Advances in Physical Education
2013. Vol.3, No.3, 125-130
Published Online August 2013 in SciRes (
Copyright © 2013 SciRes. 125
Anthropometric and Physical Characteristics of
Tunisians Young Soccer Players
Mehdi Ben Brahim1, Rym Bougatfa2, Amri Mohamed2
1Laboratory of Physiology, Faculty of Sciences of Tunis, University of Tunis, Tunis, Tunisia
2Laboratory Adaptations Cardio-Circulatory, Respiratory, Metabolic and Hormonal to Muscular Exercise,
Faculty of Medicine Ibn El Jazzar, University of Sousse, Sousse, Tunisia
Received April 20th, 2013; revised May 20th, 2013; accepted May 27th, 2013
Copyright © 2013 Mehdi Ben Brahim et al. This is an open access article distributed under the Creative Com-
mons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, pro-
vided the original work is properly cited.
The aim of this investigation was to provide anthropometric, physical and physiological performance cha-
racteristics of Tunisian young soccer players and to examine the relationship between selected parameters
according to their playing standard position. One hundred under 13 years old (U-13) male soccer players
were tested. They were classified according to their playing standard positions (goalkeeper: GK, defender:
DF, midfield: MF, and forward: FW). Testing consisted of anthropometric measurements including
weight, height, and body mass index, and performance measures of speed (5, 15, and 20 m), agility run
(Agility-15 m and Ball-15 m), vertical jumping, ball shooting, and aerobic capacity (Hoff Dribble Test
and Yo-Yo intermittent Endurance Run, YYIER). GK were taller and heavier than other players. Signifi-
cant differences of playing positions for the majority of the physical tests include 20 m sprint, Agility-15
m and Ball-15 m times (all p < .01), as well as squat jump and counter movement jump (all p < .01). In
addition, weight was significantly correlated with 20 m sprint (r = .29, p < .01), Agility-15 m (r = .30, p
< .01) and Ball-15 m (r = .31, p < .01) times as well as ball shooting speed (r = .42, p < .01). Multiple
regression analyses showed that weight and height were the most significant predictors of 20 m sprint
time and the YYIER distance, respectively. In conclusion, performance abilities between positions in
young soccer players appear to be different. Anthropometry can discriminate physical capacities and soc-
cer skills providing a scientific rational behind the coaches’ practice of selecting young soccer players.
Keywords: Young Soccer Players; Anthropometric; Performance; Playing Positions; Relationship
Soccer is the most popular worldwide sport which is charac-
terized by high intensity, short-term actions and pauses of vary-
ing length (Stroyer, Hansen, & Klausen, 2004). To succeed in a
team sport, soccer players need the optimal combination of
technical, tactical, physical characteristics (like somatotype) and
mental motivation (Bangsbo & Michalsik, 2002). Indeed, many
experts in the field, such as soccer coaches, managers and sci-
entists believe that the success of this sport can be associated
with anthropometric characteristics of players. Also, some pre-
vious studies have focused on the relationship between anthro-
pometric profiles of players and their standard positions (Rienzi,
Drust, Reilly, Carter, & Martin, 2000; Gil, Ruiz, Irazusta, &
Irazusta, 2007). Goalkeepers are taller than central position
players (Reilly, Bangsbo, & Franks, 2000), such as defensive
and offensive central players (Reilly, Williams, Nevill, & Franks,
2000). Similar studies on position-specific anthropometric pro-
files have been reported for Australian football (Young, New-
ton, Doyle, Chapman, Cormack, Stewart et al., 2005; Pyne, Du-
thie, Saunders, Petersen, & Portus, 2006), Gaelic football (Mcin-
tyre & Hall, 2005; Mcintyre, 2005), rugby (Duthie, Pyne, &
Hooper, 2003) and American football (Mcgee & Burkett, 2003).
So, we can hypothesize positional difference existing in anthro-
pometry as soccer coaches would have believed that this short-
term benefits and purposively selects some players with a body
type for specific positions. It is evident from the foregoing that
most research has focused either on amateur players or profes-
sional players on the senior which pushed us to work with
young footballers aged under 13, pre-pubescent age. Informa-
tion in this regard may be helpful to trainers and strength condi-
tioning coaches for enhancing players’ specific performance
and talent selection. The aim of the present study was to describe
anthropometric, physical and physiological performance char-
acteristics of Tunisian football players under 13 years old and
to examine the relationship between selected parameters ac-
cording to their playing standard position.
One hundredyoung male soccer players (age under 13 years)
from six different teams belonging in first division of the Tuni-
sian Championship participated in this study, which was con-
ducted during the competitive season. They performed soccer
training five times a week and played in one competitive match
during the weekends. The participants were from a range of
outfield playing positions. Following completion of a screening
questionnaire, written informed consent and parental consent
was obtained from all participants in accordance with the inter-
national ethical standards. The data collection took place during
May (towards the end of the Tunisian season), so teams were
Anthropometric Measures
Participants reported to the laboratory for the measurement
of height, body mass and percentage body fat. Body mass was
measured to the nearest .1 kg using an electronic scale (Seca
Instruments Ltd., Hamburg, Germany) and height was meas-
ured to the nearest .001 m using a stadiometer (Holtain Ltd.,
Crymych, UK). Skinfold thickness at four sites (biceps, triceps,
subscapular, and suprailiac) was measured using Harpenden
callipers (Lange, Cambridge, MA, USA). All the data were col-
lected by the authors who were experienced in taking skin fold
Performance Measures
Before the start of trials, a standard warm-up was achieved
including some exercise of jogging, dynamic stretching and a
series of sprints. Knowing that all subjects are used to this kind
of exercise so familiar with the protocols of the various tests of
this study, each player was verbally encouraged to give as his
maximum effort during the tests. To ovoid the chronobiology
bias on physical performances, all tests have been performed
during the period of May under conditions of temperature
(15˚C to 22˚C) in the same moment of day (8 h am) and after
being informed about the nutritional status of subjects (balanc-
ed morning meal).
Sprint Tests: (5, 10 and 30 m)
The participants performed three maximal 30-m sprints (with
5- and 10-m split times) on an indoor synthetic court. During
recovery (2 - 3 min), the participants walked back to the start-
ing line and then waited for the next sprint. Time was recorded
using photo-cell gates (Brower Timing Systems, Salt Lake City,
UT, USA, accuracy of .01 s) placed .4 m above the ground. The
participants started the sprint when they feel ready from a
standing start .5 m behind the first timing gate. Stance for the
start was consistent for all participants. The best performance of
both trials of 30-m time was selected for analysis.
Squat Jump
The subject started from a semi-squat position with the hands
held at the hips to avoid upper limb body contribution and
jumped upward as high as possible. This test was used to esti-
mate muscle power under concentric condition. A successful
trial was one where there was no sinking or countermovement
before the execution of the jump. The intra-class correlation
coefficient (ICC) of the squat jump (SJ) in our study was .96
(95% confidence interval [CI]: .91 - .98) with no significant
differences between the 2 trial scores (p = .62, effect size [ES]
= .05 [trivial]).
Counter Movement Jump
The subject began from an upright standing position, per-
formed a very fast preliminary downward eccentric action fol-
lowed immediately by a jump for maximal height. Hands re-
mained at the hips for the entire movement to eliminate any
influence of arm swing. The ICC of the countermovement jump
(CMJ) in our study was .97 (95% CI: .92 - .99) with no signifi-
cant differences between the 2 trial scores (p = .91, ES = .01
15-m Agility Runs (Agility-15 m)
In this test, players’ velocity in a 15-m agility run was meas-
ured using the same photocell gates system as above. As pro-
posed by Mujika et al. (2009), players started running 3 m be-
hind the initial set of gates. After 3 m of line running, players
entered a 3-m slalom section marked by three sticks 1.6 m of
height and placed 1.5 m apart, and then cleared a .5 m-height
hurdle placed 2 m beyond the third stick. Players finally ran 7
m to break the second set of photocell gates, which stopped the
timer. Each player performed two maximal Agility 15 m in-
terspersed with 3 min of passive recovery, and the fastest time
achieved was recorded.
15-m Ball Dribbling (Ball-15 m)
Five minutes after the Agility-15 m, players performed the
Ball-15 m (Mujika, Santisteban, Impellizzeri, & Castagna, 2009).
This test was similar to the Agility-15 m, but players were re-
quired to dribble a ball while performing the test. After the
slalom section of the test, the ball was kicked under the hurdle
while the player cleared it. The player then kicked the ball to-
wards either of two small goals placed diagonally 7 m on the
left and the right sides of the hurdle, and sprinted to the nish
line. Each player performed two maximal Ball 15 m intersper-
sed with 3 min of passive recovery, and the fastest time achi-
eved was recorded.
Ball Shooting Test
The players performed maximal velocity instep place kicks
of a stationary ball. A ball of FIFA standard size and inflation
was kicked 4 m toward a target 131 m in size (Dorge, Anderson,
Sorensen, & Simonsen, 2002). Players were asked to strike the
ball as hard as possible and 5 shots were allowed for each play-
er with 1-minute rest between shots (Cometti, Maffiuletti, Pous-
son, Chatard, & Maffulli, 2001). Ball speed was measured by a
radar gun (Sports Radar Gun SRA 3000; Precision Training In-
strument, IL) located .3 m to the stationary ball and pointed
toward the target according to the instruction manual. The shot
that hit the target and produced the highest ball speed was se-
lected for analysis.
Hoff Dribble Test
The Hoff dribble test which proposed by Hoff et al. (2002) is
a soccer-specific dribbling track in which players have to drib-
ble the ball through routed obstacles. Before the test, players
were instructed to jog slowly through the route for 1 lap to fa-
miliarize themselves, followed by a self-pace dribble for an-
other lap. The distance for 1 lap has been established at 290 m
such as proposed by Chamari et al. (2005). As previously de-
scribed the purpose of this test was to cover the maximum dis-
tance during a 10 minute period.
Copyright © 2013 SciRes.
Copyright © 2013 SciRes. 127
Yo-Yo Intermittent Endurance Run
Because soccer includes high-intensity intermittent bouts of
exercise, which stresses the anaerobic glycolysis metabolic
pathway (Drust, Cable, & Reilly, 2000), YYIER (level 1) is
close to the soccer exercise pattern. In this test, the players had
to perform a series of 20 m shuttle runs at a pace set by an au-
dio metronome with a standard rest interval between shuttles (5
seconds) (Bangsbo & Michalsik, 2002). The time allowed for
the shuttles was progressively decreased, that is, the speed was
increased. The test was terminated when the player was unable
to maintain the required speed. The distance covered in the shu-
ttles was recorded for analysis, but the distance covered during
rest intervals was excluded (Castagna, Impellizzeri, Belardinelli,
Abt, Coutts, Chamari et al., 2006).
Tests were performed over three days with 5 min of recovery
in-between in the following order: 1 day, maximal 30-m sprints,
SJ, CMJ and 15 m agility test with and without ball; 2nd day,
ball shooting and Hoff dribble test; and 3rd day, YYIER.
Statistical Analysis
The statistical study is based on a sample of 100 players. Dif-
ferent oven positions were determined: the goalkeepers (GK),
the defenders (DF), the midfielders (MF) and the forwards
(FW). Statistical analysis was performed using SPSS version
18.0 (SPSS Inc., Chicago, HIM (IT), and the USA). Pearson
product-moment correlations were used to examines the rela-
tionship between anthropometric, physiological, and perform-
ance variables. The method of linear regression was used for
determining the impact of the anthropometric characteristics on
the physical and physiological performances. This relation can
be represented analytically as follows: (physiological perform-
ances) = f (height or weight). The linear relation between the
anthropometric characteristics and the physical and physiologi-
cal performances is represented by several regressions (R1, R2,
R3, R4, R5, R6, R7, and R8). A one-way analysis of variance
(ANOVA) and Post Hoc Test was used to determine if signifi-
cant differences existed between the player’s positions. Pair
wise comparisons were made using Bonferroni adjustment to
control the type one error rate. Level of significance was de-
fined as p .05.
The subjects’ age, anthropometric and physical performance
data are summarized in Table 1, and significant differences be-
tween groups are indicated. GK were heavier and taller than DF,
MF and FW (p < .01). In the same way, significant difference
of positions for the majority of the physical tests including 20
m sprint time, Agility-15 m and Ball-15 m, SJ, CMJ, YYIER
distance and ball shooting speed (all p < .01). Significant posi-
tional difference was also found in Hoff dribbling distance,
since MF performed 64.5 m greater than the DF.
Body weight was significantly correlated with 20 msprint
time (r = .29, p < .01), Agility-15 m and Ball-15 m, ball shoot-
ing speed (r = .42, p < .01), Hoff dribbling and the YYIER
tests (p < .01), as well as with SJ and CMJ (p < .05). The body
mass is so significantly correlated to most of the physical and
physiological characteristics studied (p < .01). The body mass
index is not significantly correlated with all performances (Ta-
ble 2).
Multiple regressions between anthropometry and testing phy-
sical performances are summarized in Table 3. We notice that
the effect of the height and the body mass are globally signifi-
cant on the totality of the physical and physiological perfor-
Table 1.
Anthropometric and physiological performances of playing position standards.
GK DF MF FW P-value
n 14 26 34 26
Age (y) 12.4 (±.51) 12.3 (±.48) 12.4 (±.50) 12.4 (±.50) NS
Soccer experience (y) 3.0 (±1.03) 2.9 (±1.09) 2.9 (±1.07) 3.0 (±.84) NS
Height (cm) 159 (±6.56) 153 (±6.80) 149 (±5.64) 150 (±7.39) .000**
Body mass (kg) 48.8 (±5.15) 45.8 (±4.86) 42.3 (±4.17) 44.5 (±6.83) .002**
BMI (kg·m2) 19.1 (±2.05) 19.3 (±1.41) 19.0 (±2.15) 19.6 (±2.74) NS
5 m sprint (s) 1.20 (±.04) 1.17 (±.06) 1.17 (±.07) 1.19 (±.07) NS
20 m sprint (s) 3.88 (±.07) 3.37 (±.05) 3.30 (±.07) 3.52 (±.09) .000**
Agility-15 m (s) 5.01 (±.23) 4.32 (±.19) 4.24 (±.15) 4.56 (±.13) .000**
Ball-15 m (s) 5.77 (±.22) 5.36 (±.18) 4.98 (±.17) 5.12 (±.20) .000**
SJ (cm) 29.30 (±2.87) 27.39 (±4.25) 25.49 (±2.95) 26.86 (±3.44) .007**
CMJ (cm) 32.55 (±3.21) 29.41 (±4.29) 27.41 (±3.92) 28.29 (±3.81) .001**
Ball shooting (km·h1) 68.32 (±5.93) 7.12 (±8.56) 69.46 (±7.93) 71.28 (±5.45) .000**
Hoff dribbling test (m) 980 (±111) 1167 (±94) 1231 (±105) 1202 (±126) .000**
YYIER (m) 1400 (±89) 1580 (±283) 2018 (±203) 1680 (±271) .000**
Note: **p < .01. Data are mean ± SD. GK = goalkeeper; DF = defender; MF = midfielder; FW = forward; n = sample size; BMI = body mass index; YYIER = Yo-Yo
intermittent endurance run, NS = no significant difference.
Table 2.
Correlation between anthropometric and physical performances (n = 100).
Anthropometrics Physiological performances r r2
20 m sprint time .29** .08**
Agility-15 m time .36** .12**
Ball-15 m time .41** .16**
SJ height .2* .04*
CMJ height .19* .03*
Ball shooting speed .42** .17**
Hoff dribble distance .43** .18**
YYIER distance .24* .05*
20 m sprint time .34** .11**
Agility-15 m time .30** .09**
Ball-15 m time .31** .09**
SJ height .23* .05*
CMJ height .25** .06**
Hoff dribble distance .35** .12**
Body mass
YYIER distance .40** .16**
Note: *p < .05; **p < .01; BMI = body mass index; YYIER = Yo-Yo intermittent endurance run.
Table 3.
Multiple regression analyses with body mass and body height as independent variable.
20 m sprint Agility-15 m Ball-15 m SJ CMJ YYIER Hoff test Ball shooting
Regression R1 R2 R3 R4 R5 R6 R7 R8
Constant 2.29
Height .005
Body mass .01
R2 13.1% 14.7% 18.4% 06% 07% 19% 22.6% 06%
F .001*** .000*** .000*** .04** .02** .000*** .000*** .04**
Note: *p < .05; **p < .01; ***p < .001, ( ): t student, F: statistic fisher.
mances except the test of speed 5 m (results not represented in
Table 3).
The value of the probability relative to the statistics of Fisher
for R1 is of the order of .001 < .05 what shows us that the
height and the weight of the players of the category U13 have
an importing effect on the test of speed 20 meters. R3 showed
that height and body mass affect globally the test of agility
without ball with an explanation of the order of 14.7% but only
the variable of weight is statistically significant and exercises a
positive impact on the agility test without ball (tstudent = 2.44 >
1.96). R7 is the best model so showing the effect of the height
and the weight on Hoff test, in particular the weight is statisti-
cally significant (p < .05), and the weight also is statistically
significant (p < .01). These two parameters act negatively on
the performance of this test and explain approximately 22.6%
of the variation of this test for the young football players (U13).
Positional Differences in Anthropometry
The results of the present study showed significant differ-
ences between playing position standards concerning the an-
thropometric measures, especially body weight and height. In
agreement with Gill et al. (2007), GKs were heavier and taller
than other playing position groups. Similar characteristics would
help GKs in aerial duels allowing them to defend their goals.
Other anthropometric differences according to playing position
were identified. Our results are consistent in partly with the
findings of Malina et al. (2000) who found, in soccer players
aged 11 to 16 years old, that FWs were taller than DFs and GKs
were heavier than MFs, whereas FWs were shorter than MFs,
GKs, and DFs. In the contrary, no playing position effect was
noted between four positions concerning BMI. Our data are si-
Copyright © 2013 SciRes.
milar to those reported by Slavko et al. (2011) in amateur Ger-
man football players but different to those reported by Wong et
al. (2009) in Under 14 years soccer players. This discrepancy
could be explained in part by the sample size, the different
methods of measurement as well as the performance level. The
results of the current study showed substantial variations in sta-
ture and body mass suggesting that there are different physical
demands in each playing position standard. Accordingly, Reilly
et al. (2000) have concluded that elite soccer teams are charac-
terized by relative heterogeneity in body size. Therefore, there
are likely to be anthropometric predispositions for positional
roles, with taller players being the most suitable for central de-
fensive positions and for the “target” player among the strikers
or forwards. This factor may be linked with pres election of
early maturers for key positional roles, where body size rather
than playing skills provides an advantage.
Positional Differences in Physical and Physiological
The data of physical and physiological performances are dif-
ferent according to playing position standards. In fact, a sig-
nificant difference is shown for the 20 m sprint time with the
best performance observed in MFs. The results of present study
are in agreement with Gil et al. (2007) who showed that FDs
were faster than DFs and MFs at the 30 m sprint test and dis-
agree with the study of Malina et al. (2005). Accordingly, Di
Salvo et al. (2007) highlighted that FW covered the greater di-
stance at very high-intensity run compared with DF and MF. In
summary, the U13 soccer players have a level of sprint and per-
formance significantly different among playing positions, but
when it is approaching the professional level, positional differ-
ences exist, where FWs become the fastest sprinters as they
cover the greatest distance by high speed during games. Consis-
tent with Wong et al. (2009), no difference between playing po-
sitions was found in 5 m and 10 m sprint times. In addition, a
significant difference of position is shown concerning Hoff
dribbling test where MF covered the best distance in the group
(MF: 1231, GK: 980 m) which is in agreement with the results
of Di Salvo et al. (2008). Similar results were found in seniors
professional football players (Di Salvo, Baron, Tschan, Calde-
ron Montero, Bachl, & Pigozzi, 2007).
In contrast with results of previous studies (Wong, Mujika,
Castagna, Chamari, Lau, & Wisloff, 2008) performed on Under
13 to Under 15 players, our results showed that there is signifi-
cant difference in jump height (SJ and CMJ) between the GK,
DF, MF and FW. In the present study, GK had the highest jump
height and MF had the lowest compare with DF and FW. These
results contradict the hypothesis that there is no positional dif-
ference in the test of jump for the young football players who
having an experience of soccer practice less than five years
(Malina, Eisenmann, Cumming, Ribeiro, & Aroso, 2004). The
ball shooting is an important factor in football performance es-
pecially in goal concretization. Indeed, a significant difference
is observed between the various playing positions which dis-
agree with the results advanced by Wong et al. (2008) and Ma-
lina et al. (2005).
A soccer player who is agile is able to change direction
abruptly without losing balance. Agility includes factors such
as speed, strength, balance and coordination and is beneficial
because it helps a player’s ability to get and hold onto the ball
(Sheppard & Young, 2006). In our study, we found that there is
a significant difference between the various positions of the
young players. Indeed, MF present the best performance in this
test with or without ball, on the other hand the GK had the bad
performance during both tests. The DF is faster than the FW in
the test without ball. The opposite is observed in the test with
These results confirm the fact that MF and FW are techni-
cally more developed than the DF and the GK in football. In
addition, agility training is an important part of any soccer
player’s regimen because it replicates the various motions play-
ers will experience during the run of play. Soccer is a game full
of direction and speed changes with and without the ball, and
agility training helps players become more agile and improves
coordination. Malina et al. (2005) and Wong et al. (2009) con-
firmed that there is no positional difference in YYIER among
U13 to U15, which is contradictory to the data of the present
Relationship betw een Anthropometric and Physical,
Physiological Performances
Body mass is the most significant predictor of 20 m sprint
time. Indeed, a negative parallelism found in our study between
body weight and sprint time is in agreement with the results of
Malina et al. (2004) who found that body mass is the most sig-
nificant predictor of 30 m sprint time. In addition, our results
show that body mass is the most significant predictor of CMJ.
On the other hand, consistent with the previous study (Malina,
Eisenmann, Cumming, Ribeiro, & Aroso, 2004), we found that
body height is the predictor of vertical jump performance. In
contrast to Wong et al. (2002), we found a negative relationship
between the YYIER and body height. Our results suggest that
height is not the most predictor of endurance capacity in young
soccer players. Other factors such as body weight could be the
major determinant of the YYIER. In fact, in our study we found
a strong negative relationship between YYIER distance and
body weight.
In summary, a high height can be explain by an important
muscular mass and a thin body mass index which lead us to say
that the football player who enjoys a high height is better in the
activities of strength and power than in the activities of endur-
ance. Finally, this research supports but in the short term, the
fact that soccer coaches can select young players based on their
anthropometry characteristics other than technical and tactical
performance (Helsen, Van Winckel, & Williams, 2005). There-
fore, as suggested by Reilly et al. (2000), Rienzi et al. (2000),
other factors other than absolute anthropometry advantage, such
as psychological and soccer-specific skills should be also con-
sidered in the selection of young soccer players for developing
future high-class players.
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