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114
Pediatric Exercise Science, 2010, 22, 114-134© 2010 Human Kinetics, Inc.
Physical Characteristics and Physiological Attributes of Adolescent Volleyball
Players—A Review
Ronnie Lidor and Gal ZivZinman College of Physical Education and Sport Sciences
The purpose of this article was to review a series of studies (n = 31) on physical characteristics, physiological attributes, and volleyball skills of female and male adolescent volleyball players. Among the main findings were (a) that male national players were taller and heavier than state and novice players, while female national players showed lower body fat values compared with state and novice players, and (b) vertical jump values were higher in starters versus nonstarters. Among the methodological concerns based on the reviewed studies were the lack of informa-tion on maturational age and lack of longitudinal studies. It was recommended that a careful selection of physiological tests should be made when assessing the abilities of adolescent volleyball players.
Training programs for adolescent volleyball players can benefit from the use of theoretical and practical knowledge from various related domains, among them exercise physiology, kinesiology, measurement and evaluation in sport, motor development, and sports medicine. Relevant information on issues related to the training process, such as physical characteristics of the female and the male ado-lescent players, physiological attributes, and volleyball skills, can be effectively applied in volleyball programs, particularly strength and conditioning programs specifically developed for adolescent players.
The sport sciences team that works with adolescent volleyball players through-out the training program, typically composed of volleyball coaches, strength and conditioning coaches, athletic trainers, and sport physicians, should obtain relevant information on the physical and physiological aspects of adolescent volleyball players to (a) use it when planning not only the entire training program but also the practice sessions undertaken in each phase of the training program—prepara-tion, competition, and transition (3), and (b) assess the contribution of the training program to the development of the players.
The current article had three purposes: (a) to review a series of studies on physical characteristics, physiological attributes, and volleyball skills of female and male volleyball adolescent players; (b) to outline a number of methodological
Lidor and Ziv are with the Zinman College of Physical Education and Sport Sciences, Wingate Institute, Netanya 42902, Israel.
Attributes of Adolescent Volleyball Players 115
concerns associated with the reviewed studies; and (c) to provide several practical recommendations for volleyball coaches and strength and conditioning coaches who work with both competitive and recreational adolescent volleyball players.
The reviewed articles were selected from an extensive search of the literature in the English language, including major computerized-databases (PubMed and SPORT Discus) and library holdings of sport sciences journals. In addition, a manual search was performed on East European journals published in English (e.g., Kinesiology and Biology in Sport). Search terms included, among others, volleyball, volleyball players, adolescent volleyball players, volleyball tests, and volleyball physiology. The articles included in this review were those reporting on volleyball players of amateur through elite status. We defined the term adolescence as the period of development between the ages 8–19 years in girls and 10–22 years in boys (19). We chose an age criterion of under 19 years, after which virtually all girls and most boys can be considered adults. Articles that pooled data for both female and male players were excluded. Thirty-one articles conforming to our criteria were included in this review.
Physical CharacteristicsA summary of the physical characteristics of the female and male adolescent players across the reviewed studies is presented in Tables 1 and 2, respectively. In most studies percent body fat was estimated from skinfold measurements which have a standard error of the estimate (SEE) of 3.4–3.9% fat (44), depending on the number of skinfold sites and the formulas used. Comparisons should be made, therefore, with caution.
Female Players
The description and the understanding of physical characteristics are of impor-tance, since variations in physiological [e.g., vertical jump (VJ), speed] and skill (e.g., spike, feint) performances can be explained to some extent by the anthro-pometric data (29). Height, body mass, and percent fat values ranged from 141 ± 6.6 cm in 10 year-old players (18), 31.26 ± 4.56 kg in 8–9 year-old players (25), and 17.2 ± 3.8% in 16 year-old players (39) to 182.19 ± 5.88 cm in 14–17 year-old players (31), 68.4 ± 1.3 kg in 16 year-old players (6), and 25% in 13–14 year-old players (25), respectively. For comparison, the average height and body mass for 16-year old American females are 161.9 cm and 63.0 kg, respectively (11). One specific example suggested that Czech players aged 8–14 were taller and slimmer than the Czech standards from 1981 (25). Similarly, Malina (18) reported that players aged 9–13 had a similar body mass but were taller than average American girls.
Three studies (9,21,36) showed increased height and body mass as age increased while one showed no significant differences (39). In the latter study, the lack of differences may have been due to the small differences in age (from 14 to 16 years).
In one study (36), significant correlations among 14 anthropometric measure-ments as well as players’ proficiency in several aspects of the game, such as attack-ing, blocking, and serving, were reported. For example, the tallest and heaviest
116
Tab
le 1
A
Su
mm
ary
of
the
Phy
sica
l Ch
arac
teri
stic
s o
f Fe
mal
e P
laye
rs (
Mea
ns
± S
D)
Stu
dy
Po
pu
lati
on
Hei
gh
t (c
m)
Mas
s (k
g)
%B
FF
FM
(kg
)
Bea
ls 2
002
(2)
Ran
ked
adol
esce
nt v
olle
ybal
l pl
ayer
s (n
= 2
3; a
ges
= 1
4–17
ye
ars)
171.
9 ±
8.0
65.2
± 8
.718
.3 ±
2.5
4-si
te s
kinf
old;
Equ
atio
ns o
f Ja
ckso
n an
d Po
l-lo
ck
53.3
*
Cha
ng e
t al.
2008
(4)
Play
ers
from
Tai
wan
’s ju
nior
na
tiona
l tea
m a
nd a
hig
h-sc
hool
(n
= 3
9)
168
± 6
.062
.7 ±
5.8
18.1
3 ±
2.6
2B
ioel
ectr
ical
impe
danc
e an
alys
is
51.3
*
Gab
bett
and
Geo
rgie
ff
2007
(6)
Juni
or v
olle
ybal
l pla
yers
(n
= 9
6); s
chol
arsh
ip h
olde
rs
with
in th
e Q
ueen
slan
d A
cad-
emy
of S
port
Tal
ent S
earc
h vo
lleyb
all p
rogr
am (
age
=
15.6
±.1
yea
rs)
Nat
iona
l lev
el:
179.
2 ±
1.0
Stat
e le
vel:
179.
5±.6
Nov
ice:
177.
0±.6
Nat
iona
l lev
el:
68.4
± 1
.3St
ate
leve
l:67
.2 ±
1.3
Nov
ice:
66.8
± 1
.2
Sum
of
7 sk
info
lds
repo
rted
Nat
iona
l lev
el:
69.7
± 1
.1 m
mSt
ate
leve
l:85
.1 ±
2.4
mm
Nov
ice:
114.
0 ±
3.1
N/A
Grg
anto
v et
al
. 200
6 (9
)M
embe
rs o
f 13
vol
leyb
all
team
s in
Cro
atia
Age
s =
12–
13 (
n =
32)
, 14–
15
(n =
147
), 1
6–17
(n
= 5
0),
18–1
9 (n
= 1
7)
Age
s 12
–13:
169.
33 ±
6.0
9A
ges
14–1
5:17
0.86
± 6
.45
Age
s 16
–17:
174.
36 ±
6.5
7A
ges
18–1
9:17
5.99
± 7
.37
Age
s 12
–13:
55.9
2 ±
8.6
2A
ges
14–1
5:59
.51
± 7
.28
Age
s 16
–17:
63.9
8±.4
6A
ges
18–1
9:66
.84
± 7
.37
N/A
N/A
Leo
ne e
t al.
2002
(14
)Fe
mal
e pl
ayer
s ag
ed 1
2–17
ye
ars
(13.
8 ±
1.3;
n =
16)
163
± 5
57.7
± 8
.3Su
m o
f 5
skin
fold
s re
port
ed63
.1 ±
15.
5N
/A
(con
tinu
ed)
117
Stu
dy
Po
pu
lati
on
Hei
gh
t (c
m)
Mas
s (k
g)
%B
FF
FM
(kg
)M
alin
a 19
94
(18)
Fem
ale
play
ers
aged
9–1
3 ye
ars
(n =
19)
Age
10
(n =
16)
141.
1 ±
6.6
Age
11
(n =
19)
147.
3 ±
6.6
Age
12.
0 (n
= 1
8)15
4.1
± 6
.7A
ge 1
3.1
(n =
11)
160.
3 ±
5.8
Age
10
(n =
16)
31.3
± 3
.5A
ge 1
1 (n
= 1
9)35
.9 ±
3.6
Age
12
(n =
18)
41.7
± 4
.7A
ge 1
3.1
(n =
11)
48.6
± 5
.1
N/A
N/A
Mar
tel e
t al.
2005
(20
)Pl
ayer
s fr
om lo
cal h
igh
scho
ol v
olle
ybal
l tea
m (
n =
19
); T
wo
trai
ning
gro
ups:
C
ontr
ol g
roup
(n
= 1
0; a
ge =
15
± 1
yea
rs)
Aqu
atic
trai
ning
gro
up (
n =
9;
age
= 4
±1
year
s)
Con
trol
gro
up:
167
± 9
Aqu
atic
trai
ning
gr
oup:
164
± 8
Con
trol
gro
up:
64 ±
13
Aqu
atic
trai
ning
gr
oup:
57 ±
8
N/A
N/A
Mel
rose
et
al.
2007
(2
1)
Mem
bers
of
com
petit
ive
volle
ybal
l clu
b (n
= 2
9). A
ges
= 1
2–17
yea
rs (
14.3
1 ±
1.3
7)
Age
s 12
–14:
167
± 9
.0A
ges
15–1
7:17
0 ±
7.0
Age
s 12
–14:
56.0
8 ±
8.4
7A
ges
15–1
7:62
.80
± 6
.61
Age
s 12
–14:
21.6
4 ±
4.2
6A
ges
15–1
7:20
.97
± 5
.46
3-si
te s
kinf
old
mea
sure
men
ts;
Siri
for
mul
a
Age
s 12
–14:
43.9
± 4
.41
Age
s 15
–17:
49.3
9 ±
3.6
8
Nou
tsos
et
al.
2008
(2
3)
Play
ers
aged
17.
2 ±
1.3
yea
rs
(n =
28)
175.
2 ±
6.3
64.7
± 6
.5?1
8%*
5-si
te s
kinf
old
mea
sure
men
ts55
.3 ±
4.6
Tab
le 1
(co
nti
nu
ed)
(con
tinu
ed)
118
Stu
dy
Po
pu
lati
on
Hei
gh
t (c
m)
Mas
s (k
g)
%B
FF
FM
(kg
)Pr
okop
ec
et a
l. 20
03
(25)
Cze
ch p
laye
rs a
ged
8–14
(n
= 2
38)
Eac
h ag
e gr
oup
with
pla
yers
fr
om th
e 1s
t day
of
atta
ined
ag
e to
the
last
day
bef
ore
ente
ring
the
next
age
gro
up
Age
8–9
(n
= 1
6)14
1.14
± 5
.20
Age
9–1
0 (n
= 4
5)14
4.67
± 5
.29
Age
10–
11 (
n =
58)
151.
05 ±
5.9
0A
ge 1
1–12
(n
= 4
2)15
8.94
± 6
.34
Age
12–
13 (
n =
29)
163.
74 ±
6.0
6A
ge 1
3–14
(n
= 4
8)16
9.37
± 4
.26
Age
8–9
(n
= 1
6)31
.26
± 4
.56
Age
9–1
0 (n
= 4
5)33
.71
± 4
.29
Age
10–
11 (
n =
58)
37.5
0 ±
4.9
6A
ge 1
1–12
(n
= 4
2)43
.15
± 5
.70
Age
12–
13 (
n =
29)
47.5
6 ±
6.3
3A
ge 1
3–14
(n
= 4
8)54
.21
± 4
.15
Age
8–9
(n
= 1
6)21
%A
ge 9
–10
(n =
45)
22%
Age
10–
11 (
n =
58)
23%
Age
11–
12 (
n =
42)
23%
Age
12–
13 (
n =
29)
24%
Age
13–
14 (
n =
48)
25%
4-si
te s
kinf
old
mea
sure
men
ts
Age
8–9
(n
= 1
6)24
.7*
Age
9–1
0 (n
= 4
5)26
.3*
Age
10–
11 (
n =
58)
28.9
*A
ge 1
1–12
(n
= 4
2)33
.2*
Age
12–
13 (
n =
29)
36.1
*A
ge 1
3–14
(n
= 4
8)40
.7*
Rou
sano
-gl
ou e
t al.
2008
(26
)
Elit
e pl
ayer
s (n
= 2
1); A
ge=
16
.3±
.8 y
ears
170.
0 ±
9.0
61.5
± 7
.1N
/AN
/A
Stam
m e
t al.
2002
(29
)13
–16
year
-old
pla
yers
pla
y-in
g at
the
unde
r 16
cha
mpi
on-
ship
(n
= 4
6);
Tann
er s
tage
s II
I-IV
Age
13
(n =
10)
163.
19 ±
7.2
3A
ge 1
4 (n
= 1
4)16
4.08
± 4
.41
Age
15
(n =
12)
168.
43 ±
5.3
0A
ge 1
6 (n
= 1
0)16
9.60
± 5
.50
Age
13
(n =
10)
54
.48
± 1
3.34
Age
14
(n =
14)
52.5
5 ±
6.6
5A
ge 1
5 (n
= 1
2)58
.26
± 4
.20
Age
16
(n =
10)
60.4
6 ±
9.4
7
Onl
y in
divi
dual
ski
nfol
d m
ea-
sure
men
ts w
ere
repo
rted
N/A
Tab
le 1
(co
nti
nu
ed)
(con
tinu
ed)
119
Stu
dy
Po
pu
lati
on
Hei
gh
t (c
m)
Mas
s (k
g)
%B
FF
FM
(kg
)St
amm
et a
l. 20
03 (
36)
13–1
6 ye
ar-o
ld p
laye
rs p
ar-
ticip
atin
g in
you
ng f
emal
e vo
lleyb
alle
rs’
cham
pion
ship
s(n
= 3
2)Ta
nner
sta
ges
III-
IV
Age
13
(n =
5)
165.
46±
8.5
7A
ge 1
4 (n
= 9
)16
4.20
± 4
.89
Age
15
(n =
10)
168.
03 ±
5.5
5A
ge 1
6 (n
= 8
)17
0.74
± 1
.15
Age
13
(n =
5)
56.9
3 ±
17.
13A
ge 1
4 (n
= 9
)51
.76
± 6
.69
Age
15
(n =
10)
58.2
8 ±
4.5
7A
ge 1
6 (n
= 8
)60
.45±
.16
N/A
N/A
Stam
m e
t al.
2004
(30
)Pl
ayer
s fr
om e
ight
mos
t suc
-ce
ssfu
l vol
leyb
all t
eam
s of
C
lass
C w
ho p
artic
ipat
ed in
E
ston
ian
cham
pion
ship
s (n
=
77; A
ges
= 1
3–15
yea
rs)
168.
47 ±
6.2
Ran
ge:
150.
7–19
3.4
58.0
5 ±
7.4
Ran
ge:
39.9
–76.
0
N/A
N/A
Stam
m e
t al.
2005
(31
)Pl
ayer
s fr
om 1
2 te
ams
(age
s =
14–
17 y
ears
) w
ho p
artic
i-pa
ted
at G
irl’s
You
th E
uro-
pean
Vol
leyb
all C
ham
pion
-sh
ip (
n =
144
)
182.
19 ±
5.8
865
.94
± 7
.69
N/A
N/A
Thi
ssen
-M
iller
et a
l. (3
9)
Hig
h sc
hool
vol
leyb
all p
lay-
ers
(n =
50)
Fres
hman
team
(n
= 1
2);
Age
= 1
4.12
±.6
1 ye
ars
Juni
or v
arsi
ty (
n =
14;
Age
=
15.6
5±.6
3 ye
ars
Var
sity
team
(n
= 2
4; A
ge=
16
.04±
.64
year
s
Fres
hman
:16
7.1
± 6
.7Ju
nior
var
sity
:16
7.0
± 7
.4V
arsi
ty:
168.
7 ±
7.8
Fres
hman
:58
.8 ±
6.4
Juni
or v
arsi
ty:
50.7
± 8
.0V
arsi
ty:
58.6
± 1
0.5
Fres
hman
:18
.1 ±
2.6
Juni
or v
arsi
ty:
19.6
± 3
.4V
arsi
ty:
17.2
± 3
.85-
site
ski
nfol
d m
easu
rem
ents
; E
quat
ions
for
chi
ldre
n an
d yo
ung
wom
en
Fres
hman
:48
.2*
Juni
or40
.8*
Var
sity
:48
.5*
Tab
le 1
(co
nti
nu
ed)
(con
tinu
ed)
120
Stu
dy
Po
pu
lati
on
Hei
gh
t (c
m)
Mas
s (k
g)
%B
FF
FM
(kg
)T
suna
wak
e et
al.
2003
(4
1)
Play
ers
from
a te
am th
at w
on
inte
rhig
h sc
hool
mee
tings
in
Japa
n. (
n =
12)
; Age
= 1
7.4
±
.73
year
s
168.
7 ±
5.8
959
.7 ±
5.7
318
.4 ±
3.2
9E
ight
-site
ski
nfol
d m
easu
re-
men
ts a
nd u
nder
wat
er w
eigh
-in
g
48.6
± 4
.53
Viv
iani
and
B
aldi
n 19
93
(43)
Juni
or p
laye
rs (
n =
25)
; Age
=
13–1
8 ye
ars
(14.
4 ±
1.2
)16
3.3
± 5
.756
.4 ±
8.8
21.3
± 4
.6Sk
info
ld m
easu
rem
ents
; Sir
i eq
uatio
ns
44.4
*
Not
e. %
BF
= p
erce
nt b
ody
fat;
FFM
= f
at-f
ree
mas
s; *
Dat
a no
t pro
vide
d in
text
, cal
cula
ted
by a
utho
rs.
Tab
le 1
(co
nti
nu
ed)
121
Tab
le 2
A
Su
mm
ary
of
the
Phy
sica
l Ch
arac
teri
stic
s o
f M
ale
Pla
yers
(M
ean
s ±
SD
)
Stu
dyPo
pula
tion
Hei
ght (
cm)
Mas
s (k
g)%
BF
FFM
(kg)
Dun
can
et a
l. 20
06 (
5)Ju
nior
pla
yers
(n
= 2
5); A
ge=
16–
19
year
s (1
7.5±
.5)
Sette
rs:
191
± 5
.0H
itter
s:19
3 ±
4.5
Cen
ters
:18
7 ±
3.6
Opp
osite
s:19
0 ±
5.9
Sette
rs:
71.2
± 9
.3H
itter
s:77
.9 ±
8.4
Cen
ters
:77
.6 ±
5.9
Opp
osite
s:71
.3 ±
9.2
Sette
rs:
12.9
± 3
.4H
itter
s:12
.5 ±
2.4
Cen
ters
:11
.5 ±
2.2
Opp
osite
s:11
.8 ±
3.5
4-si
te s
kinf
old
mea
sure
men
ts
Sette
rs:
43.4
± 5
.2H
itter
s:50
.9 ±
7.1
Cen
ters
:49
.6 ±
4.4
Opp
osite
s:44
.5 ±
5.2
Gab
bett
et a
l. 20
06 (
7)Ju
nior
pla
yers
(n
= 2
6) S
chol
ar-
ship
hol
ders
with
in th
e Q
ueen
slan
d A
cade
my
of S
port
Tal
ent S
earc
h vo
lleyb
all p
rogr
am. A
ge=
15.
5±.2
ye
ars
182.
2 ±
1.5
72.3
± 2
.5Su
m o
f 7
skin
fold
s re
port
ed.
Pret
rain
ing:
88.
7 ±
5.7
mm
Post
trai
ning
: 86.
8 ±
5.7
mm
N/A
Gab
bett
et a
l. 20
07 (
8)Ju
nior
pla
yers
fro
m B
risb
ane
met
ro-
polit
an a
rea
(n =
28)
;A
ge =
15.
5 ±
1.0
yea
rsTe
sted
for
bei
ng a
ccep
ted
to th
e Q
ueen
slan
d A
cade
my
of S
port
Ta
lent
Sea
rch
volle
ybal
l pro
gram
Sele
cted
for
pro
-gr
am:
184.
0 ±
8.0
Not
sel
ecte
d:18
4.0
± 7
.0
Sele
cted
for
pro
-gr
am:
71.1
±.6
Not
sel
ecte
d:77
.3 ±
13.
6
Sum
of
7 sk
info
lds
repo
rted
.Se
lect
ed f
or p
rogr
am:
83.1
± 2
3.9
mm
Not
sel
ecte
d:98
.7 ±
34.
7 m
m
N/A
Gab
bett
and
Geo
rgie
ff 2
007
(6)
Juni
or v
olle
ybal
l pla
yers
(n
= 5
7)Sc
hola
rshi
p ho
lder
s w
ithin
the
Que
ensl
and
Aca
dem
y of
Spo
rt
Tale
nt S
earc
h vo
lleyb
all p
rogr
am
(age
= 1
5.6±
.1 y
ears
)
Nat
iona
l lev
el:
195.
2 ±
2.4
Stat
e le
vel:
190.
0 ±
1.2
Nov
ice:
187.
3±.5
Nat
iona
l lev
el:
80.2
± 1
.9St
ate
leve
l:81
.8 ±
1.7
Nov
ice:
80.9
± 2
.5
Sum
of
7 sk
info
lds
repo
rted
.N
atio
nal:
57.8
± 3
.0 m
mSt
ate:
50.5
± 1
.0 m
mN
ovic
e:88
.4 ±
6.2
N/A (c
onti
nued
)
122
Stu
dyPo
pula
tion
Hei
ght (
cm)
Mas
s (k
g)%
BF
FFM
(kg)
Kas
abal
is e
t al.
2005
(12
)Pl
ayer
s ag
ed 1
0–11
(n
= 2
1) a
nd
15–1
6 (n
= 1
8)A
ges
10–1
1:15
0.5
± 5
.9A
ges
15–1
6:18
9.6
± 5
.6
Age
s 10
–11:
42.0
± 6
.0A
ges
15–1
6:77
.0 ±
6.6
Age
s 10
–11:
17.3
± 2
.4A
ges
15–1
6:15
.1 ±
2.2
No
data
on
%B
F m
easu
rem
ent
Age
s 10
–11:
34.7
*A
ges
15–1
6:65
.4 *
Lid
or e
t al.
2007
(16
)M
embe
rs o
f a
cohe
rent
team
that
co
mpe
ted
in th
e 2n
d Is
rael
i nat
iona
l le
ague
(n
= 1
5). A
ge=
16.
4±.8
2 ye
ars
Star
ters
:18
8 ±
2.9
Non
star
ters
:18
6.7
± 4
.6
Star
ters
:75
.6 ±
5.9
Non
star
ters
:71
.5 ±
8
N/A
N/A
Mal
ates
ta e
t al.
2003
(17
)Pl
ayer
s of
reg
iona
l lev
el I
talia
n V
olle
ybal
l Fed
erat
ion
Lea
gue
(n =
12
; age
= 1
7.2±
.3
181.
8±.3
73.0
± 4
.2N
/AN
/A
Nac
zk e
t al.
2006
(22
)Pl
ayer
s ag
ed 1
5 ye
ars
(n =
15)
183.
5 ±
6.5
70.5
± 9
.7N
/AN
/A
Stag
anel
li et
al
. (37
)U
nder
-19
mal
e B
razi
lian
play
ers
(n
= 1
1; a
ge =
18.
0±.5
yea
rs)
Test
ing
on fi
rst w
eek
of tr
aini
ng,
nint
h w
eek
of tr
aini
ng, 1
8th
wee
k of
tr
aini
ng
198.
7 ±
5.5
(no
diff
eren
ces
betw
een
test
ing
times
)
Firs
t wee
k:85
.8 ±
6.0
Nin
th w
eek:
88.4
± 6
.418
th w
eek:
87.6
± 5
.6
Firs
t wee
k:8.
3±.9
Nin
th w
eek:
8.7
± 1
.018
th w
eek:
8.9
± 0
.93-
site
ski
nfol
d m
easu
rem
ents
Firs
t wee
k:78
.6 ±
5.1
Nin
th w
eek:
80.6
± 5
.518
th w
eek:
79.7
± 4
.9
Viv
iani
200
4 (4
2)Pl
ayer
s (n
= 2
5) a
ged
13–1
8 (1
5.5
±
1.2)
yea
rs17
8.0
± 7
.466
.6 ±
8.5
11.8
± 6
.0Sk
info
ld m
easu
rem
ents
; Sir
i eq
uatio
ns
58.7
5
Not
e. %
BF
= p
erce
nt b
ody
fat;
FFM
= f
at-f
ree
mas
s; *
Dat
a no
t pro
vide
d in
text
, cal
cula
ted
by a
utho
rs.
Tab
le 2
(co
nti
nu
ed)
Attributes of Adolescent Volleyball Players 123
girls were the most proficient at blocking. Another study (30) found similar results: the most successful players at attack, block, and reception were taller, heavier, and had larger circumference dimensions than the less successful players. In addition, taller and heavier girls comprised 25% of the players in teams ranked 1–6 in the Youth European Championship compared with only 12.5% in teams ranked 7–12 in the Championship (31).
One study (6) suggested that national and state-level players in Australia had lower skinfolds measurements than novice players. In contrast, no differences in height, body mass, or percent body fat were found between starters and nonstarters of a high school team (39).
Conflicting results were observed when volleyball players were compared with athletes of other sports. While no anthropometric differences were found between basketball and volleyball players in one study (41), another study (14) reported that volleyball players tended to be the tallest and heaviest of skaters, swimmers, and tennis players (aged approximately 14 years). Similarly, volleyball players were taller than handball players (age = 17.8 ± 1.2), while no differences were seen in body mass and body fat (23).
Male Players
Height, body mass, and percent fat values ranged from 150.5 ± 5.9 cm, 42.0 ± 6.0 kg, and 17.3±.4%, respectively, in a group of 10–11 year-old players (12) to 198.7 ± 5.5 cm, 88.4 ± 6.4 kg, and 8.3±.9%, respectively, in a group of under-19 Brazilian elite players (37). In comparison, the average height and body mass for 16 year-old American males are 175.3 cm and 69.0 kg, respectively (11).
In one study (12), while no differences in height and body mass were found between volleyball players and nonathletes in the 10–11 age-group, 15–16 year-old players were reported to be taller and heavier than nonathletes. These results are in line with findings from another study (42) reporting that 14–15 year-old Italian amateur volleyball players were taller and heavier than sedentary Italians of a similar age.
Three studies examined the relationship between the proficiency of players and anthropometric measurements (6,8,16). While two studies failed to find dif-ferences in anthropometric measurements based on proficiency level (8,16), one study (6) indicated that national players were taller than state and novice players. Another study (5) found no differences in anthropometric measurements between centers, hitters, opposites, and setters in players aged 16–19 years. Nevertheless, anthropometric data cannot be completely disregarded, since successful players require a combination of well-developed motor, physiological, and anthropometric characteristics to achieve a high level of proficiency (8).
Different types of physical training did not seem to affect body mass and per-cent fat in adolescent volleyball players. In one observational study that followed under-19 elite Brazilian players through 18 weeks of training (37), and in another experimental study assessing an eight-week conditioning program (7), training did not influence body mass or percent fat. In the latter study (7) the main objective of the training program was to improve a number of volleyball skills rather than to enhance the physiological performance. In the former study (37), it was suggested that the elite players began the training in such a physical condition (8–9% body
124 Lidor and Ziv
fat) that the applied loads could not have induced significant adaptations over an 18-week period.
Physiological Attributes
Comparisons of physiological measurements between studies should be made with caution, as different testing protocols can lead to different results. For example, VO2max values differ when they are measured on a cycle ergometer or treadmill than when estimated from a field test.
Aerobic Capacity
Female Players. Only five studies examining VO2max were found. One study (20) reported estimated VO2max values of 42 mlO2·kg¯1·min¯1, based on a submaximal cycle ergometry test in nineteen 14–15 year-old girls from a local high-school volleyball team. Another study (6) estimated VO2max values of 37.0±.8, 39.3±.7, and 41.2±.9 mlO2·kg¯1·min¯1 in novice, state-, and national-level players, respectively (approximate age = 15 years old). Estimation was based on a multistage field fitness test. VO2max values, as measured on a maximal treadmill test, were 46.6 ± 2.9 and 56.7 ± 4.17 mlO2·kg¯1·min¯1 in high-school volleyball and basketball players in Japan (age = 17.5 years), respectively (41). A study that compared tennis players, skaters, swimmers, and volleyball play-ers (ages = 12–17) found similar VO2max values in all groups (14). VO2max of the volleyball players was 48.9 ± 3.6 mlO2·kg¯1·min¯1. Lastly, V02max values of 46.3–49.2 mlO2·kg¯1·min¯1 were estimated from a 1000-m run over a training period of eight months in 14–15 year-old players who were between the 4th and 5th Tanner stages (1).
Rowland (27) reported that VO2max relative to body weight does not increase and actually decreases as girls mature. Hence, differences in VO2max are probably due to factors such as genetics, selection, and training rather than the effects of maturation.
Male Players. Four studies estimated VO2max values using a multistage fitness test in which players ran back and forth along a 20-m track, keeping in time by a series of signals. In one study (6), VO2max values were 41.2 ± 1.2, 49.8±.1, and 50.6 ± 1.4 mlO2·kg¯1·min¯1 for novice, state, and national players, respectively (approximate age = 15 years old). In another study (8), VO2max values of 43.0 ± 6.1 and 41.4 ± 3.5 mlO2·kg¯1·min¯1 were found in junior players (age = 15.5 ± 1.0 years) who were selected and nonselected, respectively, to a volleyball talent search program. A third study estimated VO2max values of more mature setters, hitters, centers, and opposites (age = 17.5±.5 years) and found values of 46.9 ± 4.9, 51.1 ± 3.7, 50.4 ± 3.7, and 48.3 ± 6.7 mlO2·kg¯1·min¯1, respectively (5).
Lastly, Gabbett et al. (7), found no significant differences in estimated VO2max values of talent-identified junior players (age = 15.5±.2 years) before (40.8 ± 1.1 mlO2·kg¯1·min¯1) and after (43.2 ± 1.1 mlO2·kg¯1·min¯1) an 8-week skill-based train-ing program. Since VO2max relative to body weight remains stable throughout the growing years in boys (27), the described differences in VO2max are probably due to genetics, selection, and training rather than the effects of maturation.
Attributes of Adolescent Volleyball Players 125
Strength and PowerFemale Players. In one study (21), VJ (with arm swing allowed) values of 12–14 year-old players were 33.22 ± 6.07 cm and those of 15–17 year-old players were 37.42 ± 5.74 cm. In another study (13), players were ranked according to their playing efficiency. The highest-ranked players aged 14–15 years demonstrated higher values for standing VJ (46.09 cm) and VJ with approach (50.09) than the lowest ranked players (32.66 and 35.12, respectively). Both jumping tests were conducted with arm swing allowed. Similar results were indicated in players aged 16–17 years. For comparison, the 90th percentile rank for 15–16 year-old females is 47.0 cm (11), suggesting that the highest-ranked players have excellent leap-ing abilities. The importance of jumping ability was revealed in one study (31) reporting that players from teams that were ranked 1–6 had better jumping abilities than players in teams ranked 7–12 in a European Youth Volleyball Championship.
In a study of 50 high-school players (39) in which the VJ protocol allowed arm swing, varsity players had significantly higher VJ values (43.6 ± 5.6 cm) compared with junior varsity (35.6 ± 5.9 cm) and freshman (37.8 ± 7.1 cm) players. However, when VJ values were converted to power, the differences between the varsity players and the freshman players were not significant (836.9 ± 79.9 and 782.2 ± 52.7 W, respectively). Similar values were reported for national (45.7± .6 cm), state (41.5 ± .9 cm), and novice (35.9 ± 1.4 cm; 6).
The effect of aquatic plyometric training (APT) on VJ was examined in 19 players (age = 15 ± 1 years; 20). The APT exercises included power skips, spike approaches, bounding, continuous jumping, squat jumps, and depth jumps. VJ pro-tocol included a jump with arm swing allowed. VJ values improved by 11% in the APT group compared with 4% in a control group participating in regular training. This study suggested that APT could provide comparable benefits to land-based plyometric training, with a lower risk of muscle soreness and/or overtraining (20).
With the exception of the VJ values reported by Katic et al. (13), and those found in Gabbett and Georgieff’s (6) study, the VJ values of adolescent volleyball players were reported to be similar to those of the population at large: the 50th percentile rank for VJ is 36.8 cm in 13–14 year-old females, and 39.4 cm in 15–16 year-old females (13). These observations can be explained by the fact that most studies examined amateur players rather than highly-talented players.
Male Players. One study (8) found higher values for VJ and spike jump (arm swing allowed in both jumps) in players aged 15.5 ± 1.0 years who were selected to a volleyball talent search program (46.0 ± 11.2 and 50.7 ± 13.6 cm, respectively) compared with those not selected (41.9 ± 10.9 and 47.5 ± 12.8 cm, respectively). Another study (6) found higher VJ and spike jump values (arm swing allowed) in novice (48.5 ± 1.0, 53.6 ± 1.1 cm), state (63.3 ± 3.2, 71.9 ± 2.9 cm), and national (54.6 ± 2.2, 65.8 ± 3.7 cm) players (approximate age = 15 years). In older adoles-cents (age = 16–19 years) VJ values were: setters (42.8 ± 8.1 cm), hitters (49.0 ± 5.7 cm), centers (47.2 ± 5.1 cm), and opposites (42.0 ± 5.1 cm; 5).
Standing VJ and VJ with approach were measured six times over a 15-month period in 15 players (age = 16.4 ±.82 years; 16). Values of both jumps improved over time. Starters had higher values of VJ with approach than those of nonstart-ers in the last testing session of the 15-month period (71 ± 5.3 vs. 66.1 ± 8.3 cm, respectively).
126 Lidor and Ziv
The relationship between values of VJ and power measured by the Wingate Anaerobic Test (WanT) were examined in 10–11 and 15–16 year-old players (12). Significant relationships were found between VJ and peak power (r = .86, p < .001), VJ and average power (r = .86, p < .001), and VJ and the lowest power (r = .56, p < .01). These relationships indicate that a VJ jump test can provide valid information on players’ anaerobic power (12). Muscle power is of importance to volleyball players; young players (age = 15) appear to have higher power values than nonathletes (22).
Since VJ is of importance to volleyball players, improving this skill can enhance game performance. Two studies examined the effects of training on VJ performances (17,37). In one study (37), the jumping performance of 11 players of the Brazilian under-19 team (age = 18.0 ± .5 years) improved over an 18-week training period composed of weight training, endurance training, jumping training, anaerobic capac-ity training, and stretching training. Five types of VJ tests were performed: squat jump (SJ), counter movement jump (CMJ), jump anaerobic resistance test (JAR; 15 s of continuous jumping), attack jump (ATJ), and block jump (BLJ). In the SJ, CMJ, and JAR, hands were kept on the waist throughout the tests. The values of ATJ and BLJ increased the most (by approximately 10 cm from baseline to Week 9). It was suggested that ATJ and BLJ may be better suited than SJ and CMJ for testing training effects on jumping performance in volleyball.
In the second study (17), an electromyostimulation (EMS) training consist-ing of three weekly sessions over the first 30 days of a 40-day training program improved SJ, CMJ, and 15-s consecutive CMJ by 5–6% by day 40 in 12 regional-level players in the Italian Volleyball Federation League. Hands were kept on the waist throughout the tests. It was suggested that EMS training can be useful in increasing VJ in volleyball players.
Agility and Speed
Female Players. In one study (21), no significant differences in agility and speed were found between players of two age groups (12–14 and 15–17 years). In another study, high-school varsity team players (age = 16.04 ± .64 years) showed signifi-cantly greater agility than junior varsity (age = 15.65 ± .63 years) and freshman (age = 14.12 ± .61 years) team players (39). The agility test required the players to rapidly change directions through a symmetrical maze of cones. Agility and speed performances were also better in national-level players compared with state-level and novice players in Australia (age = 15.6 ± .1 years) (6).
In another study (36), agility and speed as measured by a shuttle zig-zag run were found to be related to the efficiency of ball reception (partial correla-tion coefficient = -.58). Ball reception efficiency was assessed on the basis of at least four games, by recording a grade from 1 (excellent) to 5 (failed) during each game.
Lastly, 197 players (age = 14–17 years) were ranked based on their individual quality within the team as well as based on the quality of the team as a whole (13). A series of agility and speed tests were performed by the players. Data were presented separately for the 14–15 group and the 16–17 group. In both groups, performance in the tests improved from the lowest-ranking to the highest-ranking players.
Attributes of Adolescent Volleyball Players 127
Male Players. In one study (8), no significant differences in a 5-m sprint test, a 10-m sprint test, and an agility test were indicated in 28 players (age = 15.5 ± 1.0 years) who were trying out for a volleyball academy. Similarly, in a 15-month follow-up of 15 players (age = 16.4 ± .82 years; 16), no differences were observed between starters and nonstarters. However, improvements were found in a 10-m sprint test, a 20-m sprint test, and an agility test over time.
While no differences in sprint times were found between national, state, and novice players in Australia (age = 15.6±.1; 6), national-level players (9.9 ± .17 s) and state-level players (9.76 ± .15) performed better on an agility test compared with novice players (10.47 ± .18). Improved performance of national-level players may reflect the higher training and competition intensity at that level (6).
Only one study that examined agility and speed before and after a training program was found (7). Twenty-six junior players (age = 15.5 ± .2 years) underwent agility and speed tests before and after an 8-week skill-based training program designed to develop volleyball fundamentals such as blocking, game tactics, passing, positioning, setting, serving, and spiking. Speed and agility improved significantly from the pre- to posttraining phases. These improvements are noteworthy since the training program was not designed to improve physiological performance per se. It was proposed that the improved agility may have been due to increased running speed as well as improved perception and decision-making skills.
Volleyball Skills
Female Players. In one study, serving and spiking velocity were tested in two groups of players (ages = 12–14 and 15–17 years) of a volleyball club (21). While no significant differences in spiking velocity were found between groups, serving velocity was higher in the 15–17 group (17.3 ± 1.61 m·s¯1) than in the 12–14 group (14.8 ± 2.63 m·s¯1). Serving velocity had a moderate correlation with age (r = .71) while spiking velocity correlated weakly with age (r = .32). In another study of 77 players (age = 13–15 years; 30), performances of various basic fundamentals of the game (e.g., attacking and blocking) were recorded during actual volleyball games. Recording of game performance was performed using a specialized com-puter program (33), used also in other studies (e.g., 28,32,35). It was found that the players performing best in attack, block, and reception were also the taller and heavier among the players who took part in the study.
In a study of 50 high-school players (39), the varsity team players (age = 16.04 ± .64 years) outperformed the junior varsity (age = 15.65 ± .63) and the freshman team players (age = 14.12 ± .61) in four volleyball skills—bump-set, forearm pass, overhead volley, and wall spike. In addition, starters (age = 15.3 ± 1.0 years) outperformed the nonstarters (age = 14.8 ± 1.1) in all four skills.
In another study (9), six volleyball skills (blocking, field defense, serving reception, serving, setting, and spiking) were assessed in 246 players who were divided into four age groups: 12–13, 14–15, 16–17, and 18–19 years. A significant improvement in serving, setting, and spiking was indicated in the 14–15 and the 16–17 groups. Significant improvement in blocking and serving reception was observed in the 16–17 and the 18–19 groups. The best predictor of playing quality was serving in the 12–13 group, blocking and spiking in the 14–15 group, spiking and blocking in the 16–17 group, and field defense in the 18–19 group. It appears
128 Lidor and Ziv
that the easier techniques to master are learned first, while the more complex tech-niques take longer to master (9).
In a similar study that assessed the same skills (13), 14–15 and 16–17 year-old players were ranked based on their quality within the team as well as on the quality of the team as a whole. The highest ranked players in both age groups demonstrated better performance in all six skills assessed in the study compared with the lowest ranked players. In addition, the players aged 16–17 years achieved better results than the players aged 14–15 years in a series of motor tests (e.g., double-hand tap-ping, foot tapping, foot tapping against the wall, and hand tapping). The differences in volleyball performance in this study were thought to be due to the process of selection rather than the training process per se (13). In fact, another study using a factor analysis (10) suggested that performance was predominantly determined by longitudinal skeleton dimensions (mostly height) and muscle tissue.
Another study (34) examined the relationships among 21 computerized tests of psycho-physiological properties (e.g., auditory and visual reaction time and perception of speed of a moving object) and players’ efficiency in basic fundamen-tals of the game in 32 high-level players (age = 13–16 years). The best predicted fundamentals were blocking (98%), attacking (80%), and feinting (60%). It was suggested that psycho-physiological tests have good prospects in the understand-ing of volleyball, and these tests should be used in assessing individual player’s characteristics.
Male Players. One study (8) examined the accuracy and technique of four volleyball skills (passing, serving, setting, and spiking) in junior players (age = 15.5 ± 1.0 years) who were trying out for a volleyball academy. Players who were ultimately selected for the program were better at passing accuracy, as well as at spiking, serving, and passing technique. However, passing technique and serving technique were not found to be good predictors for talent identification in volleyball. It was indicated in this study that selected skill tests can discriminate between junior players selected to a talent-identified program and those who were not selected (8).
In another study (15), serving accuracy in rested conditions and after physical exertion conditions were similar in elite and near-elite adolescent players. Elite players were members of an adult Division 2 team in Israel (age = 16.4 ± .82 years) and near-elite players were members of a high-school team competing in the Divi-sion 1 high-school league (age = 16.3 ± .53 years).
Finally, in another study (7), four volleyball skills—passing, serving, setting, and spiking—were tested after an 8-week skill-based training program designed to develop technique and accuracy as well as game tactics and positional skills in 26 talent-identified junior players (age = 15.5 ± .2 years). After eight weeks, accuracy significantly improved in spiking (+76%), setting (+335%), and passing (+40%), while serving accuracy showed only a trend for improvement (+15%). Training also induced a significant improvement in technique in passing (+29%) and spiking (+24%). When summing up the results of all the tests, a general improvement of 21% in technique and 117% in accuracy can be determined. The large improve-ment in accuracy most likely reflected the poor performance of the players before training. It is assumed that such a training program would not induce such great improvement in more proficient players.
Attributes of Adolescent Volleyball Players 129
Physical Characteristics and Physiological Attributes—The Existing Interrelationships
Four key points can summarize the interrelationships between the physical charac-teristics and physiological attributes discussed in this review:
a. In female adolescent players, anthropometric data are correlated to volleyball skills’ proficiency and to game performance. In general, a taller and heavier body is related to better game proficiency. Unfortunately, the scarce data in male players project conflicting results regarding the relationships between anthropometrics and game proficiency.
b. In both male and female players, VJ is higher in highly skilled players than players of lesser abilities. In addition, VJ performance appears to increase as children grow older. The combination of a tall stature and superb VJ abilities seems to differentiate elite players from players of lesser skills.
c. While there is not enough evidence to establish a relationship between agility and speed and player performance in male players, it appears that agility and speed are related to players’ skill in female players.
d. Basic volleyball skills, such as blocking, spiking, and feinting, are related to players’ success in both male and female players. In addition, these skills develop as children grow older, with the more complex skills developing at later ages rather than the more basic skills.
While data in male adolescent players are generally lacking and those that do exist are somewhat conflicting, these four key points suggest that the successful adolescent volleyball player is tall with a relatively high body mass. In addition, he or she has excellent leaping abilities and is fast and agile. These players perform basic volleyball skills better than their less skilled peers. Lastly, as these players grow older they seem to improve their performances in game skills and physio-logical abilities.
What Can We Learn From the Reviewed Studies?—Six Methodological Concerns
Analyses of the designs of the reviewed studies revealed a number of methodologi-cal concerns. Before implementing the findings from these studies, the following concerns should be taken into account by both researchers and practitioners:
a. The lack of information on the exact chronological age of the players participated in the reviewed studies. In most studies, the information on how the mean average of the age of the players was calculated is missing. For example, if the age of one of the adolescent players is 14 years, does it refer to his or her birth date (e.g., 14.2, 14.4), or to another value reflecting six months before and after his or her birth date (e.g., 13.50–14.49)? More precise information on the chronological age of the players in the reviewed studies can allow for better comparisons among studies.
130 Lidor and Ziv
b. The lack of information on the maturational stage of the players participating in the reviewed studies. Maturation affects anthropometrics, body composi-tion, and physiological variables (19). In most of the studies, information on maturational age (e.g., skeletal age, secondary sex characteristics, and age at peak height velocity) was not provided. While older adolescents, especially girls, are usually already mature, maturity status is important in younger adolescents. In comparison, forming maturity groups of similar chronological ages (while not without limitations) can be useful in explain-ing variations in performance (19). Preferably, maturational assessment should be clinically assessed rather than self-assessed by the players.
c. The lack of longitudinal studies. Most of the studies reviewed in this article lack a longitudinal approach. In only one study (16) was a longitudinal approach adopted, enabling the researchers to collect data throughout a 15-month training program. In a longitudinal study, a group of athletes was observed over a long period of time (40), during which various dependent variables were collected, analyzed, and interpreted. The conduction of longitudinal studies allows the researcher to obtain relevant information on developmental stages of the athlete. In the case of adolescent volleyball players, it would be interesting to examine their physical characteristics and physiological attributes over a number of years of training, as well as the contribution of the training to these characteristics and attributes. In addi-tion, the use of the longitudinal approach can provide relevant information on developmental stages of female and male players not only at different ages but also at different skill levels. Adopting a longitudinal approach can help both researchers and practitioners increase their understanding of the interrelationships among the physical characteristics, physiological attributes, and skill levels in adolescent players across a number of years of professional development. In addition, this approach can help in the understanding of behavioral changes that occur with age in the young play-ers as well as of other developmental factors, among them the timing and tempo of the growth spurt and sexual maturation (19). Although it can be difficult for researchers to deal with methodological issues such as player dropout and injury while collecting data in a longitudinal process, it is recommended that this approach be used to obtain the relevant information on the multiyear developmental aspects of adolescent players.
d. The lack of experimental studies. Only a few experimental studies were conducted on adolescent volleyball players (e.g., 7,20). Although the sample size of the elite adolescent volleyball players taking part in experimental studies can be small, due to the size of the team (e.g., 15–17 players; see 16), those studies are of importance in examining the contribution of envi-ronmental factors to the development of adolescent volleyball players. By conducting experimental studies, researchers and practitioners can increase their theoretical and practical knowledge of the actual contribution of dif-ferent training programs (e.g., strength and conditioning training, specific skills programs), testing devices (e.g., agility and speed tests, power and strength tests), or protocols of physical tests to the achievement of adolescent volleyball players. Experimental studies should examine the effectiveness of learning/training environments on task-specific volleyball skills. Among
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the research questions that can be asked in these studies are: What is the optimal age to start developing VJ performance in adolescent players? At what age should players practice according to their playing position? What are the most effective techniques for improving agility in adolescent play-ers? And, do agility techniques match the needs of both female and male players? It is assumed that if answers are provided for these questions, coaches will be able to develop effective training programs that match the individual needs of their players.
e. The relative lack of data on volleyball-specific skills. Only a few studies examined the development of volleyball-specific skills such as passing, serving, setting, and spiking and their association with the physical cha-racteristics and physiological attributes of adolescent players (e.g., 9,31). Obtaining relevant information on the existing interrelationships between the physical characteristics, physiological attributes, and skill level in ado-lescent players should help volleyball coaches develop effective practice environments for the benefits of their players. This might also help them predict the future volleyball performance of their players.
f. The lack of studies with data on players’ performances during actual games. In only a few of the reviewed studies were data collected on physi-cal and physiological performances of players during actual games (e.g., 9,24,34). To plan effective volleyball training programs and strength and conditioning programs for adolescent volleyball players, more information should be gathered on the actions players perform during an actual game. A systematic analysis of the main actions demonstrated by the players during the game should be made, and then, based on this analysis, field observa-tions should be conducted on players of different skill levels as well as on players playing different positions. It is suggested that game analyses performed on other ball games (e.g., soccer; 38) be adapted for volleyball. For example, quantifying the actions performed by volleyball players in both the defensive and offensive aspects of the game should be helpful for the volleyball coach in planning their training programs effectively.
Practical Recommendations for Volleyball Coaches and Strength and Conditioning Coaches
Based on the reviewed studies, as well as on the six methodological concerns dis-cussed in our review, four practical tips for volleyball and strength and conditioning coaches are provided, as follows.
First, it is recommended that the tests most appropriate for assessing abilities in the players should be carefully selected. It is also recommended that the same test be used for comparing achievements in a specific ability among the volley-ball players. As reported in this review, there are a large number of different tests assessing physiological attributes in adolescent volleyball players, such as agility and speed, and strength and power that can yield different values.
Second, volleyball training programs should be planned for the players accord-ing to their playing positions. Centers, hitters, opposites, and setters have different physical characteristics and physiological attributes. Ultimately, volleyball and
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strength and conditioning coaches should plan their training programs according to the unique characteristics of each player.
Third, to develop appropriate training programs aimed at improving skill as well as the conditioning and strength in adolescent players, actions performed by the players during actual games should be also considered, among them blocking, serving, and spiking.
Fourth, volleyball coaches should adopt a cautious approach when attempting to predict the success of players based on their physical characteristics and on the results obtained from physiological tests. Although a number of actions such as the standing vertical jump and the vertical jump with approach were found to be good performance predictors, there are many other physiological and psychological factors that are associated with achievement in volleyball.
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