART

PAV

PLYO

RE
RUN
SD
ST

VO

Zmax

% Diff.

LIST OF ABBREVIATIONS AND SYMBOLS

Definition
Advanced Mechanical Technology Inc.
Analysis Of Variance
Ariel Performance Analysis System
Braking Change in Velocity
Braking Time
Ground Reaction Force
High Resistance strength training with free weights
High Velocity strength training (plyometrics)
Lactate Threshold
Multiple Analysis of Variance
Maximum Anaerobic Running Test
Propulsion Change in Velocity

Group whose participants replaced some run training with
plyometrics

Running Economy

Group whose participants only did run training
Standard Deviation

Support Time

Maximum aerobic power

Percentage difference between BAV and PAV
= (|PAV| - BAV) / BAV

CHAPTER ONE

Introduction

Overview of the Problem

Frank Shorter’s gold medal marathon performance in the 1972 Munich Olympics
and Bill Rodger’s numerous victories in the Boston Marathon in the 1970’s signaled the
beginning of the running boom in the United States. With this increased participation in
running, some top runners, their coaches, and other running enthusiasts (Fixx, 1979;
Galloway, 1984; Henderson, 1983; Higdon, 1978; Steben & Bell, 1979) began to write
about their training methods and why they were successful. Also, specialists in exercise
physiology and biomechanics (Anderson, 1996; Costill, 1979; Daniels, 1998; Hickson,
Rosenkoetter, & Brown, 1980; Martin, 1997) wrote about the many benefits of running as
well as the best training programs to improve performance. Consequently, many
recreational runners in the 1980’s and 1990’s began to describe their training methods
with words and phrases such as long slow distance, fartlek, interval training, repetitions,
lactate threshold running, and hill training. There has been a lot of research about the
success of these types of training methods among elite distance runners competing in
five-kilometer to marathon distances (e. g., Conley, Krahenbuhl, & Burkett, 1981;
Henritz, Weltman, Schurrer, & Barlow, 1985; Wilson, Newton, Murphy, & Humphries,
1993). However, there has been less research about how a strength training program such

as plyometrics affects the performance of young distance runners. Most strength training

studies have focused on the physiological effects of strength training on college age and
elite runners. There is a need then to study the biomechanical as well as the physiological
effects of plyometric training on high school cross-country runners.
Need for the Study

High school cross-country coaches are faced with many challenges. They have a
short season (typically four to five weeks Of conditioning followed by six to eight weeks
Of competition). Also, today’s athletes often have after-school jobs that cause them to
leave practice early or miss practices. Finally, coaches need to be concerned about the
physical growth and development of young athletes who may be more susceptible tO
injuries (Apple, 1995). According to Martin (1997), a l30-pound male running ten miles
at 6:30 min/mile pace contacts the ground about 5,280 times with each foot. The total
impact force on each foot during this run is up to 686 US. tons or 624,728 kilograms of
force. Thus, high school coaches need training programs that efficiently train their
runners yet keeps them free of injury. However, many high school coaches train their
athletes the way they were coached or follow the training program of the local or national
star athlete, which may not be appropriate for their team. There is a need for these
coaches to have training programs available to them that are based on sound research that
address the special needs of high school athletes. High school cross-country coaches
need to know the most effective ways to train runners during the limited practice time
that the coaches have with their teams.

Physiological factors such as VOZW (Foster, Costill, Daniels, & Finley, 1978),

lactate threshold (Farrell, Wilmore, Coyle, Billin, & Costill, 1979), and running economy
(Conley & Krahenbuhl, 1980) have often been used to predict endurance running

performance. Anderson (1996) stated that the keys to success in endurance running are

aerobic power production and runners’ resistance to fatigue. To improve in these areas,
runners need to increase the level of physical stress or strain they can handle or increase
the speed at which a sustainable level of stress occurs. Training programs based on
improving these components have been developed. These training programs usually
involve easy long runs, tempo runs (running at a pace above lactate threshold), repetitions
(e.g., 8 x 200 meters with full recovery), and intervals (e.g., 6 x 400 meters with one
minute rest). These types of workouts are aimed at improving oxygen delivery.
However, oxygen delivery may not be the only limiting factor of performance. Muscle
power, or the failure of muscle contractility, may also limit performance (Noakes, 1988).
Bulbian, Wilcox, and Darabos (1986) found that anaerobic power is a good predictor Of

race success among cross-country runners who have similar VO values. Cross-country

runners need to maintain relatively high velocity for an entire race. Thus, neuromuscular
characteristics related to voluntary and reflex activation, muscular force, and elasticity
take on an important role in running performance as well as anaerobic characteristics
(Paavolainen, Hakkinen, Hamalainen, N ummela, & Rusko, 1999). These types of
characteristics may be improved by some types of strength training, which may then lead
to improved running performance.

It may seem that using resistance training to improve endurance performance
violates the principle of specificity. However, endurance performance requires muscle
strength and anaerobic power which is needed for climbing hills and for the final sprint at
the end of a race (Bulbian et al., 1986). Increasing maximum power allows a runner to
work at a lower percentage of his or her maximum VOZM so he or she can last longer at

lower work rates (Stone, Fleck, Triplett, & Kraemer, 1991). This may be very beneficial

in running as it lowers the energy costs of running. According to Di Prampero et al.

(1993), a five percent decrease in energy cost of running is responsible for an
improvement of 3.8% in distance running.

Many researchers have investigated the effects of various types Of strength
training on runners. Some of the studies are summarized in Table 1.1. Hickson et al.
(1980) and Hickson, Dvorak, Gorostiaga, Kurowski, and Foster (1988) showed that
weight training can increase the endurance time to exhaustion without a change in V0,“.
Weight training has also been shown to increase lactate threshold in biking (Marcinik et
al., 1991) and lead to a 15% improvement in two-mile run time (Hortobagyi, Katch, &
Lachance, 1991) . Other researchers reported that plyometrics can increase the
acceleration and maximum speed of sprinters (Delecluse et al., 1995) and can improve
maximum power as measured by the MART test (N ummela, Mero, & Rusko, 1996a). In
recent studies, Paavolainen et al. (1999) and Turner, Owings, and Schwane (1999) found

that plyometric training can improve running economy without a change in V0 while

2",...
Nicholson and Sleivert (1999) found that weight training can improve ten-kilometer time,
lactate threshold, and running economy.

Since there is some theoretical basis that strength training can improve running
performance, the question remains as to which type of strength training is best for high
school cross-country runners. Many strength training studies have used traditional
weight training which strengthens isolated muscles groups. However, multiple muscle
groups are used in running. Runners need exercises that develop balance and
coordination of many muscle groups (Martin, 1997). Therefore, strength training that
simultaneously emphasizes and develops many muscle groups that are specific to running

may be best for runners. Also, since in each step of running there is an eccentric

contraction followed by a concentric contraction, a strength training program for runners

Table 1.1. Summary of Strength Training Studies

 

Author

Subjects

Training method

Results

 

Delecluse et al.
(1995)

18-22 year old
male physical

HR-free weights
HV-plyometrics;

I-IR-increased acceleration
HV-increased

 

 

 

education 3 days/wk for 9 weeks acceleration, maximum
students speed, better lOO-m time
Hickson et al. 9 active, 18- Weight training-legs; Endurance time to
(1980) 27 year Old 5 days/wk for 10 weeks exhaustion increased
men (12% run, 47% bike);
VOZW unchanged; lactate
concentration not raised
Hickson et al. 6 males, 2 Weight training; Endurance time to
(1988) females; 3 days/wk for 10 exhaustion increased
29-39 year weeks; added to (11% run, 13% bike);
old, trained existing endurance VOW unchanged; 10 km
training times inconclusive
Hortobagyi et 28 college Circuit training for 40 15% improvement in two
al. (1991) males minutes followed by mile run time

2-mile run; 3 days/wk
for 13 weeks

 

Marcinik et al.

18 untrained

Weight training arms

On bike 12% increase in

 

 

(1991) males, 25-34 and legs; 3 days/wk for lactate threshold; no
year old 12 weeks change in VOZW

Nicholson & 30 male and Weight training for 21 Improve 10-km time,

Sleivert (1999) female weeks lactate threshold, and
recreational running economy
runners

Nummela et al. 9 well-trained 60-600 meter intervals; Maximum power

(1996b) sprinters weight training; increased by 3.4% (as

plyometrics measured on MART)

 

Paavolainen et

22 elite, male

Explosive strength

S-km time, running

 

 

 

 

 

al. (1999) distance training: sprints, jumps, economy, 20 m velocity,
runners, high velocity weight and 5 jump improve with
23-24 year old training; run close to no change in VOW

lactate threshold flee

Turner et al. 18 male and Plyometrics for six Running economy

(1999) female trained weeks improved with no change
distance in VOZM or jump height
runners,
29 year old

 

 

should include these types of actions. Plyometric training, or jump training, meets this
criteria and would seem to be suitable for running.

Coaches have used plyometrics to train track and field athletes, football and
soccer players, wrestlers, and even golfers (Bompa, 1996; Radcliffe & Farentinos, 1999).
However, there has been little mention of using plyometrics with distance runners.
Furthermore, there have been very few studies that have shown how plyometric training
affects distance running performance. Many plyometric studies used male runners in
their twenties as subjects (see Table 1.1). The present study is unique in that relatively
inexperienced male and female high school runners were studied to investigate if
plyometrics is an effective way of improving cross-country running performance. Also,
the few studies that have been conducted on this type of training (Delecluse et al., 1995;
Nummela et al., 1996; Paavolaninen et al., 1999; Turner et al., 1999) have mainly focused
on physiological changes with little regard to biomechanical changes. The question
remains as to whether plyometrics causes changes in the biomechanics of running which
result in beneficial physiological changes. Thus, there is a need for a study that
investigates the effects of plyometric training on high school cross-country runners. High
school cross-country coaches would be interested in knowing if plyometrics is an
effective use of their limited practice time, and researchers interested in biomechanics and
running may be interested in the changes in kinetics that may occur with this type of
training program.
Statement of the Problem

This study compared a traditional high school cross-country training program
with a training program that replaced some traditional training with intense plyometric

training sessions conducted two to three times per week for six weeks. Major outcome

variables were 3200-meter run time, running economy, lactate threshold, VO, time in

.max’

support, braking time, and braking change in velocity.
Hypotheses
It was hypothesized that after six weeks of plyometric training, the plyometrics
group would:
I) spend less time in the support phase, including less braking time;
2) exhibit a decrease in the change in velocity during braking;
3) display improvement in running economy;
4) increase their lactate threshold velocity; and
5) have greater improvement in 3200-meter run time than the run-only group.
Overview Of the Research Methods
Eighteen male and female high school cross-country runners from three local high
schools were randomly assigned to either a plyometrics group (PLYO) or a running group
(RUN) using a matched-pairs technique based on their previous running experience.
During a six-week training period, participants did their regular cross-country training
administered by their coach. The plyometrics group replaced some of its easy run training
with 15-20 minute sessions of plyometric training two to three days per week. The run-
only group ran at an easy pace during this time.
All participants were tested before and after the six-week training period. The
testing consisted of three components: treadmill test, biomechanics evaluation, and a
running performance measure. The treadmill test was used to determine running
economy, lactate threshold, and V0,“. In the biomechanics evaluation, participants ran
across a force platform at 3.8 m/s (7:04 min/mile) pace. Anteroposterior and vertical

ground reaction force-time histories were obtained in order to determine support time,

braking time, and braking change in velocity. Running performance was determined by
the time to run 3200 meters on a track. MANOVA was used to determine if there was an
overall effect of the intervention. If there was an overall effect, ANOVA was performed
on that particular effect for each dependent variable. Alpha was set at 0.10 for

MANOVA and for ANOVA.

Definitions of Terms

 

Amortization phase: Time from the beginning of an eccentric contraction to the
beginning of the following concentric contraction.

Braking change in velocity The change in horizontal velocity during the braking phase.
It equals the braking impulse divided by the mass in kilograms of the subject.

Braking impulse: The area between the anteroposterior ground reaction force curve and
the time axis during the braking phase. It equals the integral of the anteroposterior ground
reaction curve during the braking phase (see Figure 1.1).

Braking phase: The initial phase of stance in which the anteroposterior ground reaction
force Opposes forward movement.

Braking time: The time spent in the braking phase (see Figure 1.1).

Cruise intervals: Repeated runs of 3 to 15 minutes at threshold pace, with a short one
minute recovery between intervals.

Eartlek training: Swedish for “speed play.” Alternating fast-paced running with slow-
paced running. Distances run at different speeds and time spent running varies and is
determined by how the runner feels.

Hill training: A type of repetition training involving running hard uphill and/or downhill

with a long recovery between each repetition.

Interval training: Training at a pace at 98-100% of V0 or 98-100% of maximum heart

rate. Intervals can last from 30 seconds up to 5 minutes with a recovery period equal to
or slightly less than the time spent running the preceding interval.

flaw threshold: The pace or work intensity just prior to a sudden increase in blood
lactate concentration.

Long slow distance runs: Easy, recovery runs at a pace at 65-75% of V0 or 70-80% of

Zmax

maximum heart rate.

Maximum aerobic power (V0 ): Maximum ability Of an individual to take up,

transport, and utilize oxygen in the working muscle.

Plyometrics: A type Of explosive strength training that involves an eccentric contraction
immediately followed by a concentric contraction of the same muscle or muscle group.
Propulsion change in velocity: The change in horizontal velocity during the propulsion

phase. It equals the propulsion impulse divided by the mass in kilograms of the subject.

Propulsion impulse: The area between the anteroposterior ground reaction force curve

 

and the time axis during the propulsion phase. It equals the integral of the anteroposterior
ground reaction force curve during the propulsion phase (see Figure 1.1).

Propulsion phase: The second phase of stance where the direction of the anteroposterior
ground reaction force is in the forward direction.

Repetition training: Training at a pace greater than V0,,“ and equal to or faster than race
pace. Each repetition lasts less than two minutes with a recovery that is four times as
long as work bout.

Running economy: Amount of oxygen consumed relative to a runner’s body weight and

speed at which he or she is running. It is the rate of submaximal oxygen consumption.

Specificity of training: Principle that metabolic and physiological adaptations are
specific to the type of training done; that is strength training induces specific strength-
power adaptations while aerobic exercise results in specific endurance adaptations with
only a limited interchange of benefits between muscular strength and aerobic training.
Stride frequency: The number of strides per minute.

Stride length: The distance between the heel contact of one foot to the next heel contact
on the same foot.

Support time: The time one foot is in contact with the force plate. Due to noise
associated with force platform, contact is defined as the period of time which the vertical
GRF exceeded 16 Newtons (Munro, Miller, & Fuglevand, 1987).

Tempo runs: A 20 minute run at threshold pace.

Threshold pace: Training at a pace at 86-88% of V0,

-ma\ ’

or 90% of maximum heart rate.

See Cruise intervals and Tempo runs.

  
    

Impulse

m Braking
Illlllllllllllll

Propulsion
Impulse

Anteroposterior GRF

 

 

Figure 1.1. Diagram of braking and propulsion phases.

CHAPTER TWO

Literature Review

Physiological Factors of Running Performance

There are many factors that influence middle distance and distance running
performance. These events range from the 800 meters which has more emphasis on
speed to the marathon which requires more endurance. Coaches and researchers (Conley
& Krahenbuhl, 1980; Farrell et al., 1979; Maffulli, Testa, Lancia, Capasso, & Lombardi,

1991) have found that VO running economy, and lactate threshold are important

factors that influence distance running performance. Distance running coach and exercise
physiologist, Jack Daniels (1998), wrote that training for speed, economy, and aerobic
power are keys to success in 1500 meter to 3000 meter races. Another factor influencing
running performance that is mentioned infrequently is the energy cost of overcoming air
resistance. Pugh (1970) found that 7.5% of the total energy cost in middle distance
running is due to air resistance. This paper focused mainly on factors which influence
five kilometer cross-country running performance which requires a blend of speed,
strength, and endurance (Martin, 1997). According to Martin success at this distance
requires athletes to train for “speed-strength” and “speed-endurance.”

Maximum aerobic power. Maximum aerobic power, or VO has Often been used

Zinax’

as a predictor of running performance (Noakes, 1988). For example, Foster et al. (1978)

found that VO was highly correlated with one-mile, two-mile, and six-mile race times.

Zlnax

ll

It has been defined as the maximum ability Of an individual to take up, transport, and
utilize oxygen in the working muscle (Green & Patala, 1992). Daniels (1998) added that
the amount of oxygen consumed depends upon the amount of oxygen delivered and used
by muscles and how well muscles deal with CO2 and lactic acid during a run. Daniels

recommended that to increase VO,

-nru ’

athletes must stress the oxygen delivery and
utilization system by running three to five minute intervals at about 3000-meter to 5000-
meter race pace. Conley et al. (1981) studied elite male runners for 18 weeks and found

that VO increased the most following interval training, while endurance training had

little effect on V021,“. It is important for 1500-meter to 3000-meter runners to have a
high aerobic capacity so they do not need to rely on the anaerobic system until the end of

the race. A high V0,

-llld‘

is also crucial to SOOO—meter runners as race pace is close to 100%
of aerobic capacity. The present study investigated how plyometric training affects high
school runners’ aerobic capacity.

Lactate threshold. Another factor influencing running performance is lactate
threshold. This has been defined as the pace just before which blood lactate levels rise
sharply, or more formally, the work intensity that initiates a sudden increase in blood
lactate concentration (Martin, 1997). Weltman et al. (1987) found that the lactate

threshold for most male runners is at about 83% of their VO or 87% of their

maximum heart rate. Blood lactate levels are determined by the amount of lactic acid
produced and by how much lactate is used by the muscles, heart, and liver (Daniels,
1998). Runners need to keep blood lactate levels down so they can run at fast speeds but

still have a low blood lactate concentration (Henritze, Weltman, Schurrer, & Barlow,

1985). Daniels often has his runners do “tempo runs” where they train at or close to their

12

lactate threshold. This type Of workout provides quality, low stress training, which can
aid in recovery from high intensity running.

Running economy. Although, coaches and physiologists have traditionally used
VO2m as a predictor Of running performance, several authors (Anderson, 1996; Daniels &

Daniels, 1992; Noakes, 1988) have reported that runners with similar VO values can

Zmax

vary widely in their performance in distance races. Daniels (1974) studied two runners

who had vastly different VO values (72 ml/kg/min and 57 ml/kg/min) but had similar

two mile race times. The difference in predicted performance was attributed to a
difference in running economy. Running economy reflects the level of physical stress
associated with steady state running at a certain pace (Anderson, 1996). Williams and
Cavanagh (1987) defined running economy as the rate of submaximal oxygen
consumption, or VOzsubmax, while Daniels (1998) formally defines it as the amount of
oxygen being consumed relative to runners’ body weight and speed they are running. For
example, a runner who uses 50 ml of oxygen per kilogram of body weight per minute
while running at 6:00 min/mile pace is more economical than a runner who uses 55 ml of
oxygen. Therefore, runners need to improve their running economy so they can run
faster without an increase in energy expenditure. Thus, some researchers (Conley &

Krahenbuhl, 1980) have stated that for runners with similar VO running economy is a

better predictor of performance than aerobic power.

Although the factors that influence running economy have not been scientifically
identified, Martin (1997) believed that an increase in fitness, strength, and coordination
may improve running economy, while Daniels (1998) recommended running repetitions

(short intervals with full recovery) to improve economy. Conley et al. (1981) found that

interval training of varying lengths and recovery periods resulted in a greater increase in

13

running economy than endurance training. In the present study, plyometric training, a
type of strength training, was investigated to see how it affects running economy.

Other physiological factors. Even though VO lactate threshold, and running

lmru’

economy are all important factors in predicting distance running performance, it is
inappropriate to use any one factor by itself in predictions. A runner could have a high

VO but a poor running economy, which would result in a poorer performance than

2mm

what is predicted by his or her VO, value. On the other hand, a person may be a very

-IIIJX

economical runner but have a relatively low VO which could result in a poorer

lrirax ’

performance than what was predicted by looking only at running economy.
As a result, researchers such as Bulbian et al. (1986) prefer a multifactor approach
that uses many factors to predict running performance. Others have studied factors that

take into consideration both running economy and V0 Daniels (1974) and Noakes,

Zrnax '

Myburgh, and Schall (1990) have used velocity at V0 or peak velocity, to

Irrrax’

successfully predict running performance. This is the velocity at which VO2mm is first

realized and takes into account V0 and running economy. Thus, two runners with

2mm

similar race times would have the same peak velocity, but one may achieve this velocity

with a high V0 and low economy, while the other has a lower VO but is more

2m.“ ’ Zmax

economical.
Other researchers have studied the percentage of VOZM needed to maintain a
particular running speed. Wilcox and Bulbulian (1984) found that over the course of a

college season, female cross country runners increased their V0 and improved their

Zmax

running economy (but not significantly). However, there was a significant reduction in

runners’ percentage VO at two speeds. By the end of the season, running at 241

2Inax

l4

m/min required almost the same percentage of V0 as running at 215 m/min at the

beginning of the year.
Biomechanical Asmts of Running

Much of the research in running has focused on the physiological aspects of
running. However, some researchers have studied biomechanical factors that may
influence running performance. To better understand the biomechanical analysis of
running, a summary of the different components of a running cycle is reviewed.

Ecker (1985) divides a complete running cycle into three phases: the driving phase,
recovery phase, and the braking phase. During the driving phase, the body is pushed
forward by extending the hip, knee, and ankle. This phase continues until the foot leaves
the ground. During the recovery phase both feet are in the air after the driving foot leaves
the ground well behind the body’s center of mass. In the braking phase, the foot opposite
the one used during the driving phase touches the ground a little ahead of the body’s
center of mass which causes a braking effect. The body moves forward until the center of
mass is ahead of the support foot, which leads to the next driving phase. Collectively the
braking and driving phases are called the support, or stance phase, while the recovery
phase is also known as the non-support or swing phase (Hamill & Knutzen, 1995).

Mechanical efficiencg One area of biomechanical study is mechanical efficiency.
This is the ratio of the total amount of mechanical work done divided by the metabolic
energy expended to do it (Norman, Sharratt, Pezak, & Noble, 1976). Highly efficient
runners have a larger work output at a low physiological cost, or if the speed is fixed,
they have a low mechanical work output at a low physiological cost. Since it appears
mechanical efficiency could be an important factor in running performance, it has been

studied by numerous researchers (e.g., Kaneko, Fuchimoto, Ito, & Toyooka, 1983;

15

Luhtanen, Rahkila, Rusko, Viitasalo, 1990; Norman et al., 1976). However, it is a
controversial subject with varied results depending on how mechanical work and the
metabolic cost are calculated. Efficiency is the biomechanical counterpart to running
economy, but some have found a weak relationship between mechanical efficiency and
economy (Gregor & Kirkendall, 1978; Norman et al., 1976).

Although there have been problems with mechanical efficiency, researchers have
found some correlation between other biomechanical variables and factors related to
running performance. For example, Williams and Cavanagh (1987) found that 54% of
the variability in running economy can be explained by biomechanical variables.
Anderson (1996) reports that running economy is correlated with height and body mass.
The present study investigated the relationship between running economy and time in
support and braking change in velocity. .

Stride length and stride frequency. Stride length and stride frequency are important
components in running as they determine the speed of the runner (velocity = stride length
x stride frequency). Increasing either will make the runner faster, although increasing
stride frequency will usually result in a shorter stride length and may not change the
speed. Similarly, increasing the stride length usually decreases the stride frequency, and
there is little change in speed.

Brandon and Boileau (1992) found that runners with longer strides had faster 1500-
meter and 3000-meter times. Daniels (1998) reported that elite runners averaged at least
90 strides per minute in distances ranging from 3000 meters to the marathon, while
beginning runners have a stride frequency that is up to 15 strides per minute less than the
elite runners. Also, Nelson and Gregor’s (1976) longitudinal study found that nine of ten

college runners tended to decrease their stride length and increase their stride rate over

16

the course of their four-year college careers. Because of information like this, some
coaches have advised runners to increase their stride length or stride frequency
(Anderson, 1994).

Coaching runners to change their stride length or stride frequency may not be
beneficial as several studies have shown that runners are most economical when they
freely choose their stride length (e.g., Cavanagh & Williams, 1982; Morgan et al., 1994).
Apparently, runners can integrate all the relevant factors through processes related to
perceived exertion to run at a stride length which minimizes energy cost. Messier et al.
(1986) had runners intentionally overstride and understride, and the runners reported
greater relative perceived exertion in both cases.

Despite these results, there may be some cases where changing stride length or
stride frequency is helpful. Runners who overstride place their support foot too far
forward (ahead of their center of gravity), and there is an increased braking effect
resulting in deacceleration. If the foot is too far back (understriding), there is an increase
in stride frequency, but overall speed decreases (Ecker, 1985). Anderson (1996)
hypothesized that overstriding requires a lot of power during propulsion which leads to
excessive vertical oscillation of center of mass and a footstrike with a large braking force.
Too high of a stride frequency may increase internal work due to an increased frequency
of reciprocal movements such as arm swinging.

If a runner is overstriding or understriding, training and feedback can help optimize
the freely chosen stride length (Morgan et al., 1994). A natural way to increase stride
length may be strength training (Ecker, 1985).

Other kinematic factors. There have been numerous other kinematic factors related

to running form which may influence running performance. Anderson (1996) reported

17

that elite runners have more acute knee angles during the swing phase while good runners
plantar-flexed 10 degrees more during toe-off. He also reported that when compared to
less economical runners, runners with better economy have a greater maximum angle of
the thigh during hip extension, smaller knee angle at toe-off, greater maximum plantar
flexion velocity and greater horizontal heel velocity at footstrike, slower thigh extension
velocity, and lower knee flexion velocity. Williams and Cavanagh (1987) found that
runners with better economy had a shank angle of greater deviation from vertical at
footstrike, lower minimum knee velocity during support phase, more acute knee angles at
midsupport, less plantar flexion at toe-off, and less arm movement.

There has been little work done on the effects of vertical oscillation on running
performance. Gregor and Kirkendall (1976) studies of elite female marathoners indicated
that better runners have less vertical oscillation, while Williams and Cavanagh (1987)
reported a nonsignficant trend of more economical runners having a lower vertical
oscillation. Luhtanen et al. (1990) explained that to increase running economy during the
stance phase, runners should strive for an optimal path of center of gravity by lowering
their center of gravity minimally with a small knee flexion during the eccentric phase.

Temporal aspects. There have not been consistent findings on the relationship
between support time and swing phase time on running economy and performance.
Nelson and Gregor (1976) found that runners improved their performance times and
decreased their time in support when tested at the same speed throughout their four-year
college careers. Williams, Cavanagh, and Ziff (1987) studied elite female marathoners
and found that they spent less time in support than a group of novice runners running at
the same speed. Paavolainen et al. (1999) found that highly economical, elite runners who

did explosive strength training had shorter contact times than less economical, elite

18

runners who mainly did endurance training. However, Williams and Cavanagh (1987)
found that that there was no significant relationship between running economy and
support time. The present study investigated how plyometric training affects time in
support.

Ground reaction forces. Many studies (Keller et al., 1996; Munro et al., 1987;
Nilsson & Thorstensson, 1989) have reported that increasing the speed of running
increases the vertical ground reaction forces. However, there has been little research
done on the relationship between ground reaction force curves and running performance.
Williams and Cavanagh (1987) found that runners with better economy have more of a
rearstriking pattern, which they hypothesized provides more cushioning than forefoot
strike. This causes less demand on muscles. They also found that more economical
runners had a significantly lower first peak for vertical ground reaction forces and a trend
toward a smaller peak anteroposterior force and a smaller peak vertical ground reaction
forces. Williams, Cavanagh, and Ziff (1987) found that when compared to novice
runners, elite female runners have a lower first vertical peak and a higher second peak, a
greater change in vertical velocity, and a higher peak braking force. In a related area,
Kaneko et al. (1983) found that better runners have less change of velocity during contact
with the ground. Martin (1997) reports that the most efficient runners decelerate the least
at footstrike and get the maximum forward movement with every footstrike. The present
study investigated if plyometric training decreased the braking change in velocity in

runners.

l9

Strength Training

Coaches have traditionally used a variety of training methods for their athletes.
Typically coaches have mixed interval training and repetition training with long runs and
tempo runs to improve running performance. There have been fewer reports of coaches
using strength training with runners, particularly to train middle distance and distance
runners. The current study focused on how strength training may improve distance
running performance.

Definitions. There are numerous ways of describing strength. Strength has been
defined as the “ability to develop force against an unyielding resistance in a single
contraction of unrestricted duration” (Atha, 1981). Others have defined it as the
maximum force or tension that can be developed (Martin, 1997; Radcliffe & Farentinos,
1999). How strength is defined also depends on how it is measured. Static strength is
strength measured isometrically where muscle length does not change. Dynamic strength
can be measured using the one—repetition maximum, or the maximum amount of weight
that can be lifted one time. Explosive strength involves a fast, maximal effort which
combines velocity and force (Atha, 1981). Strength is also related to power which is a
combination of strength and speed. Power is the rate at which work is done and also
equals force multiplied by velocity. It is the application of force through the range of
motion within a unit of time (Radcliffe & Farentinos, 1999).

Strength can also be thought of as having three components: a muscular
component, a neural component, and a mechanical component (Martin, 1997). The
muscular component depends on the cross sectional area of the muscle, the muscle fiber
length, and the muscle architecture (e.g., how much the myosin and actin overlap). The

neural component involves how the stimulus strength and frequency influences motor

20

recruitment. The mechanical component (which cannot be changed) explains how force
and lever arm distance result in the torque which produces limb rotation.

Weight training. Strength training has long been thought to be beneficial in
sprinting as it is an explosive activity that utilizes fast-twitch fibers. For example,
Delecluse et al. (1995) found that lifting free weights three days a week for nine weeks
improved the acceleration of sprinters. Nummela et al. (1996b) found that maximum
power increased by 3.4% in 400-meter runners who weight trained and did plyometrics
for ten weeks. Delecluse (1997) wrote that strength, power, and speed are all important
components of training for sprinters. Thus, strength training is beneficial as it can
increase the hypertrophy of type II fibers, cause rapid recruitment of motor units, increase
firing of motor neurons, and result in greater synchronization of motor neurons.

The benefits of strength training for sprinters may also be helpful to endurance
performance. Weight training and circuit training three to five days per week for at least
ten weeks has been shown to improve cycling and treadmill endurance time to exhaustion
(Hickson et al., 1980; Hickson et al., 1988; Marcinik et al., 1991), improve two-mile run
time by 15% (Hortobagyi et al., 1991) and improve ten-kilometer run times (Nicholson
and Sleivert, 1999). Interestingly. the subjects in these studies and others (Hunter et al.,
1987; Hurley et al., 1984) were able to improve without a significant change in their
treadmill V02m~ The improved endurance running performance in these studies may be
due to an increased lactate threshold and running economy that some researchers found
(Marcinik et al., 1991; Nicholson & Sleivert et al., 1999).

Other types of strength training. Other types of strength training that have been
studied use the resistance of an athlete’s own body weight to improve performance. Hill

workouts and explosive strength training such as plyometrics fall in this category. Hebel

21

(1983) showed that regular downhill running can improve muscle peak torque and muscle
endurance in knee flexors. Hill running has also been reported to increase power
(Humphreys & Holman, 1985), increase spring in ankles, and develop power in the toes
and feet (Hebel, 1983).

Plyometric training is another alternative to weight training. Sprinters who did nine
weeks of plyometrics increased their acceleration, maximum speed, and 100-meter
performance (Delecluse et al., 1995). Nummela et al. (1996a) found that weight training
combined with plyometrics increased maximum power among sprinters. Paavolainen et
al. (1999) and Turner et al. (1999) showed that plyometrics improved running economy.
Paavolainen’s subjects also significantly improved their five-kilometer run time.

Benefits of strenggh training. There are a variety of explanations of how strength
training might enhance endurance performance. It seems counterintuitive that resistance
training can benefit endurance performance as endurance training improves the ability to
do low load, hi gh-repetition exercise, while resistance training improves the ability to
perform high load, low repetition exercise with seemingly little effect on endurance. To
say that resistance training can benefit distance runners at first glance appears to violate
the principle of specificity of training.

Typical training for distance running includes long, slow runs and shorter, faster
interval training. These types of workouts increase capillary density so more oxygen can
reach more parts of the working muscle, increase the size and distribution of
mitochondria, and can lead to an increase in oxidative enzyme activity, which leads to a
rate at which oxygen can be processed (Daniels, 1998; Tanaka & Swensen, 1998).
Tanaka and Swenson also reported that endurance training decreases the size of type II

fibers and changes the ratio of type IIa to type IIb fibers with Na increasing in number

22

and 11b decreasing. Also, this type of training may decrease the maximum force
generating capability of type I and 11a fibers. This may actually be beneficial as Tanaka
and Swenson (1998) reported that it may increase fiber efficiency. This decreased force
generating capability may help explain why some studies have found that endurance
training hindered strength development (Dudley & Djamil, 1985; Hunter, et al., 1987).

Muscular benefits. Resistance training can increase muscle fiber size and

 

possibly fiber number, and changes the ratio of type II fibers (Tanaka & Swenson, 1998).
The percentage of type IIa fibers increase and 11b decreases. Tanaka and Swenson also
reported that strength training has little or no effect on capillary density, may increase the
glycogen content of trained muscles, and decrease the density of mitochondria (due to
increased fiber size).

One of the benefits of supplementing endurance training with resistance training is
that it may reverse some of the negative muscular changes of endurance training such as a
possible decrease in fiber size (Tanaka & Swenson, 1998). It also may help reduce or
reverse the decrease in force production due to a decrease in the velocity of shortening of
muscle fiber from endurance training. Tanaka and Swenson asserted that faster, larger,
and stronger fibers can generate more force. Thus, resistance-trained runners may be able
to exercise longer at submaximal work rates by reducing the force contribution from each
active myofiber or by using fewer fibers. Stone et al. (1991) agree that as each motor unit
gets stronger with training, fewer motor units are needed to perform at a given
submaximal workload. Tanaka and Swenson also state that stronger type I fibers may
allow resistance- trained runners to delay recruitment of less efficient type II fibers. This
hypothesis is supported by studies that found that strength training improves running

economy (Turner et al., 1999). Also, Stone et al. (1991) reported that high volume

23

weight training can lead to a slight increase in aerobic power, a larger increase in
anaerobic power, and an even greater increase in anaerobic capacity.

Neural benefits. In addition to the muscular benefits, there could also be neural
benefits to using resistance training with distance runners. Strength training can cause
motor units to become better synchronized and recruitable so more motor units are
contributing with each working at a lower intensity (Sale, 1988). Also, changes in the
nervous system could allow force to develop more rapidly by improving the ability of
muscles to become stiff. Strength training may lead to an increased facilitation of the
length-feedback component originating from the muscle-spindle which increases muscle
stiffness, and by increased inhibition of the Golgi tendon which decreases muscle
stiffness (Komi, 1986). Increasing muscle stiffness may be important in running as
Komi, Salonen, and Jarvinen (1984) found that during moderate speed running, the
Achilles tendon force reached four to five times body weight during support phase. This
force was reached very rapidly, which implies that the stiffness of the triceps surae
muscle must be very high during the support phase of running. Since these neural
adaptations can lead to increased strength in as little as six to eight weeks, they have
important implications for the present study where the training period lasted six weeks.
Plyometrics

A type of strength training that is becoming more popular among coaches is
plyometrics. Plyometric training is a type of explosive strength training that involves an
eccentric (lengthening) contraction immediately followed by a concentric (shortening)
phase (Bompa, 1996; Chu, 1992; Radcliffe & Farentinos, 1999). It often involves some
type of jumping exercise such as skipping, bounding, or hopping. It was first thought of

as a secret Russian training technique. However, coaches have been using jump training

24

for many years. Track and field athletes in the 1920’s and 1930’s usedjump training as
part of their gym training (Bompa, 1993). In the 1950's and 1960's, Russian track and
field coach Yuri Verkhoshansky used jumping exercises to train his sprinters and jumpers
(Radcliffe & Farentinos, 1999). This type of training became more popular after it was
used to train a Russian Olympic sprint champion, Valeri Borzov.

Although jump training is not new, it is just recently that the term "plyometrics"
became popular. In the last ten years it has been used by football and basketball players,
world class cross-country skiers, weight lifters, cyclists, track and field athletes,
marathoners, and mountain runners. Who first used the word "plyometrics" is debated.
Chu (1992) says the term was first used by Fred Wilt, an American track and field coach.
Radcliffe and Farentinos (1999) state "plyometrics" first appeared in a 1966 paper by
V.M. Zaciorskij, a Russian coach and exercise scientist. The origins of the term are also
not agreed upon. Chu says plyometrics has Latin origins and means "measurable
increases". Radcliffe and Farentinos state that it is derived from the Greek word
"pleythyein" which means “to augment" or "to increase. "Plio" means "more" and "plyo"
means “to move". "Metric" literally means "to measure".

Stretch-shortening cycle. It has been hypothesized that the reason plyometrics
training is an effective training tool is related to elastic characteristics of muscles and the
stretch-shortening cycle. Muscles in many movements (including gait) undergo a stretch-
shortening cycle where an eccentric contraction that stretches muscle or muscle group is
followed by a concentric contraction which shortens it (Radcliffe & Farentinos, 1999).
This is exactly what occurs in plyometrics. Vertical jump studies by Cavagna, Komarek,
Citterio, and Margaria (1971) and Cavagna, Zamboni, Faraggiana, and Margaria (1972)

showed that muscles will contract more forcefully and quickly from a prestretched

25

position. These studies also showed that the more rapid the prestretch, the more forceful
the subsequent concentric contraction. The stretch response is the property of a muscle
tissue that enables greater muscular tension. As the parallel components of muscle fibers
increase beyond resting length the tension in them increases (Radcliffe & Farentinos,
1999). This lengthening usually involves a prestretch (such as landing and then taking off
again in hopping) where muscles move in the opposite direction of the desired force
application.

The muscle spindle reflex also plays a role in plyometrics. When the muscle spindle
detects a lengthening of the muscle, an impulse is sent to the spinal cord and then motor
impulses are transmitted back to the stretched muscle causing it to contract (Bompa,
1996).

Plyometrics may enhance activation of neuromuscular components and increase
efficiency of neural actions and muscular performance (Radcliffe & Farentinos, 1999;
Paavolainen et al., 1999). Explosive strength training may cause alterations in neural
control during stretch-shortening exercises of running in both voluntary activation and
inhibitory and/or facilatory reflexes (Paavolainen et al., 1999). Then muscle groups may
increase their ability to respond more quickly and powerfully to little and quick changes
in muscle length (Radcliffe & Farentinos, 1999). Thus, plyometrics enables faster and
more powerful changes of direction which occur with each running step. The present
study investigated if these changes result in less time in support and a decreased change
in braking velocity during the support phase of running. Explosive strength training such
as plyometrics may also lead to an increase activation of motor units. Since these are
neural changes, this type of training may lead to improvements in just a few weeks with

less hypertrophy than what is associated with weight training (Paavolainen et al., 1999).

26

Given the neural benefits of plyometrics, it may also have a positive effect on
muscle power. This is "the ability of the neuromuscular system to produce power during
maximal exercise when glycolytic and oxidative energy production are high and muscle
contractility may be limited” (Paavolainen et al., 1999). This improved muscle power
could be especially beneficial to cross-country runners climbing hills in the middle of a
race or striving to have a strong finish when they are already fatigued.

Elastic energy return. Another potential benefit of plyometrics is that it may
improve athletes' ability to utilize elastic energy return. The range of elasticity of a
muscle is the ability of a muscle to change in length and in tension. It is proportional to
the ability of a tissue to resist forces and return to its original shape upon releasing a load
(Radcliffe & Farentinos, 1999). Cavagna (1977) wrote a classic paper on the storage and
utilization of elastic energy in skeletal muscle that many others have cited. He found that
muscles forcibly stretch and brake as well as propel the body. The change in length of
muscles is in the opposite direction of the force developed by the muscle. When muscles
are forcibly stretched, negative work is done by the muscle so mechanical energy is
absorbed by the muscle. Much of this stored mechanical energy is often transferred into
heat energy (when the muscle relaxes), but some of it can be used during subsequent
active shortening.

Cavagna (1977) describes several pieces of evidence that support the idea that
muscles use stored elastic energy based on his review of vertical jump and gait studies.
First, following an eccentric contraction there is an increased mechanical efficiency of
positive work done (Cavagna & Kaneko, 1977). Recall mechanical efficiency equals the
ratio of positive work done to the chemical energy to do the work. Efficiency may

increase following a lengthening of the muscle because part of the positive work comes

27

from the recoil of elastic elements, not just from the muscle converting chemical energy
to mechanical energy. Also, there is power enhancement. When shortening follows a
stretching, the force production is high from the beginning of the movement so there is a
greater acceleration of the mass (Cavagna & Kaneko, 1977). There is also a greater
amount of positive work done by a muscle when it shortens immediately after stretching
than when it shortens from an isometric contraction. Cavagna (1977) cautions that the
muscle does not behave as a simple spring since its elasticity changes, due to the
stretching which leads to a greater compliance during subsequent shortening. Thus, the
amount of elastic energy delivered immediately after stretching for a given force is
greater (up to two to three times greater) than when shortening takes place from a state of
isometric contraction. In counter-movement jumps, Komi and Bosco (1978) found that
subjects were able to utilize 50-90% of the energy absorbed in the stretching phase. They
also found further evidence of elastic energy return in drop jumps. They found that as
dropping height increased, subjects were able to jump higher indicating a greater storage
of elastic energy.

The elastic energy return is greatest when there is a minimum time delay between
lengthening and shortening (Komi & Bosco, 1978) and the lengthening tension is not too
great (Cavagna, 1977). Cavagna stated that if there is a long time delay between
lengthening and shortening, the force at the end of the muscle-spring decreases, wasting
part of the elastic energy as heat. Also, the greater compliance induced by the previous
stretching tends to be reduced in the interval between stretching and shortening.

Elastic energy return is important in running as it occurs with each step. Negative
work is being done as the foot contacts the ground during an eccentric contraction.

Positive work is being done as the muscle shortens to push-off. Thus, elastic energy

28

stored during eccentric contractions contributes to propulsion (Cavagna & Kaneko,
1977). There is evidence that actomyosin crossbridges and tendons are storage sites of
elastic energy, and that the achilles tendon and the tendon in arch of the foot can store up
to 35% and 17% of the available energy, respectfully (Ker et al., 1987; Cavagna &
Citterio, 1974). Williams and Cavanagh (1987) found that runners could realize as much

as a 47%-62% energy savings (in V02) due to elastic energy return since their subjects
had a 24% savings in V02 during knee bend experiments and since ground reaction forces

in running are two to three times larger with a time duration half as long. Some
researchers feel that varying abilities to store and release elastic energy may explain
individual differences in running economy (Anderson, 1996).

Plyometrics can be effective when used with endurance run training because it
involves eccentric contractions shortly followed by concentric contractions. This is what
occurs with each running stride. Runners can learn to optimize their running by
exploiting free elastic energy and minimizing metabolic requirements. Optimization
demands precise timing and integration of temporal, kinematic, and kinetic elements
which come from practice and timing (Anderson, 1996). Plyometrics provides this type
of training. It can help with the timing and integration of muscle activity so elastic energy
is stored and reused more effectively. Anderson also states that the balance between
eccentric and concentric contractions may influence running economy since elastic
energy is stored during eccentric contractions which are less costly than concentric
contractions. The economy of movement can be increased by changing temporal patterns
of movement, which also may help use elastic energy more effectively. The idea that

plyometrics may improve elastic energy return in runners provides support for the

29

hypothesis in the present study that the subjects in the plyometric group will improve
their running economy more than the subjects in the running-only group.

The changing temporal pattems Of movement may appear in the support phase of
running. Paavolainen et al. (1999) found that elite endurance runners who supplemented
their regular run training with nine weeks of explosive strength training (including
plyometric exercises) significantly reduced contact time during the support phase while
running at a constant speed. The reduction in contact time was observed to be significant
even after just six weeks of training. The control group of elite runners who did just the
regular run training had a small increase in contact time during the same time period. A
reduction in contact time may be beneficial to runners as Kram and Taylor (1990) found
an inverse relationship between rate of energy used for running and time in support.

In summary, plyometric training may develop the nervous system so that it will
react quickly to the lengthening of the muscle so that the muscle can shorten rapidly with
maximal force and with the greatest utilization of elastic energy. This type of strength
training may also reverse some of the negative muscular changes of endurance training
and increase the strength of each motor unit so fewer motor units are needed to perform at
a given submaximal workload. During the present study, the experimental group
replaced some of their regular run training with plyometrics to investigate how some of
these neural and muscular changes affect certain biomechanical and physiological factors
such as support time, braking time, braking change in velocity, running economy, lactate
threshold, and V0,“. These factors may in turn lead to improved running performance.
This study attempted to give a biomechanical and physiological explanation as to why

running performance may improve with plyometrics training.

30

CHAPTER THREE

Methods

Research Desi gr

The research design for this study was a nonequivalent control group pretest-
posttest design (Thomas & Nelson, 1996). The independent variable was the type of
training program with the treatment group (PLYO) replacing some of its run training with
plyometric training two to three times per week and the control group (RUN)
participating in only run training.

Several threats to internal validity should be considered. Many of these threats such
as history, maturation, testing, statistical regression, subject selection, and participants
dropping cross-country were controlled for by randomly assigning participants to the two
groups. For example, the history effects were partially controlled for as participants
were randomly assigned to two groups and participants on each high school team
practiced together except for the plyometrics training sessions. However, the history of
the participants was still a problem as some of the athletes chose to train outside of
practice by running extra or by lifting weights. Also, some participants were involved in
other sports such as biking as well as cross-country.

Testing could also have been a problem if many participants in one group ran poorly
in the time trial portion of the pretest because of inexperience, not knowing how to pace

themselves at this distance, for example. They may have improved greatly on the posttest

31

partly because of their improved knowledge of how to pace themselves; experienced
athletes would not have this advantage.

Subject selection could also be a problem if one group was comprised of more
physically fit people, which might make it more difficult for the fit participants to

improve factors such as their performance times and V0 as unfit participants.

Different levels of physical fitness were controlled for by using a matched-pair technique
(Thomas & Nelson, 1996). Participants from each school were paired based on the
number of years of previous competitive running experience and number of weeks run in
the previous six weeks. Then each pair was randomly assigned to the treatment and
control group. To help eliminate problems with fatigue during testing, participants were
asked to have at least one easy day of training before the 3200-meter run and before the
treadmill test.

Although many of the threats to internal validity were controlled by randomly
assigning participants to the two groups, external validity could be a problem as the
participants were not randomly chosen from all high school cross-country teams in the
United States. So the results may be generalized only to high school students from
similar types of large, urban schools whose cross-country coaches follow a similar
training program as those in the study.

Participants
Cross-country coaches from mid-Michigan high schools were contacted in the
spring of 2000 to determine their interest in seeking runners to participate in the study.

Coaches from three area boys and girls high school cross-country teams expressed

interest. Two of the schools are part of a large urban district, while the third is in a large

32

suburban district. All schools are class A schools, the classification for the most
populous schools (more than 1100 students) in Michigan.

Approximately 50 runners received information about the study in July 2000
before one of their summer conditioning practices. Eighteen athletes volunteered to
participate in the study. After completing a questionnaire on their running history
(Appendix A), these subjects were paired based on their previous running experience and
current fitness levels and randomly assigned to either a plyometric group (PLYO) or a
running-only group (RUN). Two subjects did not complete the six-week study, which
left PLYO with seven subjects (six males and one female) and RUN with nine subjects
(seven males and two females). The participants and one of their parents or legal
guardians were required to sign a consent form. Note: The consent form in Appendix H
indicates that the participants would run five kilometers for the running performance
tests, although they actually ran 3200 meters. This study was approved by the Michigan
State University Committee on Research Involving Human Subjects.

General characteristics of the participants are summarized in Table 3.1. PLYO
and RUN were represented by runners of similar ages, heights, and weights. The groups
were also similar in years of prior running experience and prestudy running. Prestudy
running is the number of weeks in the subjects ran at least three times per week in the six
weeks prior to the beginning of the study. It is an indication of how much time they took
off after their last period of regular running (spring track season for many of subjects).
Intervention

Run training. Both groups followed the training programs directed by the coaches at
their schools. In general these programs consisted of two to three medium-hard to hard,

continuous runs of four to nine miles each week, and one day of two to three miles of

33

interval training (intervals ranging from 400 meters to 1000 meters). “Hard” workouts
were often alternated with “easy” two to four mile runs.

Table 3.1. Characteristics of Participants

 

 

 

PLYO (n=7) RUN (n=9)

Mean (SD) Range Mean (SD) Range
Age (yrs) 15.9 (1.4) 14-18 16.4 (.73) 16-18
Height (cm) 174.9 (8.3) 162.5-186.6 172.1 (9.5) 152.1-184.1
Pretest weight (kg) 64.7 (10.0) 51.5-83.7 61.8 (7.6) 47.7-69.8
Posttest weight (kg) 64.9 (9.1) 54.7-83.1 61.2 (7.6) 47.0-70.4
Run Experience“ (yrs) 2.7 (1.3) 2-5 2.8 (1.5) 0-5
Prestudy running” (wks) 4.9 (2.2) 0-6 4.5 (1.7) 2-6

 

8Number of years of competitive running prior to study. I“Number of weeks running in six
weeks prior to study.

Two to three times a week the plyometric group replaced some of their run training
with 15-20 minute plyometric training sessions. This frequency has been suggested to be
Optimal by several researchers (Bompa, 1996; Chu, 1992; Radcliffe & Farentinos, 1999).
Some coaches and authors (Radcliffe & Farentinos, 1999) suggested that plyometric
training be done on “easy” days so that muscles will not be fatigued during other parts of
practice. However, if high intensity practices are preceded and followed by plyometrics
on the “easy” days, then muscles will not have time to recover as the anaerobic alactic
and lactic systems using glycogen as fuel are taxed every day (Bompa, 1996). In the
current study, plyometrics were usually done on designated “hard” days as Bompa
recommended. This gives the body at least 48 hours to recover from the high intensity

practice and enabled the participants to give maximal, quality efforts at each plyometric

34

training session. During these training sessions, participants in RUN did an easy run so
that training volume would be similar for both groups.

Plyometric training sessions were conducted by the researcher the first two weeks.
The remaining sessions were monitored by the coaches with the researcher assisting
periodically. Coaches were given a chart with the specific exercises for their runners to
do each day and a description of each plyometric exercise (see Appendices B and C).
Three subjects did much of their plyometric training on their own due to conflicts with
their team’s practice schedule, so they were given the same information on plyometrics as
the coaches.

Plyometric training. Some basic rules should be followed when doing extensive

 

plyometric training. Plyometrics exercises should be done on soft surfaces such as grass
or dirt following a thorough warmup. Athletes should be somewhat flexible and have a
good overall fitness level (Radcliffe & Farentinos, 1999). Also, eccentric training such as
plyometrics can be stressful to muscle cells and should be introduced gradually. Thus,
Bompa (1996), Chu (1992), and Radcliffe and Farentinos (1999) recommended that
plyometrics training should gradually progress from simple, low-intensity, low-impact
exercises to more complex, hi gher-intensity, high-impact exercises (see Table 3.2).
Radcliffe and Farentinos (1999) teach that training should undergo a “progressive
overload” that gradually changes the weight or load, the height or distance jumped, and
how rapidly and intensely the exercise is done. This philosophy was followed in the
context of the six-week training period as well as in individual training sessions. For
example, depth jumps should not be introduced at the beginning of intervention, nor
should they be the first exercise done during a training session in the sixth week of

plyometrics training.

35

Table 3.2. Plyometric Exercises Used in Present Study

Intensity Level

 

Low Moderate High
Jumps
Pogo Double-leg butt kick Single-leg stride jump
Squat jump Split jump Stride jump crossover
Box jump Scissors jump Depth jump
Box jump (multiple
response)
Bounds and Skips
Prancing Single-leg stair bound
Galloping Altemate-leg stair bound
Speed skipping Altemate-leg bound
Ankle flip Power skipping
Hops
Hurdle hops Single-leg butt kick Single leg speed hop
Double-leg speed hop Single-leg hop for height Hurdle hops (multiple
response)

Richochets
Stadium hops

 

Note. Names of exercises are from Bompa (1996), Chu (1992), and Radcliffe and

Farentinos (1999).

Because of the explosive nature of plyometrics, a full recovery between sets is

important so that each set can be done with proper technique and at a high enough

intensity (Bompa, 1996). Chu (1992) recommended a work to rest ratio of 1:5 up to 1:10.

So ten seconds Of exercise would be followed by 50 to 100 seconds of rest. Less

recovery can be given between sets if the goal is to develop muscular endurance, as long

as the athletes are still using proper technique. Radcliffe and Farentinos (1999)

recommended one to two minutes of rest between high intensity sets, and 30 to 60

seconds between sets of low impact exercises. These rest times allow neuromuscular

systems to recuperate.

36

In order for plyometrics to be effective, athletes need to use proper technique. It is
important for the eccentric contractions in these exercises to be quickly followed by a
concentric contraction; that is there should be a short amortization phase. Amortization is
the time from the beginning of the eccentric contraction to the beginning of the concentric
contraction (Radcliffe & Farentinos, 1999). If amortization is slow, more stored elastic
energy is converted into heat and less energy is used in the concentric action (Cavagna,
1977). As a result of slow amoritization, Cavagna found that the force developed by the
muscle decreased since part of the stored elastic energy is wasted. Plyometrics can be
used to train athletes to have a shorter amortization phase so they can utilize this stored
energy better, which may result in greater force and power in the muscle and a decreased
energy cost (Farentinos & Radcliffe, 1999).

Participants and their coaches were taught techniques that would enable the athletes
to have short amortization phases. They were taught to have short, quick, landings with
minimum knee flexion and contact time. Also, they were instructed to maintain a locked
ankle upon landing and to land with a dorsiflexed foot and two-thirds to a full foot
ground contact (Radcliffe & Farentinos, 1999). They were told to put more weight on the
front of the foot and to not roll from heel to toe. To ensure proper technique, “single-
response drills” were used when introducing a new exercise (Radcliffe & Farentinos,
1999). In these drills one intense effort is done, and then the athlete is stopped and
checked for technique. For example, when doing a simple jumping exercise, athletes
would take-off, land, and pause while the coach or researcher checked for proper posture,
balance, and stability. Then the drill was repeated. In “multiple-response drills” the
exercise was repeated many times. Emphasis was placed on having a short, quick

landing, followed by a rapid, powerful take-off. Note that Williams et al. (1987) found

37

that more economical runners were able to dorsiflex their ankle faster and to a greater
angle during support. Developing proper technique is important.

Plyometric exercises that were used in this study are listed in Table 3.2. They have
been chosen because of their potential to develop power in the extensors and flexors in
the legs, hips, and torso, which Martin (1997) states are important in running. Also,
Radcliffe and Farentinos (1999) identified many of these exercises as being particularly
beneficial for runners. Most of the names for these exercises are from Radcliffe and
Farentinos’ (1999) plyometrics book, although others (Bompa, 1996; Chu, 1992, Martin,
1997; Paavolainen et al., 1999) have used similar exercises with different names. Figure
3.1 and Figure 3.2 illustrate two of these exercises.

All of these exercises were not done every training session. Four to six exercises
were selected for each plyometrics session depending upon the complexity and intensity
of the exercises selected. Each training session included exercises from each category
(jumps, bounds and skips, and hops). Each exercise consisted of two to four sets of 4-10
repetitions. Quality was emphasized over volume. If athletes could not do four sets at
high intensity, they were instructed to do just three sets. Bounds and skips were done over
a 30 to 50 yards distance instead of using repetitions. Again, over the six-week treatment
period, the intensity of exercises increased from low to high. However, even when doing
high intensity exercises, some low intensity exercises were done as wannups.
Data-Collection Procedures

There were three parts to the data-collection: treadmill test, biomechanics
evaluation, and a test of running performance. Data was collected in two sessions
separated by at least one day. The test of running performance was done in session one.

The treadmill test and biomechanics evaluation were done during session two.

38

 

Figure3. 2. Photograph Of a subject perfOrming
hurdle hops (with tires).

Treadmill test. The treadmill test was done at the Human Energy Research
Laboratory at Michigan State University. Subjects began running at a pace that was
below their lactate threshold velocity. Then they were in a steady state so lactate

threshold was not a confounding variable in measuring running economy. The starting

39

speed was set at four stages (2 mi/hr) below the speed at which lactate threshold was
predicted to be reached. Each subject’s lactate threshold (LT) velocity was predicted by
the following equation (adapted from Weltman et al., 1987) using the subject’s 3200-
meter time on the pretest:
LT velocity = [493-2278 x (3200-m time)] x 60/1609.

The same initial starting speed was used on the posttest. Subjects ran at the initial speed
for five minutes. The next stages were three minutes long with the speed increasing by
0.5 mi/hr each stage. After each stage the treadmill was stopped for one minute while a
fingertip blood sample was obtained. The three-minute stages continued until it was
determined that lactate threshold had been reached. Then the speed was kept constant
while the grade was increased by 2% every minute until VO2mm was reached. Blood
lactate levels were analyzed with a Yellow Springs Instruments 2300 Stat Plus automated
blood lactate analyzer (Yellow Springs, OH). Lactate threshold was determined to be
reached if there was a significant increase (greater than 0.3 mmol/L) from baseline lactate
levels on two consecutive stages. Ventilation and VO2 were recorded every minute from
the average of three consecutive 20 second measurements from a Sensor Medics 2900
metabolic measurement cart (Yorba Linda, CA). Running economy was determined by
averaging the V02 values the last two minutes of the initial five-minute stage. VOZM was
determined as the largest mean VO2 value obtained during three consecutive 20-second
VO2 measurements. Heart rate was continually assessed by a heart rate monitor (Polar
Advantage).

Biomechanics evaluation. Measurements of component forces and temporal data

were obtained in the Biomechanics Research Station at Michigan State University using a

40

0.51 x 0.56 m AMT I force platform (Waterton, MA). Figure 3.3 shows a photograph of

the biomechanics testing area.

vd‘r ~ .‘. I
r l .
- Phototransrstors

Force
Platform

 

Figure 3.3. Photograph of biomechanics testing area.

Data was sampled at 1000 Hz and amplified with an AMTI amplifier. The force
platform was mounted flush with a lS-meter wooden platform. Some subjects used a
longer runup by running down a hallway and up a six inch high ramp onto the testing
area. Phototransistors (Vernier Software) paired with halogen lights were placed two
meters on either side of the force plate to verify speed. Figure 3.1 illustrates the testing
area.

Subjects were videotaped while running and were told that the videotape would be
used to conduct a biomechanical evaluation of their running form. They were not
informed of the presence of the force platform. Subjects were instructed to run as

naturally as possible across the testing area at a constant speed of 3.8 m/s (7:04 min/mi).

41

After several practice runs, each subject ran across the testing area 20 to 50 times in order
to achieve the goal of ten acceptable trials. Subjects were asked to move their starting
position forward or backward if the researcher noticed that they missed the force
platform. Acceptable trials were those where the subject’s entire foot landed on the force
platform without a noticeable adjustment of stride and the subject was within 5% of the
test speed. The actual number of acceptable trials for each subject ranged from 4 to 18
trials. Force-time histories for all three orthogonal directions were recorded on a

computer (Ariel Dynamics) and analyzed with Ariel Performance Analysis System

 

 

 

(APAS) software.
‘ 15 meters ’
Light Light
D‘— 4 meters—an
.iiiiisa
4’21??? . -.

 

 

 

 

 

    

Phototransistor Phototransistor

Computer

with interface

Figure 3.4. Biomechanics testing area.

Performance test. The running performance test was conducted at the subjects’

 

high schools. Participants ran 3200 meters (eight laps) on their high school track. All

participants started together and were given split times at the end of each lap. Times
were measured with a Timex Ironman chronograph.
Data Analyses

Means and standard deviations were calculated on each variable using standard
methods. Correlation coefficients were calculated to determine relationships among
variables. To determine if there was an overall effect of the intervention on the primary

dependent variables, 3200-meter time, running economy, VO time in support, and

Zirrax’
braking change in velocity were analyzed with multiple analysis of variance (MANOVA)
using Pillai’s trace test statistic. If there was a significant F-value, analysis of variance
(ANOVA) was calculated on each dependent variable to determine differences within

groups or between groups. Alpha was set at 0.10 for MANOVA and for each ANOVA

IOSI.

43

CHAPTER FOUR

Results

Training
The participants in the plyometric group (PLYO) reported completing an average

of 13 i 3.6 of the 15 scheduled plyometric training sessions. Participants in both groups

ran about the same number of miles per week (PLYO-25.4fl: 7.8; RUN-27.3 i 12.42).

However, the large variability of average miles run per week within groups should be
noted. Individuals’ average weekly mileage during the six-week training period ranged
from 12-34 miles per week in PLYO and 9-47 miles per week in RUN. There was also a
large variability of miles run by subjects in individual weeks throughout the training
period. One subject in each group reported running 0 miles one week, while a subject in
RUN reported running 80 miles one week. The maximum number of miles run in one
week reported by a subject in PLYO was 54 miles. Details of individual training data is
in Appendix D.
Results of Significance Tests

All sixteen subjects completed the biomechanical and physiological tests.
However, lactate threshold velocities were not obtained for everyone. On the posttest a
time for running 3200 meters was not obtained for one subject in PLYO and two subjects
in RUN due to scheduling conflicts and an injury.

To determine an overall effect of the primary dependent variables, running

economy, VO 3200-meter time, support time, and braking change in velocity were

2 max ’

44

analyzed with MANOVA using Pillai’s trace test statistic. Results show there was a
significant main effect of Time, E (11,4) = 1725, p < .0001. Thus, when examined as a
whole, there was some change in the dependent variables from pretest to posttest. There
was not a significant main effect of Group or of the Group by Time interaction.

The five dependent variables were then each analyzed in a Group (PLYO vs.
RUN) x Time (Pretest vs. Posttest) two-way mixed ANOVA. There was a main effect of
Time for running economy, E (l, 14) = 44.47, p < .0001, 3200-meter time, F (1,14) =
8.13, p = .013, and braking change in velocity, 15 (1, 14) = 6.19, p = .026. There was also
a Group x Time interaction effect for braking change in velocity, 13(1, 14) = 3.31, p = .09.
There were no significant differences between groups on any of the other dependent
variables.
Correlations

Correlations were calculated between the different dependent variables and
changes in dependent variables from pretest to posttest. There were high correlations
between 3200-meter time and lactate threshold velocity (1 = - .84 on pretest; I = - .92 on
posttest), and moderately high correlations between 3200-meter time and V0,” (_r = -.65
on pretest; [ = -.79 on posttest). The participants with the higher lactate threshold

velocities and V0 tended to have lower 3200-meter times.

Zmax’
There was a moderate correlation (1 = - .42) between change in lactate threshold

velocity and change in 3200-meter time. Participants who displayed a greater increase in

lactate threshold velocity from pretest to posttest tended to have a greater decrease in

their 3200-meter time from pretest to posttest. Also, there was a moderate correlation (r =

.43) between the change in 3200-meter time and previous years of running experience.

45

Participants who had spent more years training for running tended to have less change in
3200-meter time from pretest to posttest.

There was also a moderate correlation between lactate threshold velocity and
braking time (I = .40) on the posttest, but there was no relationship between these
variables (I = .04) on the pretest. There was a low correlation between 3200-meter time
and support time (I = -.39) on the posttest, but there was no relationship between these
variables on the pretest. However, there was a moderate correlation (_r: = .45) between the
change in 3200-meter time and change in support time. Larger decreases in support time
were associated with larger decreases in 3200-meter times. There was low correlation (g =
.22) between lactate threshold velocity and support time. There was no relationship (_r <
0.20) among the other variables.

Performance Variable

Means and standard deviations of 3200-meter times are summarized in Table 4.1.
The participants significantly improved (p < 0.10) their time to run 3200 meters from
pretest to posttest. The plyometric group’s average 3200-meter time improved by 31
seconds or 3.9%, while there was a 69 second or 8.0% improvement in RUN.
Improvements in individual 3200-meter times ranged from 5 seconds to 69 seconds in
PLYO, and ranged from 12 seconds to 5 minutes 9 seconds in RUN. The subject in RUN
who decreased her 3200-meter time by more than five minutes had no previous
competitive running experience. One subject in PLYO ran six seconds slower on the
posttest while a subject in RUN ran 13 seconds slower. Individual results for 3200—meter

times are listed in Appendix E.

46

Table 4.1. Mean 3200-meter Times Before (Pretest) and After (Posttest) Six Weeks of
Training

 

 

 

Pretest Posttest
Mean 3200-m Mean 3200-m
Group time (minzsec) Range time (minzsec) Range
(SD) (SD)
PLYO’ 13:16 11:27- 12:45 11:22-
(1.25“) 16:05 (1.09) 14:53
RUNc '
13:51 11:31- 12:42 11:03-
(2.8) 20:24 (1.8) 16:12

 

'p = 7 on pretest, n = 6 on posttest. hStandard deviations for 3200-meter times are in
minutes. cn = 9 on pretest, n = 7 on posttest.
Biomechanical Variables

Problems with biomechanics data. During testing a good trial was defined as a
trial where the subject ran within 5% of the preestablished running speed, and the
subject’s entire foot landed on the force plate without a noticeable adjustment in stride.
Subjects ran up to 50 trials in order to obtain the goal of ten good trials. Due to time
constraints, the actual number of good trials obtained for each subject ranged from four to
eighteen trials.

An additional criteria for an acceptable trial was that the subject’s horizontal

velocity from initial contact to departure from the force platform was approximately

unaltered. This means that the braking change in velocity (BAV) and the propulsion
change in velocity (PAV) were approximately equal. If BAV were greater than PAV, then

the subject was decelerating across the force plate. If PAV were larger, then the subject

was accelerating across the force plate. Figure 4.1 illustrates how accelerating and

decelerating affected anteroposterior ground reaction force curves.

47

  
 

 

Braking Impulse

HUM Propulsion Impulse

'”lllllillllllllllllllllllllllllIII1

Time (s)

'aoa

§
I

 

Anteroposterior GRF (N)

E"
l

-200

 

Figure 4.1a. Example of deceleration across the force platform: braking
impulse (area under the curve) is greater than propulsion impulse.

Subject 14, Trial 7, Pretest

200 " Braking Impulse

HIM Propulsion Impulse

111W

Tum (s)

-100 —
-150 '—
.2oo —
-250 .—

Anteroposterior GRF (N)
o

 

 

Figure 4.1b. Example of acceleration across the force platform: braking
impulse (area under the curve) is less than propulsion impulse.

Figure 4.1. Examples of anteroposterior ground reaction force-time histories.

48

If PAV was within 25% of BAV the subject was considered to be running at an

approximately unaltered speed. This criteria reduced the number of acceptable trials

considerably. Fourteen of the sixteen subjects performed at least one trial where BAV
and PAV were within 10% of each other on the pretest and posttest. On the remaining
two subjects’ best trials (in terms of BAV and PAV difference), there was a difference of

18% and 23% between BAV and PAV.

Another problem with analyzing the biomechanical data is the large variability
that each subject displayed from trial to trial on numerous biomechanical variables. An
example of this variability is shown in Table 4.2 with one subject’s pretest data. This
subject ran through the testing area 32 times, and he had 12 trials (shown in Table 4.2)
where his entire foot landed on the force platform. Although these trials were run at
approximately the same speed (3.7 - 3.9 m/s) through the testing area, there was still
some variability between trials on many biomechanical variables. For example, support

time (ST) ranged from 0.250 seconds to 0.275 seconds, while BAV ranged from 0.17 m/s

to 0.33 m/s. The variability in this subject’s data was typical of other subjects in the
study.

Due to the large variability between trials of individual subjects, it is not
appropriate to average just the best two or three trials and use that value for further
analysis. Since it is assumed that all subjects were running at the same constant speed, it
was decided that the best representation of each subject’s ground reaction force data was
the trial where the propulsion change in velocity had the least percentage difference from

the braking change in velocity. If two trials had the same percentage difference between

49

BAV and PAV, then the trial with the lower braking change in velocity was used.

Therefore, only one trial for each subject on the pretest and posttest was analyzed further.

Table 4.2. Ground Reaction Force Pretest Data for Subject Number 14

 

 

 

 

 

 

 

 

 

 

 

 

 

 

BT as lst Vert. 2nd Vert. BAV PAV % diff.a
Trial ST (s) BT (s) % of ST Peak (N) Peak (N) (m/s) (m/s)
7 0.259 0.123 47 782 1355 0.17 -0.27 59
8 0.275 0.138 50 776 1309 0.22 -0.23 5
9 0.271 0.141 52 782 1321 0.22 -0.23 5
11 0.262 0.131 50 759 1355 0.18 -0.27 50
12 0.250 0.137 55 880 1292 0.22 -0.20 -9
13 0.255 0.123 48 747 1378 0.17 -0.26 53
16 0.260 0.132 51 718 1321 0.20 -0.25 25
18 0.269 0.133 49 660 1373 0.18 -0.28 56
23 0.251 0.147 59 1112 1251 0.33 -0.12 -64
26 0.254 0.142 56 857 1303 0.26 -0.18 -31
29 0.261 0.143 55 724 1321 0.24 -0.19 -21
31 0.267 0.133 50 794 1297 0.20 -0.23 15
Mean 0.261 0.135 52 799 1323 0.22 -0.23 12
SD 0.008 0.008 0.03 1 15 37 0.05 0.05 0.39

 

Note. ST = Support time; BT = Braking time.
’% Diff. is the percentage difference between BAV and PAV;
% Diff = (lPAVl - BAV)/ BAV

Biomechanics results. All subjects’ pretest data were combined in order to
compare this study to data from other studies. Subjects were in the support phase an
average of 0.247 seconds, with the transition from braking to propulsion coming at 50.3%
of stance. The second vertical peak ground reaction force was 2.5 times body weight.
The mean braking change in velocity for all subjects was 0.24 m/s. These values are
comparable to results from other studies where subjects ran at similar speeds to those in
the current study (Keller et al., 1996; Munro et al., 1987; Nachbauer & Nigg, 1992).

Means and standard deviations of three biomechanical variables for both groups
on the pretest and posttest are listed in Table 4.3. As a whole, the participants

significantly decreased (p < .10) their braking change in velocity (BAV) from pretest to

50

posttest. Six of the seven subjects in PLYO decreased their braking change in velocity

from pretest to posttest while the remaining subject had no change. Overall, there was an

8% decrease in BAV in PLYO over the training period. Five of the nine subjects in RUN
decreased BAV, two increased BAV, and two had no change. As a group, there was no

change in BAV in RUN. There was a trend of support time (ST) decreasing (3.2%) over

the training period in PLYO while there was no change in support time in RUN. Five of
the seven subjects'in PLYO decreased time in support, while five of nine subjects in

RUN decreased time in support. There was little change in braking time (BT) in either

group.

Table 4.3. Biomechanics Variables Before (Pretest) and After (Posttest) Six Weeks of
Training

 

 

 

 

 

PLYO (n = 7) RUN (n =9)
Pretest Posttest Pretest Posttest
Mean Range Mean Range Mean Range Mean Range
Variable (SD) (SD) (SD) (SD)
ST (5) 0.249 0.228- 0.241 0.205- 0.245 0.201- 0.245 0.219-

(0.027) 0.295 (0.027) 0.289 (0.024) 0.280 (0.023) 0.270

BT(s) 0.122 0.102- 0.121 0.112- 0.125 0.114- 0.126 0.109-
(0.015) 0.144 (0.007) 0.133 (0.013) 0.141 (0.013) 0.146)

BAV (m/s) 0.25 0.23- 0.22 0.17- 0.23 0.20- 0.23 0.18-
(0.03) 0.29 (0.04) 0.26 (0.03) 0.29 (0.03) 0.28

Note. ST = Support time; BT = Braking time; BAV = Braking change in velocity.

Physiological Variables
Physiological data is summarized in Table 4.4. As a whole, the participants
displayed a significant improvement in running economy (p < .10) from pretest to

posttest. Running economy improved by 4.7% in PLYO and by 6.8% in RUN. Changes

51

in running economy among individuals in PLYO ranged from 0.73 to 2.44 ml/kg/min and
ranged from 0.90 to 4.73 ml/kg/min among individuals in RUN.

Lactate threshold velocities were obtained on both the pretest and posttest on six
of seven subjects in PLYO and seven of nine subjects in RUN. Some subjects started
running at a velocity above their lactate threshold or had highly variable blood lactate
levels at different speeds which made it difficult to determine lactate threshold. With this
in mind, lactated threshold velocity improved by 5.5 % in PLYO and by 10% in RUN.

Average VO was not changed during the training period in either group.

2m:u

However, there were individual changes. In PLYO individual changes in V0an ranged

from a decrease of 14% to an increase of 8.9%. Changes in V0, in RUN ranged from a

-1112.“

decrease of 4% to an increase of 24%.

Table 4.4. Physiological Variables Before (Pretest) and After (Posttest) Six Weeks of
Training

 

 

 

 

PLYO (n = 7) RUN (n = 9)
Pretest Posttest Pretest Posttest
Mean Mean Mean Mean
Variable (SD) Range (SD) Range (SD) Range (SD) Range

 

Run Econ. 40.36 29.72- 38.46 28.99- 40.12 13.3- 37.39 13.74-
(ml/kg/min) (5.3) 44.90 (4.9) 42.46 (12.40) 53.26 (11.23) 51.46

LT vel.“ 7.3 6.5- 7.7 7.0- 6.9 5.0- 7.6 6.0-
(mi/hr) (0.5) 8.0 (0.4) 8.0 (1.46) 9.0 (1.18) 9.0
V0 59.3 43.51- 59.1 43.87- 60.6 49.62- 62.0 53.23-

Zmax
(ml/kg/min) (8.5) 68.50 (8.1) 69.51 (8.4) 72.0 (6.5) 69.15
“In PLYO p = 6 on pretest and posttest; in RUN, p = 8 on pretest and p = 7 on posttest.

52

CHAPTER FIVE

Discussion

In this study eighteen high school cross-country runners were divided into a
plyometric group (PLYO) and a running group (RUN). All participants did six weeks of
regular cross-country training, while the plyometric group replaced some of their running
with plyometrics. It was expected that plyometric training would facilitate
neuromuscular response to better utilize elastic energy stored during the eccentric
contractions of each footstrike. These neural changes could potentially improve
biomechanical and physiological factors such as time in support, braking change in
velocity, and running economy. It was conjectured that the plyometric group would have
improved running performance.

Participants in PLYO did not significantly decrease their time in support or
braking time as hypothesized. The hypotheses that participants in PLYO would
significantly decrease their braking change in velocity and improve their running
economy was supported by the present study. However, these changes in PLYO did not
lead to a greater improvement in 3200-meter run time in PLYO than in RUN as
hypothesized. This researcher found a trend of a decrease in support time over the
training period, while no change in support time was found for the RUN group. In PLYO
support time decreased eight milliseconds (3.2%) from pretest to posttest, while there was
no overall change in support time in RUN. It is unclear if plyometrics led to significant

changes in lactate threshold velocity as there were difficulties in collecting lactate

53

threshold data in some of the participants so this variable was excluded from the
ANOVA.

The expected outcome that six weeks of plyometric training would lead to greater
biomechanical, physiological, and performance changes in PLYO than in RUN was not
supported by this study. Participants in both groups significantly improved their running

economy and 3200-meter time (without a change in V0 ), but there were no significant

differences between groups on those variables. Participants in PLYO decreased braking
change in velocity by 0.03 m/s (8%), while there was no change in RUN from pretest to
posttest. These results should be interpreted and applied with caution as this study just
met the minimum number of subjects per group that Schutz and Gessaroli (1987)
recommend for a design with five dependent variables.

The results of this study are comparable to other studies (Dudley & Djamil, 1985;
Hurley et al., 1984) that stated training for endurance and strength does not negatively
affect endurance performance. Also, it is typical that the participants displayed improved
running economy and running performance without changes in V0,“. Hickson et al.
(1988) found that combining strength training and running improved short-term

endurance without changing VO while Nicholson and Sleivert (1999) found that

Zrnax’

running and weight training improved ten-kilometer times and running economy with no

significant changes in V0 Likewise, Paavolainen et al. (1999) reported that

2mu'
endurance training combined with plyometrics and weight training significantly improved
running economy and five-kilometer times due to improved neuromuscular
characteristics.

A difference between this study and other strength training studies is that in the

present study both the plyometric group and the running-only group had similar

54

improvements in running economy and in running performance. In studies such as
Nicholson and Sleivert (1999) and Paavolainen et al. (1999), the runners who strength
trained displayed greater changes in their running economy and running performance than
the subjects who only trained by running. However, in those studies, strength training
involved only weight training (Nicholson and Sleivert) or weight training and plyometrics
(Paavolainen et al.) instead of using plyometrics as the sole training method as in the
present study. Also, these studies were done over a longer training period (21 weeks and
9 weeks, respectively), which may explain in part why the differences were not seen in
the present study as the subjects trained for just six weeks. However, Paavolainen et al.
also reported a significant improvement in running economy in the strength-training
group after three weeks and after six weeks of running and strength training. The group
that primarily did run training did not have any significant changes in running economy
throughout the nine-week study.

Another possible reason for differences in the results of the current study and
other strength training studies on runners is the general characteristics of the subjects.
The participants in the current study were relatively inexperienced high school runners.
Most other running and strength training studies have used college-aged athletes or older
athletes who are more experienced and have greater running abilities.

There is some support for the hypotheses that support time and braking change in
velocity would significantly decrease in PLYO. Plyometrics involves an eccentric
contraction quickly followed by a concentric phase. Plyometric training requires muscles
to respond quickly to small changes in muscle length which occur with each running step.
During the support phase when running at a constant speed, runners decrease their

forward velocity by braking and then increase their velocity during propulsion

55

(acceleration) to the original speed. Ideally runners want to minimize the amount of
braking done during support.

There is some evidence that one training adaptation of plyometrics is to cause
runners to reduce their time in support and to reduce the amount of braking and
propulsion done during the support phase. Runners in PLYO significantly decreased
their braking change in velocity and showed a trend of decreased time in support, while
there were no such changes in RUN. After training, subjects in PLYO were braking less,
which could have resulted in some type of energy savings. However, in the current study
there was no evidence of an energy savings. Running economy improved similarly in
both groups despite differences in braking change in velocity, suggesting that decreased
braking change in velocity did not result in any significant change in energy need. In a
study by Paavolainen et al. (1999), though, the experimental group that did nine weeks of
explosive strength training along with run training decreased support time and running
economy significantly, while there were no significant changes in the control group that
mainly did run training.

Cautions in Interpreting Results

The large number of dependent variables and the relatively small number of
subjects should be considered when interpreting the results of this study. In order to use
MANOVA, Schutz and Gessaroli (1987) recommended a minimum of seven subjects per
group when analyzing five dependent variables in two groups tested over two time
periods. As a rule of thumb, though, Schutz and Gessaroli recommended a minimum of
ten subjects per group (5 dependent variables x 2 groups) for the present study design,
which had groups of seven and nine subjects. Therefore, significance results should be

viewed with caution.

56

There were also difficulties in analyzing the biomechanics data. It is well known
that there is large variability between trials within subjects in ground reaction force data.
An example of this variability is presented in Chapter Four. Because of this variability,
researchers recommend doing analysis on eight (Bates, Ostemi g, Sawhill, & James,
1983) to twenty-five (Devita & Bates, 1988) trials in order to obtain accurate ground
reaction force data. Lees and Field (1985) found that there is also a lot of day-to-day
variability within subjects. They recommended pooling data from two or more days. A
shortcoming of the current study is that only one trial was used to represent each subject’s
running pattern.

One reason for the large variability in the ground reaction force data within
subjects in this study is that runners were not challenged to run close to their maximum
speed. When individuals run at or close to their maximum speed, they have very few
movement patterns which would enable them to reach their top speed. However, in the
present study, subjects were running at a slow pace, so there was the potential for greater
variability in their ground reaction force parameters. Lees and Bouracier (1994) discuss
how runners may have numerous “movement solutions” to the assigned task of running at
a particular submaximal speed through a testing area. Subjects are free to choose from a
variety of solutions to this “movement problem” or task and receive positive feedback on
each trial when they fulfilled the requirements of the task. Lees and Bouracier also found
that the amount of variability in stride patterns is related to the experience of the subjects.
Experienced runners had standard deviations in braking and propulsion impulses that
were significantly less than those standard deviations for inexperience runners across
twenty trials. As a result, experienced runners were more consistent with their stride

pattern and tended to have smaller braking and propulsion impulses.

57

Another concern in interpreting the results of this study was the variability in time
spent training. It was assumed that the participants would do most of their training
during cross-country practice so that the amount of training time would be similar for all
participants. The intention of this study was that the only difference in training groups
would be that the participants in PLYO would spend part of their training time doing
plyometrics, while the participants in RUN would continue running during this time.
However, as reported in Chapter Four, the number of miles run each week varied greatly
between subjects. The participants appeared to have a wide range of goals and
motivations for running. Some subjects reported running on weekends, and on some days
they ran a second time outside of practice. One subject in RUN reported biking 40-50
miles per week while also running 38 miles per week. Other subjects missed practice and
did not run at all on certain days. Injuries, conflicts with jobs, family vacations, and band
camp were several reasons reported for missing cross-country practices. Because of these
conflicts it was difficult for coaches to completely control training time. Variability in
training time should be kept in mind when interpreting the results of this study.
Recommendations for Further Research

There is a need for further research on the effects of plyometric training on high
school distance runners. Since subjects in both groups of the present study had both
positive and negative responses to training, researchers should take in to consideration the
experience level and running ability of their subjects when designing a study. Individuals
in the present study had varied responses to training which may have been influenced by
their previous running experience and their running ability. Further studies need to be

conducted to investigate how strength training adaptations are influenced by these factors.

58

For example, subjects could be grouped based on previous years of running experience to
determine if this factor influences the response to plyometrics.

It also would be beneficial to require participants to engage in run-only training
for three to four months prior to the beginning of the strength training phase so
participants would be more likely to achieve a steady state level of fitness. Furthermore,
there is a need to determine how many weeks of plyometrics are needed to obtain
significant changes, if any, among inexperienced, high school cross-country runners.

When collecting ground reaction force data on runners, researchers need to be
aware of the large variability in ground reaction force data and analyze up to 25
successful trials over at least two days. It would have been beneficial in the present study
if more trials were collected over more than one day. More trials may help ensure that
subjects obtain a “movement pattern fixation” as described by Lees and Bouracier (1994).
Also, biomechanists should be aware of the variability in ground reaction force data
between inexperienced and experienced runners. Groups should be equally represented
by all levels of experience.

Researchers should set up testing areas so that there is immediate feedback on
whether or not subjects are running at a constant speed across the force plate. In the
present study there were numerous trials that appeared successful at the time that later
had to be eliminated from further analysis because subjects were accelerating or
decelerating. Pacer lights to guide runners and using two sets of timing systems would
help to ensure runners were running across the testing area at a constant speed.
Implications and Conclusions

Keeping in mind the above difficulties with this study, there are some

implications that can be made with regards to this study. Six weeks of plyometric training

59

may lead to biomechanical changes in some high school runners. Specifically, replacing
some running with plyometrics may decrease braking change in velocity and time in
support. In the current study these biomechanical changes did not lead to any
significantly greater improvements in running economy or in running performance.
However, other studies lasting longer than six weeks show that running, combined with
strength training such as plyometrics, can lead to greater improvements in running
economy, lactate threshold, and run performance than can training with run-only training.

The present study indicates that among relatively inexperienced high school cross-
country runners, six weeks is not a long enough training period for plyometrics to realize
a significant advantage over run-only training. Given the confines of a busy racing
schedule and the limited practice time in a typical high school cross-country season, it is
unrealistic for coaches to spend much more than six weeks on plyometric training. An
implication for high school cross-country coaches then is that they should focus their
training on running. However, this researcher found that replacing some running with
plyometrics will not have a negative effect on running performance. Plyometric training
could be used as a mental break from running for some young runners weary from
logging high mileage. Plyometrics may be more beneficial for improving performance
among older, more experienced runners, although this has not been evaluated. Further
research needs to conducted to determine the role that age and running experience have
on the effects of plyometrics.

In conclusion there is not one type of training that best improves running
performance. A variety of factors influence running performance. These factors include

VO lactate threshold velocity, running economy, and muscle power. As a result,

21111111 ’

60

cross-country coaches should use a variety of training methods when training the runners

on their team. Suggested training methods are summarized in Table 5.1.

Table 5.1. Types of Training for Cross-Country Runners

 

 

Type of Training Reasoning Sample Workout
Easy Distance Improves cell adaptation and Seven-mile easy run.
Run ability to spare glycogen and

rely on fat as fuel.

 

Tempo Run Increases lactate threshold.

Run 20 minutes at a pace
greater than lactate threshold
velocity.

 

Repetitions Improves running economy.

8 x 200 meters with full (2-3
min) rest; pace greater than 1
mile race pace.

 

Intervals Increases VO

2m.“ '

6 x 800 meters with rest equal
to or less than time of interval;
run at max heart rate or at a
pace equal to current 5-km race
pace.

 

Hill workout Improve muscle power

8 x 150 meters up incline with
full (2-3 minute) rest.

 

 

Strength training May improve muscle power;
may increase RE“, LT”; may
decrease BAVC, ST'; use to
increase motivation.

Three sets of five plyometric
exercises (see Appendix B).

 

“RE = Running economy. l”LT = Lactate threshold. cBAV= Braking change in velocity.

“ST = Support time.

By using a variety of training methods, runners can improve their endurance,

speed, and strength. The variety of workouts may also help young runners stay motivated

to come to practice. The end result could be a more enjoyable cross-country running

experience and improved running performance.

61

 

APPENDIX A

Running History Form

62

Subject Number:

Running History and Running Performance Test

Name: Date of pretest:

 

Date of posttest:

 

Location: Weather (Pretest):

 

Weather (Posttest):

 

RUNNING HISTORY

Please answer as accurately as possible.
1. Number of years running

2. Did you run track this year? If yes, how many weeks of rest did you have after track
season?

3. In the past six weeks,
a. How many weeks have you run?
b. Estimated average number of days run per week.

c. Estimated average number of miles run per week.

 

4. To the best of your knowledge, record your best times at the following distances.
800 meters 2 mile (or 3200 meters)
. 1 mile (or 1600 meters) 5 K

RUNNING PERFORMANCE TEST-3200 METERS

131281 ma Garage
1600 m time—
2800 m time___ __
last lap split ( ) ( )
3200 In time___

63

APPENDIX B

Plyometric Training Schedule

64

SIX WEEK PLYOMETRIC TRAINING SCHEDULE
FOR CROSS-COUNTRY RUNNERS

GeneLal Guidelines

1. Plyometric training should be done on nonconsecutive days. (There should be at least
one day of rest or nonplyometric training between each plyometric training day.)

2. A complete warmup and stretching routine should be completed before each
plyometric session.

3. Plyometrics should be done on a soft surface such as dirt or grass.

4. Exercises should progress from simple, low intensity, low impact exercises to more
complex, higher intensity exercises.

5. In order for plyometrics to be effective, proper technique must be used:

0 Athletes should have short, quick landings with minimum knee flexion and
contact time.

o A locked ankle should be maintained upon landing and athletes should land with

two-thirds to a full foot ground contact. More weight should be on the front of the
foot.

0 Short, quick landings should be immediately followed by a rapid, powerful take-
off.

6. A full recovery (30 seconds to 2 minutes) should be used between sets.

7. When first learning an exercise, single-response drills should be used. This is where
there is a pause after each landing to check technique. Once the exercise has been
learned, multiple-response drills should be used where there are numerous successive
jumps with no pause between landing and taking off again.

8. The numbers preceding the exercises indicate the number of sets and repetitions. For
example, 3 x 6 squat jump means three sets of six repetitions of squat jumps. For

exercises such as skipping, a distance is given instead of number of repetitions. For

single leg exercises the required number of repetitions and sets should be done on

eachleg.

65

9. Try to follow the number of sets and repetitions that are given. However, the exact
amount of each exercise may have to be adjusted to meet the abilities of the athletes.
Emphasize quality over quantity. If the athletes are unable to perform the assigned

number of repetitions or sets of an exercise with the appropriate technique then the
sets or repetitions may have to be reduced.

10. The notation in parentheses indicates where to find a complete explanation of an

exercise in the “Plyometric Exercises” handout in Appendix C. For example, J-2
refers to jump number two, “Squat jump.”

66

 

 

 

 

 

 

 

 

WEEK DAY ONE DAY TWO DAY THREE
3 x 30 yds Prancing (B-1) 3 x 30 yds GaIIOping (B-2) off
3x8Pogo(J-1) 3x8Pogo

1 3 x 30 yds Skip for power 3 x 4 Hurdle hops
(B-3) 3 x 30 yds Skip for power
3 x 20 sec Richochet (H-3) 3 x 6 Box jumps (J-3)
3 x 4 Hurdle hops (H-1)
3 x 40 yds Prancing 3 x 40 yds Galloping off
3 x 6 Squat jump (J -2) 3 x 40 yds Skip for speed
2 3 x 30 yds Double-leg speed (B-3)
h0P (HQ) 3 x 6 Double-leg butt kick
3 x 40 yds Skip for power (1-4)
3 x 8 Box jumps 3 x 30 sec Richochets
4 x 6 Squat jumps
3 x 40 yds Skip for speed 4 x 50 yds Skip for power off
3 x 8 Double-leg butt kick 3 x 50 yds Ankle flip (B-4)
3 2 x 6 Single-leg butt kick 2 x 30 sec Richochets
(H-5) 3 x 6 Split jump (J-5)
3 x 8 Stadium hops (H-4) 3 x 6 Single-leg butt kick
2 x 6 Single-leg stair bound
(B-5)
3 x 50 yds Ankle flip 3 x 50 yds Galloping 4 x 50 yds Ankle flip
3 x 8 Split jump 3 x 50 yds Skip for speed 3 x 8 Split jump
4 x 30 yds Double leg speed 4 x 20 sec Ricochets 4 x 30 yds Double leg
4 _ hop . 3 x 10 Stadium hops speed hop
2 X 8 Single-leg 513" b09119 2 x 5 Single-leg hop for 3 x 8 Single-leg stair
3 x 20 steps Alternate leg height (each leg) bound
stair bound (3' (H-6) 3 x 20 steps Altemate-
6) leg stair bound
4 x 50 yds Skip for speed 3 x 50 yds Galloping Repeat day one of this
3 x 5 Single-leg stride jump 4 x 4 Hurdle hops (Multiple week.
(J-7) response) (H-8)
5 4 x 12 Stadium hops 3 x 8 Box jump (Multiple
3 x 6 Scissors jump (J-6) response) (J -10)
3 x 6 Single-leg hop for 1 x 4 Depth jump 09)
height (each leg) 3 x 6 Alternate leg bound
03-8)
4 x 50 yds Ankle flip 4 x 50 yds Skip for speed 3 x 50 yds Galloping
3 x 8 Scissors jump 3 x 8 Box jump (Multiple 3 x 10 Scissors jump
3 x 6 Single-leg stride jump response) 3 x 5 Stride jump
6 3 x 20 steps Altemate-leg 1 x 6 Depth jump crossover (J -8)
stair bound 5 x 4 Hurdle hops 3 x 5 Single-leg speed
2 x 5 Single-leg speed hop 4 x 30 sec Ricochets hOp
(H-7) 3 x 8 Alternate leg bound 4 x 50 yds Ankle flip

 

 

 

 

67

 

APPENDIX C

Descriptions of Plyometric Exercises

68

PLYOMETRIC EXERCISES
JUMPS (J)

1. POGO
Start: Stand with knees slightly bent, chest out, and shoulders back.

Action: Jump straight up, projecting hips up, with just a small knee flexion while in the
air. Use ankles to lock feet into toes-up position and maintain this position throughout
jumps.

2. SQUAT JUMP

Start: Stand upright with feet about shoulder-width apart. Interlock fingers and place
palms against the back of the head.

Action: Flex downward to a half-squat position; then immediately explode upward as
high as possible, extending the hips, knees, and ankles to maximum length as quickly as
you can. Upon landing, quickly jump up again.

3. BOX JUMP (Single response)
Start: Stand facing an 18-24 inch box with feet shoulder-width apart.

Action: Flex downward to a half-squat position and immediately jump up and land softly
with both feet on the box; step down and repeat.

4. DOUBLE-LEG BUTT KICK
Start: Stand upright with knees slightly bent, chest out, and shoulders back.

Action: Flex downward quickly with a slight knee bend and then immediately jump up
and pull the heels upward and slightly backward into the buttocks while tucking the toes
up. Repeat the jump immediately.

5. SPLIT JUMP

Start: Kneel on the ground with one leg extended forward with the knee over the middle
of the foot and the other leg back with the knee bent and underneath the shoulders and
hips.

Action: Jump as high as possible. Land in the same position, bending the knees to absorb

the shock. Immediately repeat the jump. Be sure to keep the shoulders back and in line
with the hips. Switch legs after the required number of repetitions.

69

Jumps (Continued)

6. SCISSORS JUMP
Start: Assume the same position as the start of the split jump.

Action: Jump up as in the split jump, but switch leg positions when in the air, flexing the
back knee as it is brought forward. Upon landing, immediately repeat jump, again
reversing the position of the legs.

7. SINGLE-LEG STRIDE JUMP

Start: Stand to the side and at one end of a bench. Place inside foot on top of the bench,
and hold arms downward at sides.

Action: Bring arms upward and initially push with both legs; then push off hard with
foot on bench to jump up as high as possible, bringing outside knee up. Upon landing
use the inside foot for support and power; the outside foot should have a quick landing
before beginning the next jump. Continue to the end of the bench and then turn around
and come back on other leg.

8. STRIDE JUMP CROSSOVER
Start: Start as in single-leg stride jump with one foot on a bench.

Action: Bring arms up and push off hard as in the single-leg stride jump. Jump as high
as possible and bring the leg that was on the bench to the opposite side of the bench. Then
the outside leg will land on the bench and the inside leg will land on the ground. Now the
body and legs should be in the opposite position as the starting position. As soon as the
original driving leg contacts the ground repeat the jump upwards. Perform the jumps as
quickly as possible.

9. DEPTH JUMP

Start: Stand on the edge of an elevated surface (box or bench) that is 12 to 36 inches
high. Knees should be slightly bent, and arms at the sides.

Action: Drop (not jump) from the box to the ground. Upon landing flex the knees

slightly and quickly jump up. Try to anticipate the landing and jump up as quickly as
possible, minimizing time on the ground.

70

10. BOX JUMP (MULTIPLE RESPONSE)

Start: Stand facing a 12 to 24 inch box approximately an arm’s length away. Arms
should be at side.

Action: Use the arms to assist a powerful jump upwards and forward onto the box.
Immediately drop or jump down to the original starting position and repeat jump.

BOUNDS AND SKIPS (B)

1. PRANCING
Start: Stand with a slight knee bend and hips tilted forward.

Action: Athletes will be projecting the hips forward with a two-foot takeoff and a two-
foot landing. Push the hips outward and upward upon takeoff with one leg landing in
front of the other. Upon landing repeat the takeoff with the opposite leg landing forward.
Move arms as in running. Both feet must land simultaneously so keep ankles locked in a
toes-up position.

2. GALLOPIN G

Start: Stand with one leg in front of the other.

Action: Push off with the back leg and foot, keeping the ankle locked upon takeoff and
landing. Keep the same leg behind the hips and project the hips forward, with the other
leg staying forward. After required distance, switch position of the legs and repeat.
Emphasize forceful, quick extensions of the back knee and ankle, with light cyclic
striding actions of the lead leg.

3. SKIPPING-POWER AND SPEED

Start: Stand with one leg slightly forward.

Action: In power skipping, skip for maximum height, emphasizing a powerful pushoff,
flicking the ankles.

In speed skipping, stay close to the ground and reduce air time. Emphasize frequency not
distance.

71

Bounds and Skips (Continued)

4. ANKLE FLIP
Start: Stand with right foot forward.

Action: This is an exaggerated running stride. Push off hard with the right foot and bring
the left foot forward. As the back leg comes through extend the front leg for duration of
the push off. Hold this extended stride for a brief time and then land on the left foot.
Repeat pushoff with the left foot. Make each stride long and keep ankles locked.

5. SINGLE-LEG STAIR BOUND
Start: Balance on right leg on the second step of stairs.

Action: Drop down to the step below landing on the left leg. Immediately push off with
the left foot, driving the right leg onto a step or two above the original starting step.
Continue this sequence (right leg, drop to left, bound up onto right) for predetermined set
of repetitions. Then repeat, starting with left leg up.

6. ALTERNATE-LEG STAIR BOUND

Start: Begin with one leg back.

Action: Run (bound) up the steps with maximum extension of the support leg, and
maximum knee drive of the swing leg. Emphasize quick, explosive takeoffs, spending as
little time as possible on each step.

7. ALTERNATE-LEG BOUND

Start: Begin with left foot forward and arms at the side.

Action: This is similar to the ankle flip, only strive for more height and distance. Push
off with the back leg, driving the knee forward and upward to gain as much height and
distance as possible. Land on the right leg in the forward position and repeat sequence

(pushing off with the other leg). Keep the ankles locked upon landing and minimize
ground contact time. Use arms as in running.

72

HOPS (H)
1. HURDLE HOPS (Single response)

Start: Stand with knees slightly bent and arms at the side in front of a series of three to
five barriers (e.g. 12 to 36 in hurdles) spaced approximately three feet apart.

Action: Use a quick countermovement and jump forward over the first barrier. Tuck the
toes, knees, and heels upward. Keep the body vertical and straight. Land with full-foot
contact, bending at the knees slightly. Pause to reset the correct starting position and then
jump over the next hurdles. Once landing and takeoff technique is correct, perform
jumps without pause.

2. DOUBLE-LEG SPEED HOP
Start: Stand with knees bent and arms at the side.
Action: Use a quick countermovement and jump up and forward, tucking the knees while

in the air. Upon landing, takeoff quickly. Strive for height and distance while
maintaining a high repetition rate.

3. RICOCHETS

Start: Stand with arms at side.

Action: Hop forward and backward, minimizing horizontal and vertical distance.
Emphasize speed, with quick takeoffs and landings. For variety do on a hill or on stairs.

4. STADIUM HOPS

Start: Stand in a semi-squat position on front portion of a step. (Alternative: do on a
hill). Hold arms slightly behind body.

Action: Follow a quick flexion of knees with an explosive jump up two or three steps.
Continue hopping up the required number of repetitions. Make landing quick and light.

5. SINGLE-LEG BUTT KICK

Start: Stand with knees slightly bent, chest out, and shoulders back. Lift one knee by
bringing heel up towards buttocks.

Action: Use a quick countermovement and jump off of one leg as high as possible. Tuck
the toes and heels of the takeoff leg upward toward the buttocks. Maintain an upright
posture during the entire movement. Repeat continuing to land and takeoff on the same
leg. After designated number of repetitions switch legs.

73

Hops (Continued)

6. SINGLE-LEG HOP FOR HEIGHT

Start: Stand with knees slightly bent and arms at the side. Balance on the right leg while
keeping the left leg flexed with the toes up, knee up in front of the body, and the heel up
in front of the hip.

Action: Do the hops similar to the hurdle hops, flexing the knees while in the air, but
landing and taking off on one foot. These may be done over small cones.

7. SINGLE-LEG SPEED HOP
Start: Begin as in single-leg hop for height.

Action: Hop for speed and distance, taking off and landing on one leg. Minimize contact
time with ground by keeping ankles locked and having a quick landing and takeoff.

8. HURDLE HOPS (MULTIPLE RESPONSE)

Do these similarly to single response hurdle hops except emphasize a brief landing and
takeoff period. To increase difficulty increase height of hurdles up to 36 inches.

 

For additional information on plyometric training see:

Bompa, TD. (1996). Power training for sport: Plyometrics for maximum power
development. Oakville, Ontario: Mosaic Press.

Chu, DA. (1992). Jumping into plyometrics. Champaign, IL: Leisure Press.
Radcliffe, J .C., & Farentinos, RC. (1999). Hi gh-Powered plyometrics. Champaign,

IL: Human Kinetics.

Pictures of the plyometric exercises used in the current study can be found in
these books. Names of most exercises were taken from Radcliffe and Farentinos’ book.

74

APPENDIX D

Individual Characteristics and Training Data

75

General Characteristics of Participants

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Run Ave. NO.of

Age Ht. Pre Wt.‘Post Wt. Exp. Prestudy mi/wk Range plyo j

' PLYO Gender (yrs) (cm) (kg) (kg) (yrs)"lrun(wks)”lrunningC (mi/wk)d days"
4 Male 15 170.7 64.2 i 64.5 2 5 l 34 2045 12
6 Male 17 180.91 60.9 61.8 2 5 30 11-51 8
7 Male 14 186.61 69.2 69.0 2 6 30 1544 10
8 Female 18 162.5‘ 60.0 59.5 5 6 25 25-25 12
10 Male 16 178.0 83.7 83.1 4 0 12 0-19 19
12 Male 16 168.0; 51.5 54.7 2 6 18 5-25 15
18 Male 15 177.6T 63.2 62.0 2 6 29 16-54 15
Mean 15.9 174.9 64.7 64.9 2.7 4.9 25.4 - 13
so 1.35 8.25 9.95 9.12 1.25 2.19 7.79 - 3.65

1 RUN 1 I 1 l
2 Male 1 18 “78.7; 68.2 69.5 5 7 26 846 0
3 Male 161175.11 71.6 70.4 I 4 5 41 33-51 0 .
9 Female 16 ‘ 1661- 58.5 57 i 0 3 19.5 11.5- 0
l , 29.5

11 ,Male 16 171 i 57.2 57.9 2 s 2 i 21 18-24 0

13 ‘Male 17 167j 57.6 57.1 3 i 5 17 11-26 0 _

14 Male 16 1781 61 60.5 3 i 6 27 1944 0 i
15 Female 16 152.1! 47.7 47 2 1 2.5 9 023.5 0
16 ,Male 17 184.1 69.8 68.5 4 6 47 20-70 0
17 Male 16 177.2 64.7 62.6 2 4 38 20-80 0
Mean 16.4 172.1 61.8 61.2 , 2.8 4.5 27.3 - 0

SD 0.73 9.50 7.57 7.55 11.4 1.73 12.42 - - j

 

aRunning experience; number of years training for running prior to study;

bNumber of weeks running in six weeks prior to beginning of study;

cAverage number of miles run per week during study;
dRange of miles run in one week during study;
‘Number of plyometric training sessions done during study.

76

APPENDIX E

Individual Data for Running Performance

77

Running Performance Data

 

 

 

 

 

 

 

Sub. No. 3200 m time (minzs)
PLYO Pretest Posttest Change
4 12:29 12:03 0:26
6 11:27 11:22 0:05
7 13:07 12:47 0:20
8 16:05 14:53 1:12
10 13:20 12:29 0:51
12 12:50 12:56 + 0:06
18 13:39 - -
Mean 13:16 12:45 0:31
SD 0.06 0.05
RUN
2 12:08 11:15 0:53
3 11:31 11:07 0:24
9 20:24 15:15 5:09
11 12:21 12:04 0:17
13 13:24 - -
14 13:01 - -
15 15:59 16:12 +0213
16 11:34 11:03 0:31
17 14:24 12:04 2:20
Mean 13:51 12:42 1:08
SD 0.12 0.09

 

Note. Dashes indicate that data was not obtained

on that trial.

78

 

APPENDIX F

Individual Data for Biomechanics Variables (Best Trial)

 

79

Individual Data for Biomechanics Variables
Best Trial (Based on braking and propulsion difference)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sub. No. Braking Change in
Time in Support (5) BrakingLime (5) Velocity (m/s)
PLYO Pretest Post Change Pretest Post Change Pretest Post Change

4 0.232 0.224 -0.008 0.102 0.1 15 0.013 0.23 0.21 -0.02
6 0.236 0.246 0.010 0.120 0.128 0.008 0.26 0.26 0’
7 0.295 0.289 -0.006 0.144 0.1 19 -0.025 0.28 0.26 -0.02
8 0.278 0.261 —0.0 1 7 0.141 0.133 -0.008 0.29 0.25 -0.04
10 0.228 0.230 0.002 0.1 16 0.1 19 0.003 0.23 0.20 -0.03
12 0.241 0.232 -0.009 0.1 17 0.121 0.004 0.23 0.21 -0.02
18 0.231 0.205 -0.026 0.1 15 0.1 12 -0.003 0.24 0.17 -0.07

Mean 0.249 0.241 -0.008 0.122 0.121 -0.001 0.25 0.22 -0.020

SD 0.027 0.027 0.015 0.007 0.025 0.035

RUN
2 0.244 0.263 0.019 0.120 0.129 0.009 0.29 0.24 -0.05
3 0.257 0.268 0.011 0.127 0.139 0.012 0.20 0.24 0.04
9 0.238 0.219 -0.019 0.127 0.115 -0.012 0.20 0.18 -0.02
I 1 0.231 0.230 -0.001 0.120 0.1 18 -0.002 0.25 0.23 -0.02
13 0.230 0.218 -0.012 0.114 0.109 -0.005 0.23 0.23 0:
14 0.271 0.261 -0.010 0.141 0.136 -0.005 0.22 0.20 -0.02
15 0.201 0.219 0.018 0.104 0.112 0.008 0.22 0.22 0
16 0.251 0.270 0.019 0.130 0.146 0.016 0.23 0.22 -0.01
17 0.280 0.258 -0.022 0.145 0.130 -0.015 0.24 0.28 0.04

Mean 0.245 0.245 0.000 0.125 0.126 -0.001 0.23 0.23 0.00

SD 0.024 0.023 0.013 0.013 0.028 0.028

 

 

 

 

 

 

 

 

 

 

 

 

 

80

APPENDIX G

Individual Data for Physiological Variables

81

Individual Data for Physiological Variables

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sub. No. Run Econ. (ml/kg/min) LT velocity (mi/hr) I VOgmx(ml/kg/min) I
PLYO Pretest Post Change Pretest Post Change Pretest Post Change ‘
4 42.5 40.7 —1.84 I 8 8 0 63.8 69.5 5.7
6 44.9 42.5 -244 7.5 I 8 0.5 66.4 65.1 -1.3
7 44.0 41.6 -2.36 6.5 7.5 1 68.5 58.7 -9.8
8 29.7 29.0 -0.73 - - - 43.5 43.9 0.4
10 37.2 34.9 -2.34 7.5 7 -0.5 54.5 56.5 2.1
12 41.1 39.0 -2.09 7.5 7.5 0 59.5 61.7 2.2
18 43.0 41.5 -1.49 7 8 1 59.1 58.1 -1.0
Mean 40.4 38.5 -1.90 7.3 7 .7 0.3 59.3 59.1 -0.3
SD 5.3 4.9 I 0.5 0.4 i 8.5 8.1
'RUN
2 37.1 36.2 -0.9 8 - 56.7 61.8 5.1
3 44.1 39.8 -4.3 8.5 8 -0.5 65.3 65.6 0.3
9 13.3 13.7 0.4 5 6.5 1.5 . 49.6 53.2 3.6
11 44.8 41.9 -2.9 6.5 8 1.5 62.7 62.3 -0.4
13 41.6 38.0 -3.6 6 7 1 53.3 66.3 13.0
14 46.3 41.9 -4.4 . 7.5 9 1.5 65.9 60.6 -5.3
15 29.1 26.7 -2.4 I 6 6 0 50.3 50.3 0.0
16 53.3 51.5 -1.8 I 9 9 0 F 72.0 69.2 —2.8
17 51.5 46.8 -4.7 - - - 69.9 68.4 -l.5
Mean 40.1 37.4 -2 . 7 6.9 7 .6 0.7 60.6 62.0 1.3
SD 12.40 11.23 1.46 1.18 I 8.4 6.5

 

Note. Dashes indicate data was not Obtained for that trial.

 

82

 

 

APPENDIX H

Consent Form

83

Informed Consent Form

Biomechanical and Physiological Effects of Plyometric Training
on High School Cross-Country Runners

There are many different types of training that cross-country coaches use with their athletes. For
example, a mixture of long slow distance runs, intervals on a track, and hill running are
important components of most high school cross-country practices. A component that is often
not included is strength training as the effects of strength training on young distance runners’
performance is unclear. This study will compare the effects of run only training with a Specific
kind of strength training, plyometrics, on jumping ability, distance running performance, and
several physiological and biomechanical factors. It is not known which approach is best.

If you agree to participate in this study, you will be randomly assigned to one of two groups: a
plyometrics group or a run only group. If you are assigned to the run only group, you will
participate in regular cross-country practice with your high school team. If you are in the
plyometrics group, you will replace some of your regular cross-country practices with plyometric
training two to three times a week for six weeks. Plyometrics involves exercises such as jumps,
skips, and hops.

You will be asked to participate in a series of tests before and after the six weeks of training.
Session one of testing will consist of a 5-hop test, a vertical jump test, and a five kilometer run
on a local cross-country course. Session two will consist of a cardiovascular fitness test and a
biomechanical evaluation. These tests will take approximately an hour for each participant to
complete and will be done at the Human Energy Research Laboratory and the Biomechanics
Research Station at Michigan State University. Cardiovascular fitness, a good predictor of
endurance performance, will be measured by a best effort on a treadmill. This will include
several small fingerpricks to obtain blood lactate levels. The biomechanics evaluation will
consist of running approximately 40 yards at a constant speed while being videotaped. Stride
length, stride frequency, and contact time with the ground are some of the factors that will be
studied.

There are minor risks involved in the testing. The risks are no greater than completing a physical
fitness test. You may experience slight discomfort during the measure of blood lactate. You may
become faint or tired during the fitness test on the treadmill and during the five kilometer run.
However, these tests will be like running during practice or in a race. You could strain or pull
muscles, sprain ankles or develop stress fractures from the plyometric training. However,
athletes will be properly warmed up and instructed on appropriate techniques for doing these
exercises to help prevent injuries. Plyometric training has been used in high school sports and in
physical education classes for many years.

Participation is voluntary and you may choose to not participate at all, refuse to participate in
certain tests, or discontinue participation at any time without penalty. Every effort will be made
to protect you from having harmful problems during the testing. Pregnant women should not
participate in the study. If you are injured as a result of participation in this research project,
Michigan State University will provide emergency medical care if necessary. If the injury is not
caused by the negligence of MSU, you are personally responsible for the expense of this
emergency care and any other medical expenses incurred as a result of this injury.

To insure your confidentiality, your identity will only be known by the principal and secondary

investigator and a limited number of research staff who assist in the treadmill test and
biomechanics evaluation. You will be assigned a number and referred to by your subject number

84

when analyzing and reporting data. In general, data analyses will consist of comparing groups
and not individuals. Pictures and a videotape of selected subjects may by shown for educational
purposes without identifying the names of the athletes. Coaches will not be given data about
their runners. You will be given your individual results which you may share with your coach if
you wish. Group averages will also be provided to you so you can compare your scores to the
group. Confidentiality will be protected to the maximum extent permissible by law.

The benefits of participating in this study include receiving information about your
cardiovascular fitness, stride length and stride frequency, five kilometer running performance,
and jumping ability before and after six weeks of cross-country practices. All participants will
be mailed a summary of the results of this study upon completion.

If you or your parents have any questions about the study you may contact any of the following individuals:

Mark Lathrop Dr. Eugene Brown

Master’s of Science Student Institute for the Study of Youth Sports
Michigan State University Michigan State University
Department of Kinesiology Department of Kinesiology

East Lansing, MI 48824 East Lansing, MI 48824

(517) 663-1920 (Home) (517) 353-6491
mlathrop@lsd.kl2.mi.us ewbrown@pilot.msu.edu

David E. Wright, Ph.D., Chair

University Committee on Research Involving Human Subjects
246 Administration Building

Michigan State University

(517)355-2180

UCRIHS@pilot.msu.edu

I have been provide information about this study and have had the opportunity to ask questions
about this study. I agree to participate in this study by signing my name on the line below.

 

Parent/Guardian Date

 

Subject Date
Note: This form must be signed by BOTH the athlete and the parent/guardian to give consent for

the athlete to participate in the study. Please remember to bring this form on the first day of
testing.

85

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