Relationship between body composition and vertical jump performance in young Spanish soccer players

Full text

Pérez-López A, Sinovas MC, Álvarez-Valverde I, and Valades D. Relationship between body
composition and vertical jump performance in young Spanish soccer players.
J Sport Human Perf 2015; 3(3):1-12.
DOI: 10.12922/jshp.0063.2015
1
RELATIONSHIP BETWEEN BODY COMPOSITION
AND VERTICAL JUMP PERFORMANCE IN YOUNG
SPANISH SOCCER PLAYERS
Pérez-López A, Sinovas MC, Álvarez-Valverde I, and Valades D
Faculty of Medicine and Health Sciences, University of Alcalá, Madrid, Spain
Keywords: jump ability, body size, children and adolescents
INTRODUCTION
The development of motor skills in
pre-adolescence and adolescence is affected
by a wide variety of factors, one of which is
training (26). Jump ability is a motor skill that
depends on muscle contractile capacity,
stretch-shortening cycle (SCC), and high
power production (6, 15).
In childhood and adolescence, lower
levels of vertical jump performance have been
found to be a predictor of inactivity (14).
Thus, jump ability (both vertical and long
jumps) is a common test in schools (7), but
jump tests have also been used in sport
performance. In soccer, the vertical jump has
been used to monitor performance (30), to
ORIGINAL RESEARCH OPEN ACCESS
ABSTRACT
The aim of this study was to examine the relative contribution of body composition to vertical jump
performance in young Spanish soccer players. Seven hundred and twenty-three soccer players aged
7 to 19 years (156 ± 17 cm; 47.8 ± 15.1 kg) who had prior soccer experience (≥ 3 yrs) and had
trained for ~2 h·day-1, 4 days·week-1 were selected. Anthropometric measurements were taken and
three vertical jumps were performed: squat jump (SJ); counter-movement jump (CMJ); counter-
movement jump with arm swing (CMJa). Multiple regression equations revealed that age (SJ, =
0.635; CMJ, = 0.687, CMJa, = 0.674) and fat mass (SJ, = -0.203; CMJ, = -0.215, CMJa, =
-0.196) in children and age (SJ, = 0.431; CMJ, = 0.496; CMJa, = 0.536), appendicular lean
body mass (SJ,  0.214; CMJ,  0.160) and waist circumference (SJ,  -0.187; CMJ, 
-0.119) in adolescents were the body composition variables that better explained vertical jump
height. Thus, in addition to age and fat mass for children, we observed for the first time that
appendicular lean body mass and waist circumference in adolescents could be taken into
consideration as body composition predictors to assess and improve vertical jump performance in
young soccer players.

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compare training loads (3, 17), and to prevent
injuries (23), though for young players, it has
been mainly utilized to identify talented
athletes (35, 39). Moreover, squat jump (SJ)
and counter-movement jump (CMJ) height
have been associated with performance
success in this sport (5, 12).
Nonetheless, the interpretation of
jump ability performance during childhood
and adolescence in educational or sport
performance environments is often based
simply on a chronological age assessment.
However, maturation status should be taken
into consideration (25) by taking into account
other biological or body composition
parameters (8).
Body size has been described as a
confounding variable in vertical jump
performance (22), and several studies have
attempted to categorize those body
composition variables which better explain
jump ability during childhood and
adolescence. Markovic and Jaric (20, 21)
identified six variables as jump predictors:
maturation, age, gender, race, physical
activity level, and motor skills. Further,
several studies have attempted to identify
novel body composition variables from a
variety of young populations: Serbians, aged
12 to 17 years (25); Norwegians, aged 7 to 11
years (13); French youth, aged 11 to 16 years
(38); and English youth, aged 10 to 15 years
(37). Finally, Aouichaoui et al. (4) found a
positive correlation between total fat free
mass (FFM) and vertical jump performance in
a Tunisian population between the ages of 7
and 13 years, supporting the body size
paradigm (22).
Therefore, the aims of this study were
first to quantify the relationship between body
composition variables and vertical jump
performance. Secondly, to establish reference
values for vertical jump in young Spanish
soccer players between the ages of 7 and 19
years. We hypothesized that the
anthropometric measurement of skeletal
muscle and/or appendicular lean body mass
could be predictors of vertical jump
performance in childhood and/or adolescence.
Furthermore, these variables would serve as
non-invasive measurements to take into
consideration when assessing vertical jump
performance of young soccer players.
METHODS
Seven hundred and twenty-three
Spanish males between 7 and 19 years of age
took part in the present study. The
participants had at least 3 years of prior
soccer experience and had trained for ~2
h·day-1, 4 days·week-1 (including a weekly
competition) in Madrid, Spain. Further, they
were familiarized with vertical jump tests,
and those without previous experience or who
were unable to properly perform any of the
required tests were excluded. No participants
had any previous history of metabolic disease,
and no participants were taking any type of
medication.
Participants were divided into the
following age groups, accordingly to age
categories of the Spanish young soccer
leagues: (A) under the age of 10 (n = 130),
(B) between the ages of 10 and 12 (n = 147),
(C) between the ages of 13 and 14 (n = 205),
(D) between the ages of 15 and 16 (n = 130),
(E) between the ages of 17 and 19 (n = 111).
Before agreeing to participate in the study,
prospective participants’ guardians were fully
informed of the procedure and any possible
discomforts associated with the study. They
then gave their written informed consent. The
study was in accordance with the University
of Alcala´s Ethics Committee and the latest
version of the Declaration of Helsinki.

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Participants were tested during their
regular training schedules (between 6 and 9
PM) in the preparation period of the season.
Environmental conditions were maintained
(20 ± 1 ºC; 56 ± 5 %), and participants were
encouraged not to eat or drink for 2 hours
before the study.
Body composition assessments
Anthropometry was the method used
to measure body composition. Standing
height was measured by a stadiometer to the
nearest 0.1 cm, and body mass was measured
on a digital scale with an accuracy of 0.1 kg
(Harpenden Portable Stadiometer, Holtain
Ltd, Crosswell, Crymych, Pembs, United
Kingdom). Skinfold thicknesses on the right
side of the body were measured to the nearest
0.2 mm using a Holtain Ltd skinfold caliper
(Crosswell, UK). All materials were
calibrated, and the same ISAK accredited
specialist took all measurements. In order to
assess the reliability of each measure,
technical error of measurement (TEM%) was
calculated for all skinfolds, triceps (1.1%),
subscapular (1.6%), biceps (2.0%), iliac crest
(1.9%), supraspinale (2.2%), abdominal
(2.1%), front thigh (2.3%), medial calf
(1.2%); and circumferences taken, relaxed
arm (0.3%), waist (0.3%), hips (0.4%), gluteal
(0.3%), and calf (0.6%).
Fat mass (FM) (R2 = 0.77) (31, 32,
34), appendicular lean body mass (corrected
muscle girth model) (ALBM) (R2 = 0.93)
(28), and skeletal muscle mass (SMM) (R2 =
0.97) (27) were obtained from previously
reported formulas.
Vertical Jump Tests
After anthropometric measurements, a
warm-up routine consisted of low-intensity
aerobic exercises (3 minutes), dynamic
stretching (5 minutes), and single and
rebound jumps (2 minutes) was completed.
Then, participants performed three protocols
of vertical jump tests with proven reliability
and validity (19): squat jump (SJ), counter-
movement jump (CMJ), and Abalakov test or
counter-movement jump with arm swing
(CMJa). Based on a pilot study performed
previously, two attempts were carried out for
each type of test, allowing 1 minute of rest
between attempts of the same test and 2
minutes between different vertical jump tests
to ensure total recovery.
The SJ is composed of a concentric
phase preceded by an isometric phase with
90º knee flexion. To prevent the use of elastic
energy, participants stayed in the isometric
phase for 3 seconds. Also, they kept their
hands on their hips to avoid arm swing
impulse when they were required to perform a
maximal jump (15). No sinking or
countermovement was allowed.
The CMJ is composed of an initial
negative or eccentric phase that finishes with
the subject in the squat position with 90º knee
flexion and is followed by an immediate
concentric or positive phase to perform a
maximal jump. Participants kept their hands
on their hips.
Finally, the CMJa consists of a CMJ
in which arm swing is permitted. All
participants performed the swing by
beginning with their arms extended in the
anatomical position. Any other arm swing
was not permitted.
All trials were video recorded to
ensure proper technique. Vertical jump
performances were collected by an infrared
photocell system called Optojump (Microgate
SRL, Bolzano, Italy) which was connected to
a portable computer with the adequate
software (Optojump software, version
3.01.0001) (11).

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Statistical Analysis
The SPSS statistical software package
(version 17.0) was used, and all results
obtained were presented as mean ± SD. The
Kolmogorov-Smirnov test was used to assess
the normality of the anthropometric and
vertical jump variables (p> 0.05). One-way
ANOVA was used to analyze the
comparisons between age groups and
Bonferroni was used as post hoc test.
Intraclass correlation coefficients (ICCs) were
also calculated to confirm the concordance of
the measurements.
Pearson correlation and partial
correlation controlling for age were used to
assess association between anthropometric
and vertical jump parameters (p< 0.01; p<
0.05). Subsequently, a linear regression
between vertical jump performance variables
and body composition (SMM, ALBM, and
FFM) was performed. Finally, three multiple
regressions were calculated to obtain the body
composition variables (p< 0.05) that predict
vertical jump height performances for
children, adolescents, and both.
RESULTS
Effects of categories on Anthropometric and
Vertical Jump variables
Mean and standard deviation data
from the anthropometric and vertical jump
variables were calculated and are presented in
Table 1. Children and adolescents showed
statistically significant differences for
demographic variables (age, height, and
weight) (p< 0.05) between all categories, as
well as for SMM, ALBM, and FFM (p<
0.01). Nevertheless, the FM variable was not
statistically different between groups A, B,
and C, but significant relationships were
found between these groups and the
remaining ones (D and E; p< 0.05). Also,
waist circumference (WC) showed a
progressive and significant increase between
categories A, B, C, and D, whereas no
significant differences were found between
categories D and E.
Finally, vertical jump repeatability
(ICC; 95% CI) was calculated for all
protocols: SJ (0.995, 0.994-0.996), CMJ
(0.994; 0.993-0.995), and CMJa (0.996;
0.995-0.997), and significant differences were
also found in all vertical jump tests among all
age groups (p< 0.001) (Table 1).
Associations between Anthropometric and
Vertical Jump variables
Relationship between the
anthropometric and vertical jump variables
was calculated through a Pearson correlation
coefficient (data not presented). Given that
Pearson correlation showed strong
correlations between anthropometric and
vertical variable measurements (p< 0.01), a
partial correlation was performed controlling
for age (Table 2). In partial correlation, a
reduction in all coefficients was detected
compared to Pearson’s correlation. Also, a
significant association between heights of the
three vertical jump tests and body
composition variables of height, weight, FM,
and FFM (p< 0.01) was observed. SMM,
ALBM, and waist circumference were also
significantly related, though this relationship
was less pronounced (p< 0.05).
Linear Regression model for Vertical Jump
Height
Figure 1 showed linear contribution of
the independent body composition variables
(SMM, ALBM, and FFM) to the vertical
jump tests (SJ height, CMJ height, and CMJa
height) of the whole cohort of participants. A
moderate to strong relationship (R2 = 0.44 to
0.61) between the SMM, ALBM, and FFM
and the vertical jump tests was observed,
though the FFM has the strongest relationship
with the tests when compared to the SMM
and ALBM.

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Table 1. Mean ± SD of anthropometric and vertical jump variables compared by category.
A
B
C
D
E
Total
(N = 130)
(N = 147)
(N = 205)
(N = 130)
(N = 111)
(N = 723)
Mean±SD
Sig.
Mean±SD
Sig.
Mean±SD
Sig.
Mean±SD
Sig.
Mean±SD
Mean±SD
Age (yr)
9.1 ±0.7
BCDE**
11.1 ±0.6
CDE**
12.9 ±0.6
DE**
15.1 ±0.7
E**
17.3 ±0.9
13.3 ±3.1
Height (cm)
130 ±7
BCDE**
144 ±7
CDE**
156 ±9
DE**
169 ±7
E**
174 ±7
156 ±17
Weight (kg)
31.2 ±6.1
BCDE**
37.1 ±6.4
CDE**
45.7 ±9.2
DE**
57 ±10
E**
66.0 ±7.6
47.7 ±15
BMI
17.3 ±2.3
CDE**
17.8 ±2.2
CDE**
18.5 ±2.5
DE**
19.9 ±2.3
E**
21.7 ±2.1
19 ±2.5
WC (cm)
64.3 ±8.5
CDE**B*
68.0 ±9
CDE***
72.6 ±11
DE**
78.1 ±11
80.8 ±10
72.8 ±11
%FM
17.3 ±6.4
E**D*
18.5 ±5.9
DE**
18.4 ±6.7
DE**
15.0 ±4.5
13.9 ±4.7
16.7 ±6.1
FM (kg)
5.7 ±3.2
CDE**B*
7.1 ±3.3
E**CD*
8.7 ±4.4
8.8 ±4.3
9.3 ±4.0
8.0 ±3.9
FFM (kg)
13.9 ±4.7
BCDE**
18.6 ±5.1
CDE**
27.2 ±8.6
DE**
42.0 ±8.7
E**
52.1 ±7.0
31 ±16
SMM (kg)
15.8 ±3.1
BCDE**
19.0 ±3.4
CDE**
22.9 ±6.6
DE**
28.3 ±4.9
E**
32.9 ±3.7
24 ±7.7
ALBM (kg)
14.4 ±2.8
BCDE**
17.1 ±3.0
CDE**
20.6 ±6.7
DE**
25.2 ±4.4
E**
29.2 ±3.4
21.5 ±7
SJ Height (cm)
17.0 ±2.6
BCDE**
19.5 ±3.1
CDE**
21.6 ±3.4
DE**
25.6 ±5.1
E**
31.0 ±3.7
22.9 ±6.0
CMJ Height (cm)
19.3 ±3.0
BCDE**
22.7 ±3.8
CDE**
25.0 ±3.8
DE**
29.8 ±4.9
E**
36.2 ±4.2
26.6 ±7.0
CMJa Height (cm)
22.5 ±3.7
BCDE**
27.0 ±4.6
CDE**
29.6 ±4.9
DE**
35.9 ±5.6
E**
42.9 ±4.9
31.6 ±8.4
A, under 10 yrs; B, under 13 yrs; C, under 15 yrs; D, under 17 yrs; E, under 19 yrs.
SD, standard deviation; Sig. statistical significance ** p < 0.001; * p < 0.05.
BMI, Body Mass Index; WC, waist circumference; FM, fat mass; FFM, fat free mass; SMM, skeletal muscle
mass; ALBM, appendicular lean body mass; SJ, squat jump; CMJ, counter-movement jump; CMJa, counter-
movement jump with arm swing.
Table 2. Partial correlation coefficient controlling for age.
Height
Weight
WC
FM
FM
FFM
SMM
ALBM
(cm)
(kg)
(cm)
(%)
(kg)
(kg)
(kg)
(kg)
SJ Height (cm)
0.173**
0.091*
-0.073*
-0.347**
-0.232**
0.372**
0.076*
0.083*
CMJ Height (cm)
0.169**
0.098*
-0.081*
-0.334**
-0.214**
0.368**
0.093*
0.101*
CMJa Height (cm)
0.203**
0.099*
-0.082*
-0.359**
-0.236**
0.389**
0.092*
0.104*
Significance: ** p < 0.01; * p <0.05.
WC, waist circumference; FM, fat mass; FFM, fat free mass; SMM, skeletal muscle mass; ALBM,
appendicular lean body mass; SJ, squat jump; CMJ, counter-movement jump; CMJa, counter-movement jump
with arm swing.

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Figure 1. Single linear regression between SMM, ALBM, and FFM and (A) SJ height, (B) CMJ height, and (C) CMJa.

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Multiple Regression model for Vertical
Jump Height
Finally, the relative contribution of
each independent body composition variable
in the groups of children, adolescents, and the
two combined to vertical jump height in the
SJ, CMJ, and CMJa tests was examined
(Table 3). Multiple prediction models for
children indicated that age and fat mass were
the best variables for explaining height
changes in the three vertical jump tests, while
the models for adolescents showed that age,
ALBM, and waist circumference were the
best predictors of the SJ and CMJ height. But,
WC and ALBM was excluded from the CMJa
height model. Finally, the prediction model
from the whole cohort of players (7 to 19)
years showed that age, FM, ALBM, and waist
circumference were the variables which best
predicted SJ and CMJ height. However,
ALBM and waist circumference were
excluded from the CMJa height model.
Table 3. Multiple regression equations predicting vertical jump height variables
SJ Height
CMJ Height
CMJa Height

SEE
R2

SEE
R2

SEE
R2
Children
(7-13 yrs)
Constant
5.490*
2.922
0.360
4.495*
3.272
0.436
4.610*
4.097
0.410
Age
0.635
0.687
0.674
FM
-0.203
-0.215
-0.196
Adolescents
(13-19 yrs)
Constant
2.461*
3.495
0.266
0.223*
4.662
0.306
-0.584*
5.369
0.288
Age
0.431
0.496
0.536
ALBM
0.214
0.160
WC
-0.187
-0.119
All
(7-19 yrs)
Constant
3.761*
3.587
0.619
2.941*
3.853
0.671
0.455*
4.635
0.672
Age
0.801
0.824
0.840
FM
-0.091
-0.098
-0.094
ALBM
0.097
0.085
WC
-0.131
-0.081
SJ, squat jump; CMJ, counter-movement jump; CMJa, counter-movement jump with arm swing; SEE, Standard error of
estimate; FM, fat mass; ALBM, appendicular lean body mass; WC, waist circumference.
Function 1 (children): Vertical jump (SJ, CMJ or CMJa) = constant + (age coefficient x age) + (FM coefficient x FM).
Function 2a (adolescents): Vertical jump (SJ or CMJ) = constant + (age coefficient x age) + (ALBM coefficient x
ALBM) + (WC coefficient x WC).
Function 2b (adolescents): Vertical jump (CMJa) = constant + (age coefficient x age).
Function 3a (7-19 yrs): Vertical jump (SJ or CMJ) = constant + (age coefficient x age) + (FM coefficient x FM) +
(ALBM coefficient x ALBM) + (WC coefficient x WC).
Function 3b (7-19 yrs): Vertical jump (CMJa) = constant + (age coefficient x age) + (FM coefficient x FM).
* p<0.001

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DISCUSSION
Vertical jump is a relevant skill for
assessing motor development during
preadolescence and adolescence (14) as well
as for examining soccer performance (5, 39).
Body size has been proposed as a
confounding factor in vertical jump
performance during childhood and
adolescence (22, 25), and several variables
related to body composition have been found
to be predictors of vertical jump performance
(4, 20, 21): age, height, weight, and fat free
mass. Therefore, we hypothesized that
skeletal muscle mass and/or appendicular lean
body mass may influence and improve the
existing model for predicting vertical jump
height in young Spanish soccer players.
Puberty involves important bodily and
physiological changes in humans and could
explain the significant increase in all
anthropometric parameters that we found in
this study (29). As expected, the association
between fat mass and male pubertal onset was
nonlinear (Table 1), and the progressive
increase of the fat mass began after group C
(under 15 yrs), in accordance with the
beginning of puberty in boys (~13 years)
(36); thus, a high fat mass in this age range
could be explained as “hormonal preparation”
for puberty (1, 2). Accordingly, skeletal
muscle mass showed the largest increase (5.4
kg) between groups B (under 13 yrs) and C
(under 15 yrs), whereas appendicular lean
body mass reported a more progressive and
significant increase.
It has been suggested that between the
ages of 13 and 15 years, young soccer players
obtain their best performance in vertical jump
tests (18, 25). Thus, we expected to find
greater differences between groups C and D
(under 15 and under 17, respectively).
However, in Table 1, it can be observed that
within the progressive and statistically
significant increase in vertical jump heights of
the three tests, the greatest improvement in
performance was detected between groups D
and E (under 17 and under 19, respectively)
for all tests, even though the increase between
group C and D (under 15 and under 17,
respectively) was also considerable (5.4 vs.
4.0 cm, SJ; 6.4 vs. 4.8 cm, CMJ; 7.0 vs. 6.3
cm, CMJa; respectively).
Malina et al. (18) showed that vertical
jump performance increased concurrently
with sexual maturity. Moreover, testosterone
and androgen hormones have been marked as
the main factors responsible for the higher
performance in young male soccer players
during puberty (8), based on their anabolic
effects, including bone and muscle
development, loss of fat mass, and increased
lean body mass (9). Concretely, testosterone
levels increase significantly after Tanner
stage 2 and until stage 5, but not before (10).
Thus, those young soccer players in later
stages of puberty with higher androgen levels
had higher vertical jump performance in all
tests compared to those in early or mid-
puberty with lower androgen levels.
Nevertheless, motor unit synchronization and
recruitment must be also taken into
consideration (16).
Therefore, the assessment of some
variables related to the androgenic or anabolic
changes produced during the maturation
process would be useful in interpreting
vertical jump performance (8, 18). Thus, a
partial correlation controlling for age (Table
2) was carried out and revealed that FM and
FFM were more strongly correlated with
height variables of the SJ, CMJ, and CMJa
tests (p< 0.01), while SMM and ALBM were
less significantly correlated (p< 0.05).
Subsequently, linear regressions among
vertical jump test variables and FFM, SMM,
and ALBM were performed, and they showed
that FFM was a more accurate body

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composition variable for explaining vertical
jump height compared to ALBM and SMM.
Finally, three multiple regression
equations were calculated for children,
adolescents, and the whole cohort. Previous
data from a population of active Tunisian
children between the ages of 7 and 13 years
revealed that age, height, weight, and fat-free
mass were the body composition variables
that most accurately predicted vertical jump
performance (4). Though our previous
analysis seemed to support that idea, we did
not find this relationship. In contrast, in table
3 it can be observed that for children between
the ages of 7 and 13 years, age and FM were
the best predictors of vertical jump height.
The discrepancy in the two regression models
might reside in the population differences. In
this study, a population of seven hundred and
twenty-three children who trained ~2 h·day-1,
4 days·week-1 and had 3 years of soccer
experience was recruited. Likely, the degree
of training and soccer expertise could explain
why in this study height, weight, and FFM did
not predict vertical jump height in the
regression models performed (20, 21). On the
other hand, for the adolescent group (table 3),
age, ALBM, and waist circumference were
the most accurate variables for predicting SJ
and CMJ height, while for the CMJa, only age
was included in the function. The inclusion of
waist circumference, which has been related
to abdominal fat among children and
adolescent populations (33), suggests that
trunk fat mass may play an important role in
vertical jump prediction in pubertal soccer
players. Likewise, lean body mass has been
associated with maximal anaerobic power
during growth (24), and fat free mass has
been related to vertical jump performance in
children as well (4). Thus, the identification
of appendicular body mass as a body
composition variable that predicts vertical
jump height was not a surprise, even though it
had not been observed previously. Lastly, we
observed that age, FM, ALBM, and waist
circumference were the body composition
variables that predicted SJ and CMJ height
for a population of young soccer players aged
7 to 19 years. It is also observed that age
coefficient increased substantially  0.801
vs.  0.635 vs.  0.431) compared to
children and adolescents models in
accordance with the influence of age in
vertical jump performance (37).
PRACTICAL APPLICATIONS
Vertical jump is simple and recurrent
skill measured by physical educators and
strength and conditioning coaches during
childhood and adolescent for several
purposes. However, chronological age is the
only variable used to categorize the result
obtained in this population. According to the
present study, it should take into
consideration body composition variables
such as fat mass, appendicular lean body mass
and waist circumference in order to consider
biological individuality of each children
and/or adolescent and thus to perform a more
adequate assessment of vertical jump skill and
also improve it performance throughout the
reduction of fat mass and waist circumference
as well as the augment of appendicular lean
body mass.
CONCLUSIONS
We conclude that for a Spanish
population of children and adolescents
between the ages of 7 and 19 who had prior
soccer experience (≥ 3 yrs) and had trained
for ~2 h·day-1, 4 days·week-1, age, fat mass,
appendicular lean body mass, and waist
circumference were identified as predictors of
vertical jump height. Although. total skeletal
muscle mass measured anthropometrically
has not been identified as a predictor of
vertical jump neither in childhood or
adolescence, we found for the first time a

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relationship between appendicular lean body
mass and waist circumference in the
adolescent group (13 to 19 yrs) of young
soccer players.
Thus, in addition to age, the
anthropometric measure of fat mass in
children and appendicular lean body mass and
waist circumference in adolescents could be
taken into consideration to perform a fairly
assessment of vertical jump performance in
an educational or performance perspective of
young soccer players.
Acknowledgement
The authors have no conflicts of
interest that are directly relevant to the
content of this research and wish to thank all
participants and tutors for their invaluable
contribution to the study.
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