International  Journal  of
Environmental Research
and Public Health
Article
A Comparative Study on the Performance Proﬁle of
Under-17 and Under-19 Handball Players Trained in
the Sports School System
Tomasz Gabrys 1
, Arkadiusz Stanula 2,*
, Subir Gupta 3, Urszula Szmatlan-Gabrys 4,
Daniela Benešová 1
, Łukasz Wicha 5 and Jakub Baron 2
1
Department of Physical Education and Sport Science, Faculty of Pedagogy, University of West Bohemia,
301 00 Pilsen, Czech Republic; tomaszek1960@o2.pl (T.G.); dbenesov@ktv.zcu.cz (D.B.)
2
Institute of Sport Science, The Jerzy Kukuczka Academy of Physical Education, Mikołowska 72A,
40-065 Katowice, Poland; j.baron@awf.katowice.pl
3
Faculty of Medical Sciences, University of West Indies, 11000 Cave Hill, Barbados;
subir.gupta@cavehill.uwi.edu
4
Faculty of Rehabilitation, Department of Anatomy, University of Physical Education,
31-571 Krakow, Poland; urszula.szmatlan@awf.krakow.pl
5
Polish Handball Federation, Puławska 300 A, 02-819 Warszawa, Poland; lukaszwicha85@gmail.com
*
Correspondence: a.stanula@awf.katowice.pl; Tel.: +48 207-53-33
Received: 26 September 2020; Accepted: 28 October 2020; Published: 30 October 2020


Abstract: This study evaluates the anatomical proﬁles, jump, sprint, power outputs, endurance, and
peak blood lactate levels ([LA]peak) of handball players of two age groups—U17 (n = 77) and U19
(n = 46)—and analyses the role of training in their physical abilities. Vertical jump performance was
determined by counter movement jump (CMJ) and counter movement jump with free arms (CMJFA)
tests. A running-based anaerobic sprint test (RAST) determined the relative power output (watts/kg
body weight) and absolute power output (watts) of the players. Sprint performance over 5 m, 10 m,
and 30 m distances was evaluated. An incremental shuttle run test (40 m) was designed to determine
aerobic threshold (AeT), anaerobic threshold (AnT), and [LA]peak. All parameters were measured for
pivots, wingers, backs, and goalkeepers of each group. The U19 players were signiﬁcantly heavier
than the U17 group, but both the groups were nearly equal in height. The U19 group jumped higher
than the U17 members, although the only signiﬁcant diﬀerence (p = 0.032) was observed between
the wingers of the groups in CMJ. Sprint performance varied marginally between the groups and
only U19 pivots were found to be signiﬁcantly (for distances of 5, 10, and 30 m: p = 0.047, p = 0.018,
and p = 0.021, respectively) faster than U17 pivots. No diﬀerence in relative power output between
the groups was noted, although the U19 players recorded higher absolute power outputs. Maximal
velocity and velocities at the AeT and AnT were almost similar in the groups. Distance covered by
the groups at the intensities of AeT and AnT varied only little. Higher [LA]peak was observed in the
U19 players. U19 players failed to convert their superior power into speed and jump. The training
pattern of the handball players needs to be revised so that U19 players may develop faster and be
more enduring than the U17 group.
Keywords: power output; aerobic threshold; anaerobic threshold; peak blood lactate; jump tests
1. Introduction
Selection and training systems of sports schools in Poland, coordinated by various sports bodies,
including the Polish Handball Federation, have merits and demerits. Besides providing sports training
to their athletes, sports schools in Poland focus on other social matters as well. The assessment of
Int. J. Environ. Res. Public Health 2020, 17, 7979; doi:10.3390/ijerph17217979
www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2020, 17, 7979
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a player’s talent in team sports is based on three areas: motor skills and physique, mental health,
and social features [1–3]. A common training program in the sports schools has its pros and cons.
A common physical training program in sports schools across the country is likely to cause similar
physiological adaptation in the adolescents and young players, although individual development
factor plays an important steering force in their overall development. However, a similar training
pattern does not create opportunities to implement sports-speciﬁc training programs [4–6].
Handball players require speciﬁc training that allows them to perform cyclic and acyclic activities
eﬃciently during 60 min of match play. Like many other team sports, the movement pattern of handball
players during match play is intermittent, intense, and varies widely in phases of defense and attack [7,8].
Apart from physical training, the performance of a handball player is inﬂuenced by anthropometric,
physiological, and kinematic factors, like many other team sports [9–11]. Match-speciﬁc ﬁtness of
a handball player can be evaluated by a number of well-designed ﬁeld tests [12]. The physical and
physiological characteristics of handball players of various levels have been studied extensively by
researchers [13–15]. These are concerned with aerobic capacity, anaerobic endurance, and anaerobic
power determined by sprint run, jump, and throw [13–15].
The diﬀerences between youth (16–19 year) handball players of various levels have been
documented by researchers [16,17]. Handball matches are played at the intensity range of 65 to
85% VO2max and at a blood lactate concentration of 3 to 11 mmol/L. The VO2max of the youth
(16–21 year) handball players varies from 50 to 65 mL/kg/min, which partly depends on their position
of play. The blood lactate concentration in same group of handball players after a run ramp test for the
exhaustion is 10–12 mmol/L [14,18–22]. The endurance capability of athletes is commonly assessed by
measuring their performance or running speed at the level of anaerobic threshold (AnT), which reﬂects
the running economy and eﬃciency of the player. The VO2max reﬂects the endurance potential of
a player and is not as important a marker of economy of run as the AnT [23,24]. In spite of the
dominance of aerobic metabolism, the sport of handball is interspersed by high intensity activities like
jumps, throws, changes of direction, and stops that greatly tax anaerobic metabolism [18,23]. The load
imposed on the players is determined mostly by the demand of the game. Much of the movement
during a handball game takes place in quick succession, with brief rest or slow movement in between.
Although these activities are anaerobic in nature, the need to repeat them frequently demands a high
level of aerobic capacity. Endurance training is designed to delay the appearance of fatigue of the
players, during both training and match-play [19,25].
Handball is a game with a large number of explosive movements such as accelerations, turns,
jumps, and throws [4]. Therefore, in assessing a player’s progress, it is very important to measure
the anaerobic capacity of the player. Sprint, jump, and throw are commonly measured to assess the
anaerobic power of a handball player [26–28]. Studies [29,30] show that CMJ values in the groups of
handball players aged 16–19 do not show signiﬁcant progression similar to the mean power in the
RAST test [29,31]. However, to the best of our knowledge, no studies have been conducted so far that
evaluated the physical and physiological proﬁles of age-group handball players in the sports schools
of Poland. The age of 17–19 years in the development of handball players is a period of transition
from junior handball to the requirements for handball players in senior teams, as indicated by the
values of motor preparation indicators recorded in other studies [14,15,29,32]. It should be expected
that, during this period, there will be a signiﬁcant development of motor skills such as endurance,
relative power, and running speed. The sports schools of Poland still follow the guidelines for the
selection of players and their training set by the concerned authority decades before. A review of
the selection criteria and training programs is absolutely essential, especially in the light of recent
advancement of sports science and training. The aim of the present study is to revise the selection
criteria and eﬃcacy of training of the U17 and U19 handball players of the Polish Handball Federation
Sports Schools, by comparing anthropometric proﬁles and explosive power, sprinting ability, and
selected physiological characteristics.
Int. J. Environ. Res. Public Health 2020, 17, 7979
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2. Materials and Methods
2.1. Participants
A total of 133 male handball players, all of whom were students of the Polish Handball Federation
Sports Schools at Gda´nsk, Kielce, Kwidzyn, and Płock, participated in this study. Players were divided
into two categories: U17 (age: 15 to <17 years) and U19 (age: 17 to <19 years). In each age group,
the players were divided according to the position: pivots (U17: n = 7, U19: n = 10), wingers U17:
n = 8, U19: n = 22, backs (U17: n = 26, U19: n = 42), and goalkeepers (U17: n = 5, U19: n = 13). All
of the U19 and some of the U17 players were selected for the Junior Polish National Team. Body
weight and height of the participants and their playing positions are presented in Table 1. All subjects
(in the case of 18+ years) or their parents or legal guardians (in the case of <18 years) provided their
written consent to participate in this study after being informed of all procedures and risks involved in
this study. They were in good health and reported no injuries and infections at the time of the study.
The study was conducted during a scheduled training week, before competitive session.
Table 1. Physical characteristics of handball players across their playing positions.
Indicator
Position
U19
U17
Mean
Diﬀerence (%)
p-Value
Eﬀect Size
Weight (kg)
P
101.9 ± 11.3
92.4 ± 14.93
9.52 (9.3%)
0.176
0.70/Moderate
W
80.5 ± 3.10
69.4 ± 4.89
11.13 (13.8%)
<0.001
2.47/Very large
B
86.5 ± 10.92
78.5 ± 8.71
7.99 (9.2%)
0.003 #
0.83/Moderate
GK
92.8 ± 11.69
81.6 ± 8.07
11.15 (12.0%)
0.033
1.22/Large
Height (cm)
P
190.3 ± 4.89
192.3 ± 6.06
−2.01 (−1.1%)
0.478
0.36/Small
W
183.4 ± 4.07
180.5 ± 7.48
2.92 (1.6%)
0.307
0.43/Small
B
188.7 ± 5.60
187.0 ± 6.68
1.71 (0.9%)
0.281
0.27/Small
GK
189.6 ± 5.32
188.3 ± 4.64
1.29 (0.7%)
0.554 #
0.27/Small
Note: P—pivots; W—wingers; B—backs; GK—goalkeepers; # a nonparametric test was used to compare the groups.
The whole experiment was divided in two sessions and conducted over two days. The two
experimental sessions were separated by approximately 24 h. Subjects were instructed to refrain
from all sorts of caﬀeine ingestion 48 h before tests. In the ﬁrst session, all subjects performed a
countermovement jump (CMJ) test and countermovement jump with free arms (CMJFA) test, sprint
run over a distance of 30 m, and running-based anaerobic sprint test (RAST), after 20 min of break.
Both the jump and the sprint tests were performed twice and only the better result was analyzed for this
study. In the second session, the endurance capability of the subjects was evaluated. The endurance
test and the RAST, however, were performed once only.
2.1.1. Jump Tests
All the subjects performed two jump tests—(1) counter movement vertical jump without arm swing
(CMJ): participants were instructed to stand upright comfortably with hands on hips. They remained in
this position for 3 s before the jump was performed. Following a verbal command, the players initiated
a countermovement followed by a maximal vertical jump in one continuous motion. Participants were
instructed to keep their hands on their hips throughout the jump, and their legs straight while in the
air [33–35]. (2) Counter movement vertical jump with arm swing (CMJFA): this diﬀers from the CMJ
in that both the arms were allowed to move freely during the vertical jump [36]. Each of the jump
tests was repeated twice, with a passive recovery of 1 min between the two, and the best result was
recorded and analyzed. Optojump (Microgate, Srl., Bolzano, Italy) was used for the measurement of
the jump height.
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2.1.2. Sprint Test
This test was preceded by a non-standardized 20 min warm-up. Subjects performed two 30 m
sprint runs starting from a standing position. A 4 min interval with light active recovery separated
two trials. Time was recorded using SMARTSPEED PRO time gate system (Fusion Sport, Brisbane,
Australia). Time was measured at the 5 m, 10 m, and 30 m marks. Time measured for the 5 m and 10 m
distances indicated the ability to quick start, whereas the speed achieved for the 30 m distance reﬂected
the speed usually obtained during the transition from defense to attack phase in typical handball
match play.
2.1.3. Running-Based Anaerobic Sprint Test (RAST)
Anaerobic capacity was measured by a running-based anaerobic sprint test (RAST). It has been
shown that this test can replace the Wingate test to estimate anaerobic power and capacity [37].
Each subject completed six 35 m sprint runs, with 10 s passive rest between two repetitions. Time was
recorded using SMARTSPEED PRO time gate system (Fusion Sport, Brisbane, Australia). The power
output (in watts) for each sprint was calculated according to the following equation:
Anaerobic capacity (Watt) = Weight (kg) × Distance (m) 2 ÷ Time (s) 3
(1)
Fatigue Index = [Maximum power (watts) − Minimum power (watts)] ÷ Total time (s)
for the 6 sprints
(2)
The RAST gives an estimate of the neuromuscular and energy determinants of maximal anaerobic
performance and is a simple, but very useful test used in team sports like handball, where running is
an important component of activities [38].
2.1.4. Endurance Test
This is a multistage ﬁtness test that determines endurance by an incremental shuttle run. This test
was conducted on a synthetic surface in an indoor hall. The test involved continuous running between
two lines 40 m apart [39]. Subjects started running at the speed of 8 km/h, which is increased by
1.5 km/h after every 3 min thereafter, until exhaustion. To assure the constant running speed, subjects
were instructed to adjust their pace using audio signals. The audio signal was given at the end and
at the middle of 40 m distance. The end of the test was considered when the participant twice failed
to reach the front line in time (objective evaluation) or he felt not able to cover another shuttle at the
dictated speed (subjective evaluation) [40].
During the test, heart rate was continuously recorded at an interval of 5 s using Polar Team2
Pro chest-worn heart rate monitors (Polar Electro, Kempele, Finland). Maximal heart rate (HRmax):
the highest heart rate (HR) recorded at the exhaustive stage of the endurance test was considered as
the HRmax.
Collection of blood samples for the measurement of lactate concentration: after the end of each
stage of run, the subjects were stopped for 30 s, during which 20 mL of capillary blood was collected
from earlobe by pin-prick under aseptic conditions. Blood samples were also taken at the end of the
test and at the 4th and 8th minutes of the recovery period. Blood lactate concentration ([LA]) was
measured using a lactate analyzer (Biosen C-Line EKF Diagnostic GmbH, Magdeburg, Germany).
Peak blood lactate concentration ([LA]peak): the highest [LA] recorded following the end of the
test was recorded as the [LA]peak.
Determination of aerobic threshold (AeT): the running intensity at which the [LA] increased by
0.5 mmol/L was marked as the AeT [41].
Determination of anaerobic threshold (AnT): the running speed at the [LA] of 4 mmol/L was
considered as the AnT of the player [42].
Int. J. Environ. Res. Public Health 2020, 17, 7979
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The total distance of run, completed by the subject in the endurance test, was divided into three
intensity zones—(a) zone 1: up to AeT, (b) zone 2: above AeT to AnT, and (c) zone 3: above the
AnT level.
2.2. Statistical Analyses
Mean and standard deviation were used to represent the average and the typical spread of values
of all the measured variables. The normal Gaussian distribution of the data was veriﬁed by the
Shapiro–Wilk’s test. If the data were normally distributed within groups, an independent samples
t-test was used to test the diﬀerences between U17 and U19. If the data were not normally distributed,
a Mann–Whitney U-test was used. Two separate one-way analyses of variance with a Tukey post-hoc
test were used to determine whether and where diﬀerences existed in the all measured variables
between the playing positions in each age group. The eﬀect size (ES) of the intervention was calculated
using Cohen’s guidelines. Threshold values for ES were >0.2 (small), >0.6 (moderate), >1.2 (large),
and >2.0 (very large) [43]. Statistical signiﬁcance was set at p ≤ 0.05. All calculations were performed
with STATISTICA ver. 13.3 (TIBCO Software Inc., Palo Alto, CA, USA).
3. Results
3.1. Body Weight and Height
Body weight and height of the U17 and U19 players are presented in Table 1. Weight and height
between the U17 and U19 players for all position of play are compared. No statistically signiﬁcant
diﬀerence in body height between U17 and U19 players was noted. Under 19 players, however, were
heavier than their U17 counterparts by 9.2 to 13.8% and the diﬀerence was signiﬁcant in all cases,
except in pivots.
3.2. Vertical Jump Performance
Figure 1 presents the jump performance of the players. It compares the performance of the U19
and U17 players of each playing position. Superior jumping skill was demonstrated by the U19
players compared with the U17 players, for any given position of play, although the diﬀerence was
non-signiﬁcant in most of the cases. Wingers of the U19 group demonstrated signiﬁcantly higher CMJ
ability than the U17 players. As expected, CMJFA score was higher than all the respective cases of CMJ.
Int. J. Environ. Res. Public Health 2020, 17, x 
5 of 15 
difference in body height between U17 and U19 players was noted. Under 19 players, however, were 
heavier than their U17 counterparts by 9.2 to 13.8% and the difference was significant in all cases, 
except in pivots. 
Table 1. Physical characteristics of handball players across their playing positions. 
Indicator 
Position 
U19 
U17 
Mean Difference (%) 
p-Value 
Effect Size 
Weight (kg) 
P 
101.9 ± 11.3 
92.4 ± 14.93 
9.52 (9.3%) 
0.176 
0.70/Moderate 
W 
80.5 ± 3.10 
69.4 ± 4.89 
11.13 (13.8%) 
<0.001 
2.47/Very large 
B 
86.5 ± 10.92 
78.5 ± 8.71 
7.99 (9.2%) 
0.003 # 
0.83/Moderate 
GK 
92.8 ± 11.69 
81.6 ± 8.07 
11.15 (12.0%) 
0.033 
1.22/Large 
Height (cm) 
P 
190.3 ± 4.89 
192.3 ± 6.06 
−2.01 (−1.1%) 
0.478 
0.36/Small 
W 
183.4 ± 4.07 
180.5 ± 7.48 
2.92 (1.6%) 
0.307 
0.43/Small 
B 
188.7 ± 5.60 
187.0 ± 6.68 
1.71 (0.9%) 
0.281 
0.27/Small 
GK 
189.6 ± 5.32 
188.3 ± 4.64 
1.29 (0.7%) 
0.554 # 
0.27/Small 
Note: P—pivots; W—wingers; B—backs; GK—goalkeepers; # a nonparametric test was used to 
compare the groups. 
3.2. Vertical Jump Performance  
Figure 1 presents the jump performance of the players. It compares the performance of the U19 
and U17 players of each playing position. Superior jumping skill was demonstrated by the U19 
players compared with the U17 players, for any given position of play, although the difference was 
non-significant in most of the cases. Wingers of the U19 group demonstrated significantly higher CMJ 
ability than the U17 players. As expected, CMJFA score was higher than all the respective cases of CMJ. 
 
Figure 1. Test results of counter movement jump (CMJ) and counter movement jump free arms 
(CMJFA) of the participants. (P—pivots; W—wingers; B—backs; GK—goalkeepers; * p < 0.05). 
3.3. Sprint Performance 
Sprint performance (time) of the participant handball players, for various distance marks, as 
well as differences in performance between U17 and U19 groups, and the p-values and the ES of the 
difference, are presented in Table 2. The players of all positions of the U19 group outperformed the 
e
e ti e U17
laye
i
both the 10
a d 30
i t u
althou h the diffe e
e
a
i
ifi a t
Figure 1. Test results of counter movement jump (CMJ) and counter movement jump free arms (CMJFA)
of the participants. (P—pivots; W—wingers; B—backs; GK—goalkeepers; * p < 0.05).
Int. J. Environ. Res. Public Health 2020, 17, 7979
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3.3. Sprint Performance
Sprint performance (time) of the participant handball players, for various distance marks, as
well as diﬀerences in performance between U17 and U19 groups, and the p-values and the ES of the
diﬀerence, are presented in Table 2. The players of all positions of the U19 group outperformed the
respective U17 players in both the 10 m and 30 m sprint runs, although the diﬀerence was signiﬁcant
only in the case of pivots. On the other hand, except in the case of pivots, the U17 group members in
the 5 m sprint demonstrated better performance than their U19 counterparts.
Table 2. Sprint performance of the U17 and U19 participant handball players.
Distance (m)
Position
Sprint Time (Seconds)
Mean
Diﬀerence (%)
p-Value
Eﬀect Size
U19
U17
5 m
P
1.06 ± 0.04
1.10 ± 0.03
−0.03 (−3.3%)
0.045 #
1.05/Moderate
W
1.08 ± 0.05
1.05 ± 0.05
0.03 (2.7%)
0.151
0.61/Moderate
B
1.05 ± 0.03
1.05 ± 0.04
0.00 (0.4%)
0.717
0.11/Trivial
GK
1.10 ± 0.03
1.08 ± 0.06
0.02 (1.5%)
0.574
0.29/Small
10 m
P
1.80 ± 0.07
1.89 ± 0.06
−0.09 (−4.72%)
0.017 #
1.32/Large
W
1.77 ± 0.07
1.78 ± 0.07
−0.01 (−0.6%)
0.721
0.15/Trivial
B
1.76 ± 0.04
1.78 ± 0.07
−0.02 (−1.1%)
0.18
0.34/Small
GK
1.83 ± 0.07
1.84 ± 0.08
−0.01 (−0.8%)
0.721
0.18/Trivial
30 m
P
4.38 ± 0.13
4.62 ± 0.23
−0.25 (−5.6%)
0.007 #
1.27/Large
W
4.21 ± 0.12
4.31 ± 0.16
−0.10 (−2.4%)
0.113
0.67/Moderate
B
4.26 ± 0.13
4.32 ± 0.17
−0.06 (−1.3%)
0.142
0.37/Small
GK
4.43 ± 0.24
4.48 ± 0.16
−0.05 (−1.1%)
0.625
0.26/Small
Note: P—pivots, W—wingers, B—backs, GK—goalkeepers; # a nonparametric test was used to compare the groups.
3.4. Running-Based Anaerobic Sprint Test (RAST)
Maximum power (Pmax), minimum power (Pmin), average power (Pav), and fatigue index (FI),
recorded in RAST, are presented in Table 3. All the power outputs are expressed in watts/kg body
weight in this table. All the power outputs—Pmax, Pmin, and Pav—of U19 outﬁeld players exceeded
the power outputs of U17 players of similar positions, although the diﬀerence in none of the cases was
found to be signiﬁcant. Only goalkeepers of the U17 group demonstrated higher Pmin and Pav than the
U19 goalkeepers, although the ES was only trivial. Wingers of both the U19 and U17 groups showed
higher Pmax and Pav than other players of their own group. No signiﬁcant diﬀerence of FI between the
groups was found and the ES varied from trivial to moderate.
Table 4 shows the power output of the players determined by RAST, but the power output in this
table is expressed in watts. All the power outputs (Pmax, Pmin, and Pav) of the older age group (U19)
were recorded higher than those of the younger group (U17) of handball players and the diﬀerence was
signiﬁcant in all the cases, except Pmin between the goalkeepers. The ES varied from moderate to large.
Table 3. Power output (watts/kg body weight) and fatigue index (FI) in handball players as determined
by the running-based anaerobic sprint test (RAST).
Indicator
Position
U19
U17
Mean
Diﬀerence (%)
p-Value
Eﬀect Size
Pmax
(Watts/kg
body weight)
P
8.05 ± 0.84
7.02 ± 1.13
1.03 (12.8%)
0.060
1.00/Moderate
W
9.66 ± 0.95
9.07 ± 1.47
0.59 (6.1%)
0.301
0.44/Small
B
9.17 ± 0.95
8.96 ± 1.36
0.21 (2.3%)
0.499
0.17/Trivial
GK
8.30 ± 1.15
7.89 ± 0.93
0.41 (4.9%)
0.440
0.42/Small
Int. J. Environ. Res. Public Health 2020, 17, 7979
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Table 3. Cont.
Indicator
Position
U19
U17
Mean
Diﬀerence (%)
p-Value
Eﬀect Size
Pmin
(Watts/kg
body weight)
P
5.70 ± 0.94
5.07 ± 0.91
0.63 (11.1%)
0.183
0.69/Moderate
W
6.68 ± 0.64
6.13 ± 1.17
0.55 (8.3%)
0.218
0.52/Small
B
6.57 ± 0.78
6.37 ± 0.99
0.2 (3.1%)
0.383
0.22/Small
GK
5.47 ± 0.88
5.63 ± 0.90
−0.16 (−2.9%)
0.742
0.18/Trivial
Pav
(Watts/kg
body weight)
P
6.69 ± 0.77
5.88 ± 0.98
0.81 (12.1%)
0.088
0.90/Moderate
W
7.98 ± 0.74
7.62 ± 1.05
0.35 (4.4%)
0.391
0.36/Small
B
7.71 ± 0.81
7.57 ± 1.12
0.14 (1.9%)
0.574
0.14/Trivial
GK
6.67 ± 1.05
6.75 ± 0.87
−0.08 (−1.2%)
0.874
0.08/Trivial
FI
P
29.24 ± 8.66
27.79 ± 7.02
1.44 (4.9%)
0.709
0.19/Trivial
W
30.60 ± 5.11
32.71 ± 14.99
−2.11 (−6.9%)
0.702
0.16/Trivial
B
28.27 ± 5.73
28.57 ± 7.68
−0.3 (−1.1%)
0.865
0.04/Trivial
GK
34.17 ± 4.23
28.82 ± 6.36
5.35 (15.7%)
0.104
0.91/Moderate
Note: P—pivots; W—wingers; B—backs; GK—goalkeepers; FI—fatigue index.
Table 4. Absolute power (watts) produced in the players of various playing positions, recorded in RAST.
Indicator
Position
U19
U17
Mean
Diﬀerence (%)
p-Value
Eﬀect Size
Pmax
(Watts)
P
798.2 ± 125.4
641.8 ± 112.9
156.4 (19.6%)
0.017
1.33/Large
W
807.5 ± 121.9
630.9 ± 121.5
176.6 (21.9%)
<0.001 #
1.45/Large
B
784.4 ± 98.2
701.2 ± 122.2
83.2 (10.6%)
0.005
0.73/Moderate
GK
777.9 ± 102.0
641.1 ± 80.1
136.8 (17.6%)
0.008
1.59/Large
Pmin
(Watts)
P
561.5 ± 88.9
459.6 ± 65.5
101.9 (18.2%)
0.015
1.35/Large
W
556.8 ± 62.9
425.9 ± 89.5
130.9 (23.5%)
0.001
1.57/Large
B
563.1 ± 85.3
497.0 ± 79.8
66.0 (11.7%)
0.002
0.81/Moderate
GK
511.4 ± 66.2
455.7 ± 65.1
55.6 (10.9%)
0.125
0.85/Moderate
Pav
(Watts)
P
662.6 ± 100.9
534.7 ± 80.1
127.9 (19.3%)
0.011
1.44/Large
W
666.4 ± 92.2
529.8 ± 86.6
136.6 (20.5%)
0.001 #
1.55/Large
B
661.0 ± 91.6
591.6 ± 96.1
69.5 (10.5%)
0.004
0.74/Moderate
GK
623.8 ± 78.6
547.3 ± 64.9
76.5 (12.3%)
0.050
1.12/Moderate
Note: P—pivots; W—wingers; B—backs; GK—goalkeepers; # a nonparametric test was used to compare the groups.
3.5. Endurance Performance
Maximum velocity (Vmax), velocity at the aerobic threshold (VAeT), and the velocity of the players
at the intensity of anaerobic threshold (VAnT), determined in endurance test, are presented in Figure 2.
The U19 players of most of the playing positions showed higher Vmax, VAeT, and VAnT. When compared
between the age groups (U19 and U17), the diﬀerence of the velocity for any given intensity was only
marginal, no signiﬁcant diﬀerence was observed in any of the cases, and the ES varied only from trivial
to small.
The distance covered by the players at three diﬀerent intensity zones is shown in Figure 3. The total
distance covered (DTOTAL) is the arithmetic sum of the distance covered up to the aerobic threshold
(DAeT) and the distance covered up to the intensity of anaerobic threshold (DAnT) (but higher than
the AeT level). Like velocity, the diﬀerence of distance covered for any of the three given intensities
between the groups (U19 and U17) was marginal again. Only DTOTAL of the U19 backs was found to
be signiﬁcantly higher than that of the U17 backs.
Table 5 shows HRmax% at the intensities of AeT (HRAeT) and AnT (HRAnT) of the participants.
No signiﬁcant diﬀerence in HRAeT and HRAnT between the age groups was found, except the HRAeT
of the backs.
Int. J. Environ. Res. Public Health 2020, 17, 7979
8 of 15
Maximum velocity (Vmax), velocity at the aerobic threshold (VAeT), and the velocity of the players 
at the intensity of anaerobic threshold (VAnT), determined in endurance test, are presented in Figure 
2. The U19 players of most of the playing positions showed higher Vmax, VAeT, and VAnT. When 
compared between the age groups (U19 and U17), the difference of the velocity for any given 
intensity was only marginal, no significant difference was observed in any of the cases, and the ES 
varied only from trivial to small. 
 
Figure 2. Velocity of the players at three intensity zones. 
The distance covered by the players at three different intensity zones is shown in Figure 3. The 
total distance covered (DTOTAL) is the arithmetic sum of the distance covered up to the aerobic 
threshold (DAeT) and the distance covered up to the intensity of anaerobic threshold (DAnT) (but higher 
than the AeT level). Like velocity, the difference of distance covered for any of the three given 
intensities between the groups (U19 and U17) was marginal again. Only DTOTAL of the U19 backs was 
found to be significantly higher than that of the U17 backs. 
Figure 2. Velocity of the players at three intensity zones.
Int. J. Environ. Res. Public Health 2020, 17, x 
8 of 15 
 
Figure 3. Distance covered by the players at different intensity zones in the endurance test. 
Table 5 shows HRmax% at the intensities of AeT (HRAeT) and AnT (HRAnT) of the participants. No 
significant difference in HRAeT and HRAnT between the age groups was found, except the HRAeT of the 
backs. 
Table 5. Internal load parameters of the subjects. 
Indicator 
Position 
U19 
U17 
Mean Difference (%) 
p-Value 
Effect Size 
HRmax 
[beats/min] 
P 
195.4 ± 8.72 
199.1 ± 5.93 
N/A 
N/A 
N/A 
W 
196.4 ± 5.29 
200.3 ± 6.7 
N/A 
N/A 
N/A 
B 
196.0 ± 10.13 
195.6 ± 5.81 
N/A 
N/A 
N/A 
GK 
193.6 ± 5.03 
199.4 ± 3.66 
N/A 
N/A 
N/A 
HRAnT 
[%HRmax] 
P 
91.8 ± 2.79 
89.6 ± 4.18 
2.20 (2.4%) 
0.244 
0.60/Small 
W 
91.6 ± 3.20 
91.0 ± 4.09 
0.58 (0.6%) 
0.720 
0.15/Trivial 
B 
89.8 ± 4.86 
91.0 ± 3.26 
−1.21 (−1.4%) 
0.227 
0.31/Small 
GK 
90.1 ± 3.89 
91.5 ± 2.93 
−1.38 (−1.5%) 
0.425 
0.43/Small 
HRAeT 
[%HRmax] 
P 
83.4 ± 1.63 
82.2 ± 4.90 
1.20 (1.4%) 
0.770 # 
0.31/Small 
W 
82.6 ± 4.09 
84.5 ± 4.30 
−1.88 (−2.3%) 
0.292 
0.44/Small 
B 
80.8 ± 5.06 
83.5 ± 3.83 
−2.72 (−3.4%) 
0.015 
0.63/Moderate 
GK 
82.6 ± 2.18 
82.6 ± 3.99 
−0.01 (−0.01%) 
0.997 
0/Trivial 
Note: P—pivots; W—wings; B—backs; GK—goalkeeper; N/A—not appropriate; # a nonparametric 
test was used to compare the groups. 
Figure 4 presents [LA]peak of the subjects recorded after the end of the endurance test. The players 
of all the positions of U19 demonstrated higher [LA]peak than their U17 counterparts, although the 
difference was statistically significant only between the backs (p < 0.001) and the pivots (p = 0.037) of 
the two groups. 
Figure 3. Distance covered by the players at diﬀerent intensity zones in the endurance test.
Table 5. Internal load parameters of the subjects.
Indicator
Position
U19
U17
Mean Diﬀerence (%)
p-Value
Eﬀect Size
HRmax
[beats/min]
P
195.4 ± 8.72
199.1 ± 5.93
N/A
N/A
N/A
W
196.4 ± 5.29
200.3 ± 6.7
N/A
N/A
N/A
B
196.0 ± 10.13
195.6 ± 5.81
N/A
N/A
N/A
GK
193.6 ± 5.03
199.4 ± 3.66
N/A
N/A
N/A
HRAnT
[%HRmax]
P
91.8 ± 2.79
89.6 ± 4.18
2.20 (2.4%)
0.244
0.60/Small
W
91.6 ± 3.20
91.0 ± 4.09
0.58 (0.6%)
0.720
0.15/Trivial
B
89.8 ± 4.86
91.0 ± 3.26
−1.21 (−1.4%)
0.227
0.31/Small
GK
90.1 ± 3.89
91.5 ± 2.93
−1.38 (−1.5%)
0.425
0.43/Small
HRAeT
[%HRmax]
P
83.4 ± 1.63
82.2 ± 4.90
1.20 (1.4%)
0.770 #
0.31/Small
W
82.6 ± 4.09
84.5 ± 4.30
−1.88 (−2.3%)
0.292
0.44/Small
B
80.8 ± 5.06
83.5 ± 3.83
−2.72 (−3.4%)
0.015
0.63/Moderate
GK
82.6 ± 2.18
82.6 ± 3.99
−0.01 (−0.01%)
0.997
0/Trivial
Note: P—pivots; W—wings; B—backs; GK—goalkeeper; N/A—not appropriate; # a nonparametric test was used to
compare the groups.
Figure 4 presents [LA]peak of the subjects recorded after the end of the endurance test. The players
of all the positions of U19 demonstrated higher [LA]peak than their U17 counterparts, although the
diﬀerence was statistically signiﬁcant only between the backs (p < 0.001) and the pivots (p = 0.037) of
the two groups.
Int. J. Environ. Res. Public Health 2020, 17, 7979
9 of 15
test was used to compare the groups. 
Figure 4 presents [LA]peak of the subjects recorded after the end of the endurance test. The players 
of all the positions of U19 demonstrated higher [LA]peak than their U17 counterparts, although the 
difference was statistically significant only between the backs (p < 0.001) and the pivots (p = 0.037) of 
the two groups. 
 
Figure 4. Peak blood lactate [LA]peak concentrations in the participants determined in the endurance 
test (* p < 0.05, **** p < 0.001). 
Figure 4. Peak blood lactate [LA]peak concentrations in the participants determined in the endurance
test (* p < 0.05, **** p < 0.001).
4. Discussion
Handball players need speciﬁc training that allows them to do multiple and complex physical
tasks successfully. Like many other team sports, age, training, skill, and playing position serve
important roles in developing eﬃciency in handball players [8,44]. The requirements for playing in
each position are determined by the appropriate physique, absolute power, and physiological proﬁle
of the player [45]. This, in turn, sets appropriate training demands for players of each playing position,
and thus can diﬀerentiate a winger from a pivot or a back [15,25,46]. The key ﬁndings of this study are
that the explosive power of the U19 players was superior to that of the U17 players, which resulted in
better jump performance, but failed to improve speed in the U19 group. The training program in the
sports schools of Poland was unsuccessful in the improvement of endurance in U19 players.
4.1. Pivots
Pivots experience more physical confrontations than players of any other positions, against the
opponent team members, during a game. As a result, strength and explosive power are some of
the primary requirements for pivots [6,29]. This is evident from the body weight and height of the
U19 and U17 groups, where U19 pivots are nearly 10% heavier than pivots of the U17 group, but
the diﬀerence in height between the two is almost absent (~1%). Another important requirement for
pivots is the ability to run fast on a longer available space of the court (e.g., the 15–30 m segment of the
sprint test in this study), which is especially very useful in counterattack. Fast attack and defense in
quick succession, jumps, and powerful throws during game require appropriate anaerobic training of
the players, especially for pivots [47]. A high training load elevates the serum growth hormone and
testosterone in puberty and adolescence, which modulate muscle development and power.
Training of high intensity and long duration act as appropriate stimuli that favor to improve
or maintain body stature and power [48]. Raspberry and Bouchard [49] have shown that resistance
training can be carried out to a maximum load of 80% without appreciable risk of injury at this age.
According to Gorostiaga et al. [50], a training program including high resistance exercises with slow
movements that favor muscle hypertrophy hinders the development of explosive power, and thus
favors sprinting ability. There was no diﬀerence in explosive power between the U17 and U19 groups
as reﬂected by CMJ and CMJFA performance. Pivots of the U19 group showed signiﬁcantly higher
sprinting performance than the U17 pivots for all the distance marks (5 m, 10 m, and 30 m). This change
of direction ability in pivot players was also reported in other studies [47,51]. The ability of change of
direction with maximum power in pivots largely occurs between the ages of 16 and 19 years [52]. In all
power ratings, U19s dominate over U16s. This is particularly evident when the power output was
expressed in watts/kg body weight [31,38].
Int. J. Environ. Res. Public Health 2020, 17, 7979
10 of 15
In case of the pivots, the anaerobic power generated was largely transferred to external loads,
as noted by Krüger et al. [19]. This is partly supported by the fact that the [LA]peak of the pivots of
U19s was ~23% higher than that of the younger (U17) group of players. However, the Vmax, VAeT and
VAnT of the U19 pivots were only marginally higher than those of the pivots of the U17 group.
4.2. Wingers
Jump, sprint; explosive strength; ability to accelerate, especially between 20 and 30 m distance;
and reasonably high aerobic power are some of the key requirements for successful wingers [51,53].
There was no diﬀerence in body height between the age groups, although weight increased signiﬁcantly
(13.8%, p < 0.001; ES = very large) in the higher age group (U19). With a signiﬁcant increase in body
weight, a signiﬁcant increase in anaerobic power and explosive strength is expected in U19 wingers
compared with their U17 counterparts. However, an increase in muscle mass in U19, if any, and its role
in the improvement of explosive strength requires further study. In the studied groups, no signiﬁcant
diﬀerence in speed over the distance of 5 to 10 m was found. The diﬀerence in explosive power
is clearly visible in the CMJ results (p = 0.032) between the two age groups. The height of CMJ is
higher by 11% and CMJFA by 9% in the U19 group. Thus, the increase in mass is accompanied by an
increase in explosive power, but the increase in muscle mass did not support faster running in the
U19 players. This observation is also supported by the fact that the absolute power (watts) output in
the U19 players in RAST was signiﬁcantly higher than that in the U17 group, but no such diﬀerence
existed when the power was expressed in watts/kg body weight. While an increase in muscle mass is
usually associated with an increase in power, there is no real diﬀerence in power with respect to the
body mass in both age groups in this study. Improper training methods and loads probably failed to
stimulate the relative increase in power in U19 players [54]. This was observed in other team sports as
well [55,56]. The inclusion of agility in speed training brings much better results than repeated speed
training or interval training in handball players [54,57,58]. Running economy in handball players, like
many other team games, plays a crucial role in maintaining the higher intensity of work during match
play without appreciable fatigue [59,60].
Running intensity above the AnT level resulted in more dependence on the anaerobic metabolism
and decreased running economy of the players. The U19 players, except pivots, covered a longer
distance above the AnT and produced higher [LA] than the participants of the U17 group. This suggests
a decrease in the running economy in the U19 group compared with the U17 group [59]. The relationship
between anthropometric parameters, including body weight and running speed, was pointed out by
Kukoli et al. [61] and Young et al. [62]. The increase in absolute power generation without any change
in relative power likely results from the increase in body weight of U19 players. The reason behind the
lack of improvement of relative power in U19 players needs further study.
4.3. Backs
One of the major requirements of backs is a high level of strength combined with muscle mass.
The U19 backs demonstrated higher glycolytic capacity than the backs of U17 group, as reﬂected by the
23% higher [LA]peak, in spite of lower HRAeT in comparison with the U17 backs. The strength training
is likely to improve the sprint, acceleration, and jumping and throwing abilities of the handball players.
The longer distance covered by the backs during competitive match play needs reasonable aerobic
training as well [19,53,63]. A signiﬁcant diﬀerence in body weight (9%, p = 0.001; ES = moderate) of
backs between the groups (U19 and U17) is noticeable, although no diﬀerences in explosive power
and running speed were found between the groups in this study. No signiﬁcant motor development
beyond the age of 17 years is commonly found that would diﬀerentiate the U19 group from the U17
group, and this can explain why there is no signiﬁcant diﬀerence in explosive power and running speed
between the groups [47]. In backs, like pivots and wingers, power development in U19 players mainly
results from an increase in muscle mass. A 10% increase in power is not enough to improve the speed
signiﬁcantly in U19 backs when compared with the backs of the U17 group. The total distance covered
Int. J. Environ. Res. Public Health 2020, 17, 7979
11 of 15
(DTotal) by the backs of the U19 group exceeded the DTotal covered by the backs of the U17 group by 6%,
mainly due to a much higher (>16%) DAnT, in spite of the lower DAeT. This again explains superiority
of the anaerobic power in U19 backs in spite of compromised aerobic capacity.
4.4. Goalkeepers
Besides game-speciﬁc skill, handball goalkeepers are trained for developing explosive power,
which is a prerequisite to eﬃcient and eﬀective jumping, throwing the ball, and quick acceleration of
movement in all possible directions [19,27,32].
The height of the goalkeepers of both the age groups, like outﬁeld players, does not vary
signiﬁcantly [64]. However, U19 goalkeepers were heavier than their U17 counterparts. Probably,
stronger muscles of the U19 members were responsible for their superior performance in CMJ and
CMJFA when compared with the U17 group. In spite of an increase in the explosive power of leg
muscles, which improved their jumping ability, the U19 players were not faster than the U17 group.
Higher FI in the U19 group suggests that they were unable to maintain the desired speed in repetitive
sprints in comparison with the U17 goalkeepers. Longer DTotal and DAeT by the U19 participants
indicate higher aerobic capacity in U19 handball players than U17 players. More intense and frequent
anaerobic training stimulated the anaerobic glycolytic system in the older group (U19) of handball
players, and this was reﬂected by higher [LA]peak in these players than the U17 participants. The reason
for the limitations of the motor development of goalkeepers of U19 may be slowing down of biological
maturity after 17 years of age [65].
5. Conclusions
The aim of this cross-sectional study was to compare physical ﬁtness and some physiological
characteristics of U17 and U19 Polish handball players with special reference to their position of play.
Players of both the groups were equally taller, but the U19 members were signiﬁcantly heavier than the
U17 participants. Players of all the U19 positions dominate over the U17 players in terms of absolute
power. However, a higher body weight has eliminated these diﬀerences in relative power values.
Increases in body weight and total muscle mass in U19 players were responsible for superior explosive
power, which caused better performance in the jump tests (CMJ and CMJFA) when compared with
U17 players. The players of the U19 group showed lower running eﬃciency up to AeT level and
longer distance covered above AeT than the U17 group. However, the U19 players possessed higher
anaerobic capacity and an eﬃcient glycolytic system compared with the group of U17 players. Players
with higher body weight (U19) worked at a signiﬁcantly higher energy cost level compared with the
players of lower body weight (U17) of similar playing positions.
6. Study Limitations
The research has limitations on its wide use in men’s handball. The training system in a sports
school has strict conditions that are diﬀerent from training in sports clubs. The sports school players
who participated in the research did not diﬀer in the organization of the day, diet, and training loads.
When relating the results of the presented studies to the values obtained in other training groups,
the above limitations, which constitute an integral part of each sports training process, should be taken
into account.
7. Practical Recommendations
Training of U19 groups should be targeted to transfer power into speed. There is a clear increase
in maximum power with a lack of adequate development of running speed at distances important in
handball (5 and 10 m). This is because of the fact that weight gain is not accompanied by an increase
in relative power, so the observed power development is only compensated for by weight gain. It
is also important because of the size of players, which limits their ﬂexibility and ability to change
directions rapidly. Development of endurance and running economy of the players should not be
Int. J. Environ. Res. Public Health 2020, 17, 7979
12 of 15
ignored, while focusing the training on the explosive power and sprinting ability of the players. It is
recommended to increase the training impact at the age of 17–19 towards the development of running
economy and speed increase on the thresholds (AeT and AnT).
Author Contributions: Conceptualization, T.G., A.S., and S.G.; methodology, T.G., A.S., and S.G.; software, U.S.-G.
and J.B.; validation, D.B., Ł.W., and J.B.; formal analysis, A.S., T.G., and D.B.; investigation, T.G., U.S.-G., and D.B.;
resources, T.G. and Ł.W.; data curation, S.G. and J.B.; writing—original draft preparation, T.G., A.S., and S.G.;
writing—review and editing, U.S.-G. and D.B.; visualization, A.S.; supervision, T.G. All authors have read and
agreed to the published version of the manuscript.
Funding: Financed by the project: SGS-2019-011.
Conﬂicts of Interest: The authors declare no conﬂict of interest.
References
1.
Fraser-Thomas, J.L.; Côté, J.; Deakin, J. Youth sport programs: An avenue to foster positive youth development.
Phys. Educ. Sport Pedagog. 2005, 10, 19–40. [CrossRef]
2.
Nideﬀer, R.M.; Sagal, M.S.; Lowry, M.; Bond, J. Identifying and developing world-class performers.
In The Practiceof Sport Psychology; Tenenbaum, G., Morgantown, W., Eds.; Fitness Information Technology:
Morgantown, WV, USA, 2001; pp. 129–144.
3.
Abbott, A.; Button, C.; Pepping, G.J.; Collins, D. Unnatural selection: Talent identiﬁcation and development
in sport. Nonlinear Dyn. Psychol. Life Sci. 2005, 9, 61–88.
4.
Michalsik, L.B.; Aagaard, P.; Madsen, K. Locomotion characteristics and match-induced impairments in
physical performance in male elite team handball players. Int. J. Sports Med. 2013, 34, 590–599. [CrossRef]
5.
Pearson, D.T.; Naughton, G.A.; Torode, M. Predictability of physiological testing and the role of maturation
in talent identiﬁcation for adolescent team sports. J. Sci. Med. Sport 2006, 9, 277–287. [CrossRef]
6.
Vaeyens, R.; Lenoir, M.; Williams, A.M.; Philippaerts, R.M. Talent identiﬁcation and development programmes
in sport: Current models and future directions. Sports Med. 2008, 38, 703–714. [CrossRef]
7.
Marques, M.C.; van den Tilaar, R.; Vescovi, J.D.; Gonzalez-Badillo, J.J. Relationship between throwing velocity,
muscle power, and bar velocity during bench press in elite handball players. Int. J. Sports Physiol. Perform.
2007, 2, 414–422. [CrossRef]
8.
Pori, P.; Kovaˇciˇc, S.; Bon, M.; Dolenec, M.; Šibila, M. Various age category—Related diﬀerences in the volume
and intensity of the large-scale cyclic movements of male players in team handball. Acta Univ. Palacki.
Olomuc. Gymnica 2005, 35, 119–125.
9.
Deutsch, M.U.; Maw, G.J.; Jenkins, D.; Reaburn, P. Heart rate, blood lactate and kinematic data of elite colts
(under-19) rugby union players during competition. J. Sports Sci. 1998, 16, 561–570. [CrossRef] [PubMed]
10.
Krustrup, P.; Mohr, M.; Bangsbo, J. Activity proﬁle and physiological demands of top-class soccer assistant
refereeing in relation to training status. J. Sports Sci. 2002, 20, 861–871. [CrossRef] [PubMed]
11.
Reilly, T. Assessment of sports performance with particular reference to ﬁeld games. Eur. J. Sport Sci. 2001, 1,
1–12. [CrossRef]
12.
Wagner, H.; Orwat, M.; Hinz, M.; Pfusterschmied, J.; Bacharach, D.W.; Von Duvillard, S.P.; Müller, E. Testing
game-based performance in team-handball. J. Strength Cond. Res. 2016, 30, 2794–2801. [CrossRef] [PubMed]
13.
Buchheit, M.; Lepretre, P.M.; Behaegel, A.L.; Millet, G.P.; Cuvelier, G.; Ahmaidi, S. Cardiorespiratory
responses during running and sport-speciﬁc exercises in handball players. J. Sci. Med. Sport 2009, 12, 399–405.
[CrossRef]
14.
Wagner, H.; Fuchs, P.X.; Von Duvillard, S.P. Speciﬁc physiological and biomechanical performance in elite,
sub-elite and in non-elite male team handball players. J. Sports Med. Phys. Fit. 2018, 58, 73–81. [CrossRef]
15.
Ziv, G.; Lidor, R. Physical characteristics, physiological attributes, and on-court performances of handball
players: A review. Eur. J. Sport Sci. 2009, 9, 375–386. [CrossRef]
16.
Chelly, M.S.; Hermassi, S.; Shephard, R.J. Relationships between power and strength of the upper and lower
limb muscles and throwing velocity in male handball players. J. Strength Cond. Res. 2010, 24, 1480–1487.
[CrossRef] [PubMed]
17.
Zapartidis, I.; Vareltzis, I.; Gouvali, M.; Kororos, P. Physical Fitness and Anthropometric Characteristics in
Diﬀerent Levels of Young Team Handball Players. Open Sports Sci. J. 2009, 2, 22–28. [CrossRef]
Int. J. Environ. Res. Public Health 2020, 17, 7979
13 of 15
18.
Karcher, C.; Buchheit, M. On-Court demands of elite handball, with special reference to playing positions.
Sport. Med. 2014, 44, 797–814. [CrossRef] [PubMed]
19.
Krüger, K.; Pilat, C.; Ückert, K.; Frech, T.; Mooren, F.C. Physical performance proﬁle of handball players is
related to playing position and playing class. J. Strength Cond. Res. 2014, 28, 117–125. [CrossRef] [PubMed]
20.
Delamarche, P.; Gratas, A.; Beillot, J.; Dassonville, J.; Rochcongar, P.; Lessard, Y. Extent of lactic anaerobic
metabolism in handballers. Int. J. Sports Med. 1987, 8, 55–59. [CrossRef]
21.
Michalsik, L.B.; Madsen, K.; Aagaard, P. Physiological capacity and physical testing in male elite team
handball. J. Sports Med. Phys. Fit. 2015, 55, 415–429.
22.
Gorostiaga, E.M.; Granados, C.; Ibáñez, J.; González-Badillo, J.J.; Izquierdo, M. Eﬀects of an entire season on
physical ﬁtness changes in elite male handball players. Med. Sci. Sports Exerc. 2006, 38, 357–366. [CrossRef]
23.
Póvoas, S.C.A.; Seabra, A.F.T.; Ascensão, A.A.M.R.; Magalhães, J.; Soares, J.M.C.; Rebelo, A.N.C. Physical
and physiological demands of elite team handball. J. Strength Cond. Res. 2012, 26, 3365–3375. [CrossRef]
[PubMed]
24.
Tanaka, M.; Michalsik, L.; Bangsbo, J. Activity proﬁles during an oﬃcial league game of Danish elite team
handball players. Jpn. J. Phys. Fit. Sport Med. 2002, 15, 61–73.
25.
Sporiš, G.; Vuleta, D.; Milanovi´c, D. Fitness proﬁling in handball: Physical and physiological characteristics
of elite players. Coll. Antropol. 2010, 34, 1009–1014.
26.
Haugen, T.A.; Tønnessen, E.; Seiler, S. Speed and countermovement-jump characteristics of elite female
soccer players, 1995–2010. Int. J. Sports Physiol. Perform. 2012, 7, 340–349. [CrossRef] [PubMed]
27.
Manchado, C.; Tortosa-Martínez, J.; Vila, H.; Ferragut, C.; Platen, P. Performance factors in women’s team
handball: Physical and physiological aspects-a review. J. Strength Cond. Res. 2013, 27, 1708–1719. [CrossRef]
28.
Kvorning, T.; Hansen, M.R.B.; Jensen, K. Strength and Conditioning Training by the Danish National
Handball Team before an Olympic Tournament. J. Strength Cond. Res. 2017, 31, 1759–1765. [CrossRef]
29.
Ingebrigtsen, J.; Jeﬀreys, I.; Rodahl, S. Physical characteristics and abilities of junior elite male and female
handball players. J. Strength Cond. Res. 2013, 27, 302–309. [CrossRef]
30.
Molina-López, J.; Zarzuela, I.B.; Sáez-Padilla, J.; Tornero-Quiñones, I.; Planells, E. Mediation eﬀect of age
category on the relationship between body composition and the physical ﬁtness proﬁle in youth handball
players. Int. J. Environ. Res. Public Health 2020, 17, 2350. [CrossRef]
31.
Roseguini, A.Z.; Da Silva, A.S.R.; Gobatto, C.A. Determinations and Relationships of the RAST Anaerobic
Parameters, Anaerobic Threshold and Lactacidemia Response Obtained at the Beginning, Interval and the
End of an Oﬃcial Handball Match. Rev. Bras. Med. Esporte 2008, 14, 46–50. [CrossRef]
32.
Hermassi, S.; Laudner, K.; Schwesig, R. Playing level and position diﬀerences in body characteristics and
physical ﬁtness performance among male team handball players. Front. Bioeng. Biotechnol. 2019, 7, 149.
[CrossRef] [PubMed]
33.
Burr, J.F.; Jamnik, V.K.; Dogra, S.; Gledhill, N. Evaluation of jump protocols to assess leg power and predict
hockey playing potential. J. Strength Cond. Res. 2007, 21, 1139–1145. [CrossRef] [PubMed]
34.
Petrigna, L.; Karsten, B.; Marcolin, G.; Paoli, A.; D’Antona, G.; Palma, A.; Bianco, A. A Review of
Countermovement and Squat Jump Testing Methods in the Context of Public Health Examination in
Adolescence: Reliability and Feasibility of Current Testing Procedures. Front. Physiol. 2019, 10, 1384.
[CrossRef] [PubMed]
35.
Bosco, C.; Luhtanen, P.; Komi, P.V. A simple method for measurement of mechanical power in jumping.
Eur. J. Appl. Physiol. Occup. Physiol. 1983, 50, 273–282. [CrossRef]
36.
Baron, J.; Bieniec, A.; Swinarew, A.S.; Gabry´s, T.; Stanula, A. Eﬀect of 12-week functional training intervention
on the speed of young footballers. Int. J. Environ. Res. Public Health 2020, 17, 160. [CrossRef]
37.
Zacharogiannis, E.; Paradisis, G.; Tziortzis, S. An evaluation of tests of anaerobic power and capacity. Med. Sci.
Sport Exerc. 2004, 36, 116.
38.
Balˇeiunas, M.; Stonkus, S.; Abrantes, C.; Sampaio, J. Long term eﬀects of diﬀerent training modalities
on power, speed, skill and anaerobic capacity in young male basketball players. J. Sport Sci. Med. 2006,
5, 163–170.
39.
Beltz, N.M.; Gibson, A.L.; Janot, J.M.; Kravitz, L.; Mermier, C.M.; Dalleck, L.C. Graded Exercise Testing
Protocols for the Determination of VO2max: Historical Perspectives, Progress, and Future Considerations. J.
Sports Med. 2016, 2016, 1–12. [CrossRef]
Int. J. Environ. Res. Public Health 2020, 17, 7979
14 of 15
40.
Castagna, C.; Impellizzeri, F.M.; Belardinelli, R.; Abt, G.; Coutts, A.; Chamari, K.; D’Ottavio, S.
Cardiorespiratory responses to Yo-yo Intermittent Endurance Test in nonelite youth soccer players. J. Strength
Cond. Res. 2006, 20, 326–330. [CrossRef]
41.
Hughson, R.L.; Green, H.J. Blood acid-base and lactate relationships studied by ramp work tests. Med. Sci.
Sports Exerc. 1982, 14, 297–302. [CrossRef]
42.
Mader, A.; Liesen, H.; Heck, H.; Philippi, H.; Rost, R.; Schuerch, P.; Hollmann, W. Zur Beurteilung der
sportartspeziﬁschen Ausdauerleistungsfähigkeit im Labor. Sportarzt Sportmed 1976, 27, 109–112.
43.
Hopkins, W.G.; Marshall, S.W.; Batterham, A.M.; Hanin, J. Progressive statistics for studies in sports medicine
and exercise science. Med. Sci. Sports Exerc. 2009, 41, 3–13. [CrossRef] [PubMed]
44.
Gümü¸s, M.; Eler, S. Evaluation of Physical and Physiological Characteristics of the Olympic Champion
Turkish Deaf Men’s National Handball Team. J. Educ. Train. Stud. 2018, 6, 207. [CrossRef]
45.
Schwesig, R.; Hermassi, S.; Fieseler, G.; Irlenbusch, L.; Noack, F.; Delank, K.S.; Shephard, R.J.; Chelly, M.S.
Anthropometric and physical performance characteristics of professional handball players: Inﬂuence of
playing position. J. Sports Med. Phys. Fit. 2017, 57, 1471–1478. [CrossRef]
46.
Rannou, F.; Prioux, J.; Zouhal, H.; Gratas-Delamarche, A.; Delamarche, P. Physiological proﬁle of handball
players. J. Sports Med. Phys. Fit. 2001, 41, 349–353.
47.
Massuca, L.; Branco, B.; Miarka, B.; Fragoso, I. Physical ﬁtness attributes of team-handball players are related
to playing position and performance level. Asian J. Sports Med. 2015, 6, e24712. [CrossRef]
48.
Zakas, A.; Mandroukas, K.; Karamouzis, G.; Panagiotopoulou, G. Physical training, growth hormone and
testosterone levels and blood pressure in prepubertal, pubertal and adolescent boys. Scand. J. Med. Sci. Sports
1994, 4, 113–118. [CrossRef]
49.
Malina, R.M.; Bouchard, C.; Bar-Or, O. Growth, Maturation, and Physical Activity, 2nd ed.; Human Kinetics:
Champaign, IL, USA, 2004; ISBN 0880118822.
50.
Gorostiaga, E.M.; Izquierdo, M.; Iturralde, P.; Ruesta, M.; Ibáñez, J. Eﬀects of heavy resistance training on
maximal and explosive force production, endurance and serum hormones in adolescent handball players.
Eur. J. Appl. Physiol. Occup. Physiol. 1999, 80, 485–493. [CrossRef]
51.
Michalsik, L.B. On-Court Physical Demands and Physiological Aspects in Elite Team Handball. In Handball
Sports Medicine; Springer: Berlin/Heidelberg, Germany, 2018; pp. 15–33.
52.
Reverter-Masía, J.; Legaz-Arrese, A.; Munguía-Izquierdo, D.; Barbany, J.R.; Serrano-Ostáriz, E. A proﬁle of
the resistance training practices of elite Spanish club teams. J. Strength Cond. Res. 2009, 23, 1537–1547.
53.
Cardinale, M.; Whiteley, R.; Hosny, A.A.; Popovic, N. Activity proﬁles and positional diﬀerences of handball
players during the world championships in Qatar 2015. Int. J. Sports Physiol. Perform. 2017, 12, 908–915.
[CrossRef]
54.
Buchheit, M.; Mendez-Villanueva, A.; Quod, M.; Quesnel, T.; Ahmaidi, S. Improving acceleration and
repeated sprint ability in well-trained adolescent handball players: Speed versus sprint interval training.
Int. J. Sports Physiol. Perform. 2010, 5, 152–164. [CrossRef]
55.
Spencer, M.; Bishop, D.; Dawson, B.; Goodman, C. Physiological and metabolic responses of repeated-sprint
activities:speciﬁc to ﬁeld-based team sports. Sports Med. 2005, 35, 1025–1044. [CrossRef]
56.
Ferrari Bravo, D.; Impellizzeri, F.M.; Rampinini, E.; Castagna, C.; Bishop, D.; Wisloﬀ, U. Sprint vs. interval
training in football. Int. J. Sports Med. 2008, 29, 668–674. [CrossRef] [PubMed]
57.
Burgomaster, K.A.; Howarth, K.R.; Phillips, S.M.; Rakobowchuk, M.; Macdonald, M.J.; Mcgee, S.L.; Gibala, M.J.
Similar metabolic adaptations during exercise after low volume sprint interval and traditional endurance
training in humans. J. Physiol. 2008, 586, 151–160. [CrossRef] [PubMed]
58.
Gibala, M.J.; Little, J.P.; van Essen, M.; Wilkin, G.P.; Burgomaster, K.A.; Safdar, A.; Raha, S.; Tarnopolsky, M.A.
Short-term sprint interval versus traditional endurance training: Similar initial adaptations in human skeletal
muscle and exercise performance. J. Physiol. 2006, 575, 901–911. [CrossRef]
59.
Barnes, K.R.;
Kilding, A.E. Running economy:
Measurement, norms, and determining factors.
Sports Med. Open 2015, 1, 1–15. [CrossRef]
60.
Sporiš, G.; Vuˇceti´c, V.; Milanovi´c, L.; Milanovi´c, Z.; Krespi, M.; Krakan, I. A comparison anaerobic endurance
capacity in elite soccer, handball and basketball players. Kinesiology 2014, 46, 52–59.
61.
Kukolj, M.; Ropret, R.; Ugarkovic, D.; Jaric, S. Anthropometric, strength, and power predictors of sprinting
performance. J. Sports Med. Phys. Fit. 1999, 39, 120–122.
Int. J. Environ. Res. Public Health 2020, 17, 7979
15 of 15
62.
Young, W.; McLean, B.; Ardagna, J. Relationship between strength qualities and sprinting performance.
J. Sports Med. Phys. Fit. 1995, 35, 13–19.
63.
Massuça, L.M.; Fragoso, I.; Teles, J. Attributes of top elite team-handball players. J. Strength Cond. Res. 2014,
28, 178–186. [CrossRef]
64.
Hansen, C.; Sanz-Lopez, F.; Whiteley, R.; Popovic, N.; Ahmed, H.A.; Cardinale, M. Performance analysis
of male handball goalkeepers at the world handball championship 2015. Biol. Sport 2017, 34, 393–400.
[CrossRef] [PubMed]
65.
Havolli, J. Comparison between Some Morphological Characteristics and Motor Tests of Young Handball
and Football Goalkeepers. J. Phys. Fit. Med. Treat. Sport 2018, 3. [CrossRef]
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