818 Training & Testing
Authors
M. Buchheit, A. Mendez-Villanueva, B. M. Simpson, P. C. Bourdon
Affiliations
Physiology Unit, Sport Science Department, ASPIRE, Academy for Sports Excellence, Doha, Qatar
Key words
▶ football
●
▶ high-intensity running
●
▶ field tests
●
▶ adolescents
●
▶ global positioning system
●
Abstract
▼
accepted after revision
July 05, 2010
Bibliography
DOI http://dx.doi.org/
10.1055/s-0030-1262838
Published online:
August 11, 2010
Int J Sports Med 2010; 31:
818–825 © Georg Thieme
Verlag KG Stuttgart · New York
ISSN 0172-4622
Correspondence
Dr. Martin Buchheit
Physiology Unit, Sport Science
Department
ASPIRE, Academy for Sports
Excellence
P.O. Box 22287, Doha
Qatar
Tel.: + 974/4413/6103
Fax: + 974/4413/6060
[email protected]
The activity profiles of highly trained young soccer players were examined in relation to age,
playing position and physical capacity. Timemotion analyses (global positioning system) were
performed on 77 players (U13–U18; fullbacks
[FB], centre-backs [CB], midfielders [MD], wide
midfielders [W], second strikers [2ndS] and strikers [S]) during 42 international club games. Total
distance covered (TD) and very high-intensity
activities (VHIA; > 16.1 km · h − 1) were computed
during 186 entire player-matches. Physical capacity was assessed via field test measures (e. g., peak
running speed during an incremental field test,
VVam-eval). Match running performance showed
an increasing trend with age (P < 0.001, partial
Introduction
▼
Most professional soccer academies are seeking
to optimize the early detection and physical
development of their young players [39]. The
assessment of the physical determinants of running performance during competitive matches
according to age and playing position is therefore
required to improve talent detection procedures
and long-term training interventions. Nevertheless, while some information is available about
the physical and physiological demands of highly
trained young soccer players during match play
[6, 9, 10, 17, 40], little is known about whether
physical capacities are important determinants
of physical match performance in these players.
Several studies have reported significant correlations between field or laboratory test results and
running performance during soccer matches,
suggesting that individual physical capacities can
account for game-related physical performance
[10, 17, 23, 34]. For example, in professional male
soccer players, significant correlations have been
eta-squared (η2): 0.20–0.45). When adjusted for
age and individual playing time, match running
performance was position-dependent (P < 0.001,
η2: 0.13–0.40). MD covered the greater TD; CB the
lowest (P < 0.05). Distance for VHIA was lower for
CB compared with all other positions (P < 0.05); W
and S displayed the highest VHIA (P < 0.05). Relationships between match running performance
and physical capacities were position-dependent, with poor or non-significant correlations
within FB, CB, MD and W (e. g., VHIA vs. VVam-eval:
r = 0.06 in FB) but large associations within 2ndS
and S positions (e. g., VHIA vs. VVam-eval: r = 0.70 in
2ndS). In highly trained young soccer players, the
importance of fitness level as a determinant of
match running performance should be regarded
as a function of playing position.
reported between distance covered at high intensity during a match and both peak running speed
during an incremental field test and mean sprint
time on a repeated sprint ability (RSA) test [34].
Maximal oxygen uptake [23] and maximal performance for the Yo-Yo Intermittent Recovery
Tests were also shown to correlate well with the
amount of high intensity activities during games
in adult females [23] and young male players
[10]. However, these relationships have consistently been reported with all players from a team
pooled together; none of the aforementioned
studies considered the correlation between
match running performance and physical capacities with regard to playing positions.
In young [40] and in top-level adult soccer players [5, 13, 14, 35], match analyses have demonstrated that match running performance, and
especially high-intensity running, are positiondependent. Centre-backs generally undertake
less high-intensity running, whereas midfielders
and attackers generally display the most
[5, 13, 14, 35]. Therefore, if physical capacities
Buchheit M et al. Match Running Performance and Fitness in Youth Soccer. Int J Sports Med 2010; 31: 818–825
Downloaded by: Koebenhavns Universitetsbibliotek. Copyrighted material.
Match Running Performance and Fitness in Youth
Soccer
Training & Testing 819
▶ Table 1). All
Under 13 to Under 18 in an elite soccer academy (●
the players participated on average in ~14 h of combined soccerspecific training and competitive play per week (6–8 soccer
training sessions, 1 strength training session, 1–2 conditioning
sessions, 1 domestic game per week and 2 international club
games every 3 weeks). All players had a minimum of 3 years of
prior soccer-specific training. Written informed consent was
obtained from the players and their parents. The study was performed in accordance with the ethical standards of the IJSM [16]
and conformed to the Declaration of Helsinki.
Anthropometric measurements and maturity
assessment
Height (Harpenden, Baty International, Burguess Hill, U.K.), body
mass (ADE Electronic Column Scales, Hamburg, Germany) and
the sum of 7 skinfold sites (triceps, subscapular, biceps, supraspinale, abdominal, thigh and medial calf; Harpenden skinfold
caliper (Baty International, Burguess Hill, U.K.) were measured
by an experienced tester [26]. Although the teams differed in
chronological age, the possibility of an overlapping of some players’ maturity status was likely given the heterogeneity of biological and physical maturity of children around puberty [25].
The age at peak height velocity (PHV) is an indicator of somatic
maturity representing the time of maximum growth in stature
during adolescence. Maturity timing (yr) was calculated by subtracting the chronological age at the time of measurement from
the age at estimated PHV [28].
Experimental procedures
Methods
▼
Subjects
Time-motion match analysis data was collected on 99 young
football players belonging to 6 different age groups ranging from
Match analyses were performed on 42 matches against international club teams, played over a 4-month period. Each outfield
player was assessed 1–9 times. The high level of the opposing
teams and the same competition format likely reduced match-
Table 1 Physical capacities and match running performance according to age.
U13
U14
number of players
year from PHV
height (cm)
body mass (kg)
CMJ (cm)
Acc (s)
PV (km.h − 1)
RSAmean
VVam-eval (km.h − 1)
n=7
− 1.7 ± 0.4a,b,c,d,e
150 ± 6a,b,c,d,e
39.3 ± 5.1b,c,d,e
27.5 ± 2.5a,b,c,d,e
1.96 ± 0.07a,b,c,d,e
25.4 ± 0.7a,b,c,d,e
5.15 ± 0.08a,b,c,d,e
13.7 ± 0.8a,b,c,d,e
number of files
playing time
TD (m)
LIR (m)
HIR (m)
VHIR (m)
Sprinting (m)
VHIA (m)
peak game speed (km.h − 1)
n = 18 files
2 × 35 min
6549 ± 597a,b,c,d,e
5370 ± 470b,c,d,e
671 ± 180b,c,d,e
323 ± 87b,c,d,e
186 ± 92b,c,d,e
509 ± 156a,b,c,d,e
22.3 ± 1.4a,b,c,d,e
U15
U16
anthropometric, maturity data and physical capacities
n = 17
n = 10
n = 12
− 0.7 ± 0.5c,d,e
− 0.1 ± 0.7d,e
0.6 ± 0.8d,e
159 ± 7d,e
161 ± 6d,e
163 ± 9
43.9 ± 5.2d,e
48.8 ± 9.8d
52.0 ± 7.2
32.0 ± 3.1b,c,d,e
39.2 ± 4.1d,e
37.9 ± 3.7d,e
1.89 ± 0.06b,c,d,e
1.79 ± 0.08d,e
1.77 ± 0.05e
b,c,d,e
d,e
27.0 ± 1.5
29.0 ± 1.8
29.4 ± 1.0d,e
4.88 ± 0.16b,c,d,e
4.60 ± 0.20d,e
4.51 ± 0.12e
15.3 ± 1.4d,e
15.8 ± 1.3e
15.8 ± 1.1e
match running performance
n = 40 files
n = 25 files
n = 21 files
2 × 35 min
2 × 40 min
2 × 40 min
7383 ± 640b,c,d,e
8129 ± 879e
8312 ± 1054
5799 ± 454b,c,d,e
6288 ± 610
6480 ± 845
821 ± 231
954 ± 297
968 ± 258
446 ± 162e
477 ± 156
479 ± 180
318 ± 183e
410 ± 204e
384 ± 163e
d,e
e
763 ± 307
887 ± 311
864 ± 314e
24.4 ± 1.8b,c,d,e
26.0 ± 2.4e
26.3 ± 2.3e
U17
U18
η2
n = 17
1.6 ± 0.6e
170 ± 7
58.1 ± 4.7
42.6 ± 4.0
1.74 ± 0.04
31.3 ± 0.7e
4.39 ± 0.12
16.6 ± 0.9
n = 14
2.2 ± 0.4
171 ± 9
56.3 ± 7.5
44.5 ± 5.2
1.71 ± 0.06
32.3 ± 1.9
4.31 ± 0.17
17.4 ± 0.9
0.83
0.58
0.51
0.69
0.67
0.74
0.78
0.51
n = 29 files
2 × 40 min
8707 ± 1101
6749 ± 768
991 ± 370
519 ± 155
449 ± 147e
967 ± 221e
26.6 ± 2.2e
n = 53 files
2 × 45 min
8867 ± 859
6650 ± 565
976 ± 240
574 ± 134
666 ± 256
1239 ± 337
28.3 ± 2.2
0.44
0.36
0.28
0.20
0.39
0.39
0.45
Mean ( ± SD) values of anthropometric and match running performances and least squared means ( ± SE) of physical capacities of the Under 13 (U13), Under 14 (U14), Under 15
(U15), Under 16 (U16), Under 17 (U17) and Under 18 (U18) soccer players. PHV peak height velocity. Field tests: counter movement jump (CMJ), acceleration (Acc), peak velocity (PV), mean sprint time on the repeated sprint test (RSAmean) and peak running speed during the incremental field test (VVam-eval). Match running performance: total distance
covered (TD), low-intensity running (LIR; running speed < 13.0 km · h − 1 ), high-intensity running (HIR; running speed from 13.1 to 16 km · h − 1 ), very high-intensity running
(VHIR; running speed from 16.1 to 19 km · h − 1 ) and sprinting distance (Sprinting; running speed > 19.1 km · h − 1 ). Very high-intensity activities (VHIA) = VHIR + Sprinting. Main
age-group effect: all P < 0.001. a: significant difference vs. U14 (P < 0.05), b: vs. U15, c: vs. U16, d: vs. U17, e: vs. U18. η2 : effect size
Buchheit M et al. Match Running Performance and Fitness in Youth Soccer. Int J Sports Med 2010; 31: 818–825
Downloaded by: Koebenhavns Universitetsbibliotek. Copyrighted material.
were to significantly account for match running performance,
irrespective of playing positions [10, 23, 34], centre-backs would
be expected to consistently present the poorest physical tests
results, and conversely, midfielders and attackers, the best ones.
While between-position differences in physical capacities have
been reported for some physical capacities [15, 22, 44], such differences are not always apparent [20] or even absent [41]. For
example, while fullbacks performed more distance in the Yo-Yo
test than attackers [22], the mean sprint time on the RSA test
conducted by Impellizzeri et al. [20] did not discriminate fullbacks, midfielders and forwards, despite the important differences in their match running performance [5, 13, 14, 35]. It is
therefore unclear to what extent physical fitness and/or specific
technical/tactical roles assigned to each playing position and
playing style can dictate player’s running activity during the
game. In addition, given the reported existence of different position-specific running patterns [13], it is also unclear which physical capacities (e. g., lower limb explosive strength, maximal
aerobic function, RSA [34]) are related with match running performance for a given playing position.
The purpose of this study was therefore to 1) examine for the first
time match running performance in a wide age range of highly
trained young soccer players as a function of age and playing position, 2) determine whether individual differences in match running performances are related to differences in physical capacities
(as evidenced via field tests results), and 3) evaluate the magnitude of these relationships for each separate playing position.
820 Training & Testing
Activity pattern measurements
Materials
A Global Positioning System (GPS) unit capturing data at 1 Hz
(SPI Elite, GPSports, Canberra, Australia) was fitted to the upper
back of each player using an adjustable neoprene harness. All
players, irrespective of age, wore the same equipment and the
same GPS devices. Despite a possible underestimation of highintensity running distance with the time-resolution of 1 Hz [37],
good accuracy (r = 0.97) was reported for the assessment of short
sprints for this GPS device compared with an infra-red timing
system [4]. While the accuracy of the device for total distance
has been reported to be good (3–7 %), that for high-intensity
running is only moderate (11–30 %) [12]. However, in the absence
of “a gold standard” method, the current system has been
reported to be capable of measuring individual movement patterns in soccer [37]. More importantly for this study design, the
GPS device utilized has been reported to have good reliability
(i. e., CV = 1.7 % [4] and < 5 % [12]). Despite possible between-GPS
variability [31], we were confident in the results observed since
players always wore the same device.
Analyses
While 635 player-matches were assessed in total from 99 different players, only data from players who participated in the
full game were retained (n = 186 files from 77 different
▶ Table 1). This unfortunately resulted in a small data
players, ●
set for the U13 players (n = 7), which was largely a consequence
of the high substitution rate of players during games in this age
group. Tactically, all teams used a 4-4-1-1 formation, a variation
of 4-4-2 with 1 of the strikers playing as a “second striker”,
slightly behind their partner. Since players’ roles within the team
structure changed little during the games analysed, all players
were assigned to 1 of 6 positional groups; fullbacks (FB, n = 15
players, yielding 36 files), centre-backs (CB, n = 16 players, yielding 54 files), midfielders (MD, n = 13 players, yielding 40 files),
wide midfielders (W, n = 13 players, yielding 16 files), second
strikers (2ndS, n = 9 players, yielding 19 files) and strikers (S,
n = 11 players, yielding 21 files). All match data was analysed
with a custom-made Microsoft Excel program designed to provide objective measures of physical match performance. Activity
ranges selected for analysis were identical for all categories to
allow direct between-age comparisons and were adapted from
previous studies on young soccer players [6, 10] as follows: 1)
total distance covered (TD), 2) low-intensity running (LIR; running speed < 13.0 km.h − 1), 3) high-intensity running (HIR; running speed from 13.1 to 16 km.h − 1), 4) very high-intensity
running (VHIR; running speed from 16.1 to 19 km.h − 1) and 5)
sprinting distance (Sprinting; running speed > 19.1 km.h − 1).
Very high-intensity activities (VHIA) were also calculated as
VHIR plus Sprinting. Peak game running speed (i. e., the highest
speed recorded during the game) was also collected. While previous studies have also analysed match running for fixed intervals throughout the game (e. g., 15-min periods) or reported the
duration and occurrences of specific actions to assess fatigue
development [5, 8], we restricted our analyses to the game as a
whole so as to focus on possible differences in match running
performance as a function of age, playing position and physical
fitness.
Physical performance assessment
Since football-specific tests (i. e., which replicate soccer movement patterns and efforts, such as Hoff [18], Yo-Yo [22] and
shuttle RSA [20] tests) evaluate different physical qualities
simultaneously (e. g., the performance at the Yo-Yo IR1 test is the
results of, among others, cardiovascular fitness, intra-effort
recovery capacities and change of direction ability), we chose,
for the purpose of the present study, simple performance tests to
evaluate and isolate basic physical qualities of each player.
Lower limb explosive strength
A vertical countermovement jump (CMJ; cm) with flight time
measured with a contact mat (KMS, Fitness Technology, South
Australia) to calculate jump height was used to assess lower limb
explosive strength. Players were instructed to keep their hands
on their hips with the depth of the counter movement selfselected. Each trial was validated by visual inspection to ensure
each landing was without significant leg flexion. Athletes were
encouraged to perform each jump maximally. At least 3 valid
CMJ’s were performed separated by 25 s of passive recovery,
with the best performance recorded.
Acceleration and peak running velocity
The player’s acceleration (Acc) as measured by their 10 m sprint
time and their peak running velocity (PV) defined as the fastest
10-m split time were measured during a maximal 40-m sprint
(dual-beam electronic timing gates set at 10-m intervals, Swift
Performance Equipment, Lismore, Australia) [27]. Split times
were measured to the nearest 0.01 s. Players commenced each
sprint from a standing start with their front foot 0.5 m behind
the first timing gate and were instructed to sprint as fast as possible over the 40-m distance. The players started when ready,
thus eliminating reaction time and completed 2 trials with the
best performances used as the final result.
Repeated-sprint performance
All players performed a RSA test following a 10-min rest break
after the 40-m sprint trials. The RSA test consisted of 10 repeated
straight-line 30-m sprints separated by 30 s of active recovery
(i. e., jogging back to the starting line within approx 25 s, in order
to allow 4–5 s of passive recovery before the commencement of
the next sprint repetition). This test is similar to other RSA tests
previously used with team sport athletes [33]. Time was recorded
to the nearest 0.01 s using 2 sets of electronic timing gates (Swift
Performance Equipment, Lismore, Australia). Players used a
standing start 0.5 m behind the timing lights. Players were given
verbal encouragement to run as fast as possible for each of the
10 sprints and constant verbal feedback was provided during the
Buchheit M et al. Match Running Performance and Fitness in Youth Soccer. Int J Sports Med 2010; 31: 818–825
Downloaded by: Koebenhavns Universitetsbibliotek. Copyrighted material.
by-match variability in running performance [35]. All matches
were played on two 100 × 70 m standard outdoor natural grass
fields with 11 players per side. Playing time was 2 × 35 min for
U13 and U14, 2 × 40 min for U15, U16 and U17, and 2 × 45 min for
U18. Since growth can potentially influence physical performance [25], all performance tests were reassessed at least once
during the 4-month investigation period. To avoid fatigue unduly
influencing the results, performance tests were performed over
2 testing sessions with at least 1 day between them. Speed and
jump tests were completed on the first day, while the incremental running test was performed in the second testing session. All
performance tests were performed in an indoor facility maintained at standard environmental conditions (23–24 ° C). All
testing sessions were preceded by a 20-min standardized warmup and players were familiar with all test procedures.
Training & Testing 821
Incremental field test
A modified version of the University of Montreal Track Test [24]
(i. e., Vam-eval) was used to assess cardiorespiratory fitness [27].
Compared with other intermittent tests such as the Yo-Yo test,
this test is a better predictor of maximal oxygen uptake, i. e., the
correlation between maximal running speed and maximal oxygen uptake is 0.96 [24], while it is only 0.70 for Yo-Yo vs. maximal oxygen uptake [2]. The test begins with an initial running
speed of 8 km · h − 1 with consecutive speed increases of
0.5 km · h − 1 each minute until exhaustion. The players adjusted
their running speed according to auditory signals timed to match
20-m intervals delineated by cones around a 200-m long indoor
athletics track. The test ended when participants twice failed to
reach the next cone in the required time. During the test, players
were verbally encouraged by testers and coaches. The average
velocity of the last 1-min completed was recorded as the players’
VVam-eval (km.h − 1). If the last stage was not fully completed, the
VVam-eval was calculated as VVam-eval = V + (t/60 · 0.5), where V is the
last completed velocity in km.h − 1 and t is the time in seconds of
the uncompleted stage [27].
Statistical analysis
Data are presented as means ± standard deviations (SD) or
means ± standard errors (SE) when stated. The distribution of
each variable was examined with the Kolmogorov-Smirnov normality test. Homogeneity of variance was verified with a Levene
test. To increase statistical power, the effect of age and playing
position on match running performance was analysed separately. The effect of age on match running performance was first
assessed with a 1-way ANOVA. To account for differences in playing time between age-groups (i. e., 70 vs. 90 min for U13 vs. U18,
respectively), match running performance was also analysed by
ANCOVA, with each data adjusted for individual playing time.
Between-position differences in physical capacities were examined with a 1-way ANCOVA, with data adjusted for age. A separate 1-way ANCOVA was also used to examine the effect of
playing position on match running performance, with data
adjusted for both age and playing time. For all analyses, when a
Distance covered (m)
9000
8000
LIR
HIR
c,d,e
8436±156 8448±135
8254±118
7956±128 8026±143 394±43 e 428±37 e
7497±196 363±35 e 402±39 e
260±53 e
7000
VHIR
Sprinting
484±26
387±40
922±46
487±32
501±28
991±56
946±48
470±29
617±32
533±24
936±51
869±42
837±70
6000
c,d
5000
6012±142
6187±93 6218±103 6565±113 6573±98
6235±85
4000
U13
U14
U15
U16
U17
U18
Fig. 1 Least squared means ( ± SE) for match running performance in
U13 (n = 18 files), U14 (n = 40 files), U15 (n = 25 files), U16 (n = 21 files),
U17 (n = 29 files) and U18 (n = 53 files) soccer players. Values are adjusted
for total playing time. a: significant difference vs. U14 (P < 0.05), b: vs.
U15, c: vs. U16, d: vs. U17, e: vs. U18.
significant interaction was found, Bonferroni’s post hoc tests
were applied. For each ANCOVA, partial eta-squared (η2) was
calculated as measures of effect size. Values of 0.01, 0.06 and
above 0.15 were considered as small, medium and large, respectively [11]. The relationships between match running performance and each physical quality were assessed using partial
correlations adjusted for age and individual playing time. This
was performed with all players pooled and also within each
playing position. In addition to measures of statistical significance, the following criteria were adopted to interpret the magnitude of the correlation (r) between test measures: < 0.1, trivial;
> 0.1–0.3, small; > 0.3–0.5, moderate; > 0.5–0.7, large; > 0.7–0.9,
very large; and > 0.9–1.0, almost perfect. If the 90 % confidence
limits overlapped, small positive and negative values for the
magnitude were deemed unclear; otherwise that magnitude
was deemed to be the observed magnitude [19]. All analyses
were carried out with Minitab 14.1 (Minitab Inc, Paris, France)
and SPSS 12.0 (SPSS Inc, Chicago, USA) software with the level of
significance set at P ≤ 0.05.
Results
▼
Age-related match running performances accounting for actual
▶ Table 1. There was a trend for the
playing times are detailed in ●
older players to cover greater TD and more distance in all running categories (e. g., η2 = 0.44 for TD, and all P < 0.01). U16, U17
and U18 only differed in the distance at VHIA, which was significantly higher for the U18 (P < 0.05). When adjusted for indi▶ Fig. 1), between-age group differences
vidual playing time (●
were less evident (i. e., η2 values were 0.10, 0.10, 0.03, 0.05 and
0.17 for TD, LIR, HIR, VHIR and Sprinting, respectively, all P < 0.05).
U18 displayed higher total sprinting distance than all other
teams (P < 0.05). U13 covered less TD than U16, U17 and U18 and
less LIR than U14 and U15 (P < 0.05).
Players’ physical capacities, according to their playing position
▶ Table 2. There were no
and adjusted by age, are presented in ●
position-differences in Acc (P = 0.16) and the magnitude of the
differences was rated as ‘medium’ for VVam-eval. Strikers tended to
have the best physical capacities, while FB and CB, the weakest.
Between-position differences varied as a function of the physical capacities considered (e. g., MD have worse RSAmean values
than W and 2ndS despite similar VVam-eval).
Position-related match running differences in performance,
adjusted by age and playing time, were all rated as ‘large’
▶ Table 2). CB presented the lowest TD, which was associated
(●
with the lowest VHIA values compared with all other positions
(P < 0.05). Conversely, MD, 2ndS and S covered the greatest TD
(P < 0.05); W and S showing the highest VHIA values (P < 0.05).
The correlations between match running performances and
▶ Fig. 2. When players were all
physical capacities are shown in ●
pooled together, TD was only significantly related to VVam-eval;
VHIA was significantly related to CMJ, PV, RSAmean and VVam-eval.
However, all correlations were only small to moderate (e. g.,
r = ranging from 0.17 (90 % CI, 0.05; 0.29) for VHIA vs. PV to 0.41
(0.30; 0.51) for VHIA vs. VVam-eval). Relationships between match
running performance and physical capacities were more clearly
position-dependent, with trivial and non-significant correlations for FB, CB, MD and W (e. g., VHIA vs. VVam-eval: r = 0.06
( − 0.22; 0.33) and 0.022 ( − 0.01; 0.43) in FB and CB) but large
associations for 2ndS and S (e. g., VHIA vs. VVam-eval: r = 0.70 (0.43;
Buchheit M et al. Match Running Performance and Fitness in Youth Soccer. Int J Sports Med 2010; 31: 818–825
Downloaded by: Koebenhavns Universitetsbibliotek. Copyrighted material.
recovery run. Mean repeated-sprint time (RSAmean) was determined as a measure of repeated-sprint performance.
822 Training & Testing
FB
number of players
height (cm)
body mass (kg)
year from PHV
CMJ (cm)
Acc (s)
PV (km.h − 1)
RSAmean
VVam-eval (km.h − 1)
CB
n = 15
163 ± 11
50.6 ± 9.8
0.5 ± 1.5
36.0 ± 0.7a,c,e
1.81 ± 0.01
28.7 ± 0.2a,c,e
4.73 ± 0.03a,c,e
15.8 ± 0.2
number of files
n = 36 files
TD (m)
8118 ± 103a,b
LIR (m)
6197 ± 81b
HIR (m)
909 ± 33a,b
VHIR (m)
525 ± 20a
Sprinting (m)
487 ± 27a,b,e
VHIA (m)
1012 ± 41a,e
25.9 ± 0.3b,e
peak game speed (km.h − 1)
MD
2ndS
W
anthropometric and maturity data and physical capacities
n = 16
n = 13
n = 13
n=9
166 ± 8
164 ± 9
163 ± 9
159 ± 10
53.8 ± 8.6
51.6 ± 7.4
53.2 ± 10.0
50.1 ± 7.8
0.4 ± 1.1
0.6 ± 1.3
0.6 ± 1.3
− 0.6 ± 1.2
38.7 ± 0.6e
36.8 ± 0.6e
40.3 ± 1.0
37.6 ± 1.0e
1.78 ± 0.01
1.81 ± 0.01
1.79 ± 0.01
1.82 ± 0.01
30.0 ± 0.2b
29.0 ± 0.2e
30.0 ± 0.4
29.0 ± 0.3e
4.59 ± 0.02
4.65 ± 0.03c,e
4.51 ± 0.04
4.60 ± 0.04
15.6 ± 0.2c
16.3 ± 0.2
16.8 ± 0.3
16.0 ± 0.3
match running performance
n = 54 files
n = 40 files
n = 16 files
n = 19 files
7675 ± 84b,c,d
8665 ± 98e
8469 ± 155e
8429 ± 143e
6197 ± 66 b
6638 ± 77e
6231 ± 122
6524 ± 112e
732 ± 27b,c,d,e
1150 ± 32d,e
1037 ± 50e
988 ± 46e
363 ± 16b,c,d,e
552 ± 19
612 ± 30
514 ± 27
384 ± 22c,e
325 ± 26c,e
581 ± 41d
403 ± 38e
747 ± 33c,e
877 ± 38c,e
1200 ± 61d
917 ± 56e
26.4 ± 0.2b,e
24.6 ± 0.3c,e
27.0 ± 0.5
25.6 ± 0.4e
P
η2
n = 11
163 ± 10
51.3 ± 13.4
− 0.1 ± 1.5
42.4 ± 0.9
1.78 ± 0.01
30.7 ± 0.3
4.51 ± 0.03
16.1 ± 0.3
0.35
0.63
0.20
< 0.001
0.16
< 0.001
< 0.001
0.01
0.06
0.04
0.07
0.21
0.05
0.21
0.20
0.09
n = 21 files
7834 ± 136
5867 ± 106
766 ± 44
516 ± 26
686 ± 36
1202 ± 53
28.0 ± 0.4
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
< 0.001
0.29
0.20
0.40
0.35
0.33
0.32
0.13
S
Mean anthropometric ( ± SD) values and least squared means ( ± SE) for counter movement jump (CMJ), acceleration (Acc), peak velocity (PV), mean sprint time on the repeated
sprint test (RSAmean) and peak running speed during the incremental field test (VVam-eval), total distance (TD), low-intensity running (LIR), high-intensity running (HIR), very-highintensity running (VHIR), sprint running (Sprinting), very-high-intensity running activities (VHIA) and peak game speed reached as a function of playing position (fullbacks (FB),
centre-backs (CB), midfielders (MD), wide midfielders (W), second strikers (2nd S) and strikers (S)). Values are adjusted for age and playing time. a: significant difference vs. CB
(P < 0.05), b: vs. MD, c: vs. W, d: vs. 2nd S, e: vs. S. η2 : effect size
TD
VHIA
FB
FB
*
CB
CB
*
MD
MD
W
W
2ndS
*
S
*
**
*
CMJ
Acc
PV
RSAmean
VVam-eval
**
All pooled
Sprinting
FB
CB
**
*
**
*
**
**
* **
**
**
S
All pooled
Peak game Speed
**
**
*
**
*
*
*
**
FB
**
**
CB
MD
MD
W
W
**
**
**
**
Partial correlation coefficient (90% CI)
S
Almost perfect
Large
Very large
Small
Moderate
-0.9 -0.7 -0.5 -0.3 -0.1 0.1 0.3 0.5 0.7 0.9
Small
Almost perfect
Large
Very large
Small
Moderate
Small
Trivial
Large
Moderate
Very large
Almost perfect
-0.9 -0.7 -0.5 -0.3 -0.1 0.1 0.3 0.5 0.7 0.9
**
2ndS
All pooled
**
**
Trivial
**
Very large
All pooled
*
**
**
**
**
Large
S
*
*
**
Moderate
**
***
*
**
**
Almost perfect
2ndS
2ndS
Fig. 2 Correlation coefficients (90 % confidence
intervals, CI) between match running performance and performance in field tests, adjusted for
age and individual playing time. Match running
performance: total distance (TD), very-high-intensity running activities (VHIA), sprint running
(Sprinting) and peak game speed reached during
the game. Playing positions: fullbacks (FB, n = 36
files), centre-backs (CB, n = 54 files), midfielders
(MD, n = 40 files), wide midfielders (W, n = 16 files),
second strikers (2nd S, n = 19 files) and strikers (S,
n = 21 files). Field tests: counter movement jump
(CMJ), acceleration (Acc), peak velocity (PV), mean
sprint time on the repeated sprint test (RSAmean)
and peak running speed during the incremental
field test (VVam-eval). * P < 0.05 ; ** P < 0.01.
Partial correlation coefficient (90% CI)
0.86) and 0.64 (0.35; 0.82) in 2ndS and S; VHIA vs. RSAmean:
r = 0.66 ( − 0.83; − 0.36) in 2ndS).
Discussion
▼
This is the first time that the activity profiles of highly trained
young soccer players are reported in relation to age, playing
position and physical capacities. The main findings of the present
study were: 1) match running performance was slightly affected
by age, with differences only apparent between the extreme age
groups, 2) match running performance was also playing posi-
tion-dependent, with the centre-backs tending to cover less distance, 3) match running performance tended to be related to
most physical capacities, but 4) the magnitude of the relationships between match running performance and physical capacities (i. e., r values) varied considerably according to physical
capacities and playing positions.
Since physical capacities are known to improve with growth
[30, 32], and given the observed age-differences in field test
▶ Table 1), we expected a gradual increase in match
results (●
running performance with age. This was apparent when consid▶ Table 1), due largely to the younger
ering actual playing time (●
age groups playing shorter games than their older counterparts.
Buchheit M et al. Match Running Performance and Fitness in Youth Soccer. Int J Sports Med 2010; 31: 818–825
Downloaded by: Koebenhavns Universitetsbibliotek. Copyrighted material.
Table 2 Physical capacities and match running performance according to playing positions.
However, when adjusted for individual playing time, there was
no difference in running performance between U14, U15, U16
and U17; differences in TD were only significant for the youngest
(U13) vs. the 3 oldest teams (U16, U17 and U18), while the U18
differed from the younger teams (U14-U17) only by their greater
▶ Fig. 1). While we are not aware of any
total sprinting distance (●
comparable data in the literature, these small age-related differences are in line with the lack of difference observed in game
activity patterns between pre- and post pubertal elite soccer
players [40]. A possible overlapping of some players’ maturity
status between teams (as exemplified by the high standard devi▶ Table 1) might also explain the
ations of the mean PHV values, ●
lack of between-team differences observed. These betweenteam comparisons were however not adjusted for PHV to remain
consistent with the way players are classified in soccer clubs.
The present results therefore suggest for the first time that age/
maturation itself (and the associated increase in physical capacities) is not a major determinant of actual match running
performance in soccer. While speculative, it can be hypothesized
that the complexity of the game itself may constrain a player’s
actual running activity, with older players, due to their greater
levels of experience, playing more tactically demanding games
and therefore tending to be more restricted in using their full
▶ Table 1). It
(greater) physical capacities than younger players (●
is also possible that the particularly high cardiorespiratory fitness levels of the younger players in the present study (VVam-eval
for U14 and U15 = 15.3 and 15.8 km.h − 1, respectively. [3]) partly
explains their ability to achieve high match running performances. Another explanation for the lack of differences in match
running performance between the U14 and U17 can be related
to the intermittent nature of high-intensity actions during soccer match play, which was likely more favourable to the youngest players [38]. Since using individualized speed thresholds to
differentiate exercise intensities [1] would have probably weakened between-player differences, absolute speed thresholds
were preferred to enable accurate examinations of the impact of
physical capacities on match running performance. This also
allowed easier comparisons with the existing literature in young
players [6, 10]. Further investigations are however required to
assess the respective impact of physical/physiological changes
resulting from aging/growth vs. match-related tactical aspects
on match running performance.
In our young highly trained players, match running performance
▶ Table 2). CB
was significantly influenced by playing position (●
covered the lowest TD and VHIA, while W and S showed the
highest VHIA values. Since running distances were adjusted for
age and total playing time to allow the inclusion of players differing by age, direct comparisons with data from the literature is
not possible. The present results however extend the previous
findings on positional differences in the occurrence of repeatedsprint sequences [8], as well as in the cardiorespiratory load of
competitive games in young players [40]. They also confirm data
on position-specific running patterns reported in adult soccer
players [5, 13, 14, 35]. The greater amount of high-intensity running in W and S in the present study is probably related to their
need to complete sprints away from defending players in order
to generate space or capitalize on goal scoring opportunities
[14]. These specialized match running patterns appear to be
indicative of a mature tactical understanding of position-specific tasks [40]; this is consistent with the highly trained playergroup examined here. Since replicating competitive performance
conditions is thought to be an effective training practice for pre-
paring athletes for competition [13], the present information
can be used to develop position-specific training strategies for
developing soccer players. Another practical application that can
derive from these position-specific match running responses is
that playing position can be used as a means of manipulating
physiological load during (training) soccer match simulations.
While the beneficial impact of good physical capacities on game
match running performance has been shown in young moderately-trained [10], adult female [23], elite male [34] soccer players, and top-class referees [21, 43], to our knowledge no study
has also considered their effects taking into account playing
positions. The respective impact on match running performance
of individual physical capacities and/or specific technical/tactical
roles assigned to each playing position (see above), was difficult
to predict. We observed no difference in VVam-eval values between
FB, MD, W, 2ndS and S, despite important differences in game
▶ Table 2). Conversely, FB were slower
running performance (●
than W on the RSA test, but presented similar high-intensity
activities during games. Thus, position-related differences in
physical capacities did not always match position-difference in
▶ Table 2), and the magnitudes of
match running performance (●
the ‘position effect’ were also much lower for physical capacity
than for match running performance (η2 < 0.21 vs. 0.30–0.40 for
physical capacities vs. match running performance, respectively). Moreover, while correlations were moderate when all
▶ Fig. 2),
players were pooled together (VHIA vs. VVam-eval: r = 0.41,●
we observed trivial and non-significant correlations within FB,
CB, MD and W (e. g., VHIA vs. VVam-eval: r = 0.06 and 0.022 in FB
and CB), but large-to-very large and significant associations
within 2ndS and S positions (e. g., VHIA vs. VVam-eval: r = 0.70 and
0.64 in 2ndS and S; VHIA vs. RSAmean: r = 0.66 in 2ndS). Although
present correlations should be considered with care given the
limited sample size for some positions (e. g., 2ndS), they suggest
that playing soccer is likely to constrain defenders’ running
activities; conversely, attackers (i. e., 2ndS and S) have apparently
more space and opportunity to express and use their full physical potential. For these latter positions, the fitter players (i. e.,
having greater PV and VVam-eval) are therefore likely to benefit the
most from their higher physical capacities. The lack of large correlations between match running performance and physical
capacities found for W was however surprising given the high▶ Table 2). We could howintensity nature of this position (see ●
ever postulate that differences in individual playing style or
specific tactical ploys within the 4-4-1-1 formation used by our
teams, might partly explain these findings. Studies matching
time-motion analyses to qualitative (technical/tactical) game
examinations [36] should however be performed in the future to
clarify these observations.
Despite of the use of some less soccer-specific field tests (e. g.,
Vam-eval) compared with other studies [10, 23], the present
findings show for the first time that the general importance of
physical capacities on match running performance is not as evident as previously reported [10, 23, 34]. Playing position and its
associated tactical roles need to be taken into consideration
when examining the relationship between physical capacities
and match running performance. Although speculative with
present data restricted to correlations, our results suggest that,
from a talent identification and development perspective, physical capacities are more likely to be a limiting factor for players
who are required to play as attackers. While the precise physical
determinants of success in elite soccer are still debated [29, 42],
the present results suggest that physical training for highly
Buchheit M et al. Match Running Performance and Fitness in Youth Soccer. Int J Sports Med 2010; 31: 818–825
Downloaded by: Koebenhavns Universitetsbibliotek. Copyrighted material.
Training & Testing 823
trained young soccer players should target the development of
lower limbs explosive strength (influencing jumping height,
maximal sprinting speed and repeated-sprint ability [7]) and/or
maximal aerobic power (aimed at improving high-intensity
intermittent exercise capacity [17]), especially for prospective
attacking players.
Finally, defining the specific physical capacities that are most
likely to predict position-specific match running performance is
also likely to improve the selection/training process of talented
soccer players. In elite adult players, Rampinini et al. [34] showed
that peak running speed in an incremental field test, mean sprint
time on a RSA test, but not jumping height, were predictive of
high-intensity activities during competitive games. In the
present study, the physical capacities assessed by the performance tests showed significant and moderate-to-large correlations with some match running performance measures
▶ Fig. 2); however the magnitude of these correlations were
(●
position-dependent. For example, jump height, peak velocity
and repeated-sprint performance were significantly and largely
related with the peak speed reached during games in FB, 2ndS
and S (e. g., in S, CMJ and PV shared 61 and 55 % of the variance of
peak game speed), but not in MD (less than 0.001 %). The correlations for VHIA vs. RSAmean were however lower than those
reported for VHIA vs. VVam-eval, which was consistently the better
predictor of game running performance (all correlations rated at
least large and VVam-eval explaining more than 25 % of TD, VHIA,
Sprinting and even peak running speed reached in 2ndS and S). In
contrast, acceleration (inferred from a 10-m sprint time) showed
the weakest correlations with game running performance, irre▶ Fig. 2). While these findings
spective of playing positions (●
suggest that all the performance tests used in this study appear
to be of interest in the prediction of match running performance,
VVam-eval remained the most powerful determinant of physical
game performance, at least for the positions where running
activity is less likely to be constrained by tactical tasks. It is however possible that larger correlations could have been reported
with the use of more soccer-specific field tests (e. g., Yo-Yo
[10, 23] or shuttle RSA [34] tests) and individualized speed
thresholds for assessing match running performance [1].
In conclusion, during international club games in highly trained
young soccer players, match running performance is affected by
age and playing position; with playing position having a greater
impact than age (and its associated changes in physical capacities). Older players, as well as W and S, generally cover greater
distances at high-intensities. Although this requires further
tactical/technical analysis, the small age-related differences in
match running performance, despite the considerable differences observed in physical capacities, suggest that the older
players’ ability to use their physical potential might be restricted
during games. Moreover, the beneficial impact of high physical
fitness on game running performance is likely position-dependent, with attackers (i. e., 2ndS and S) likely to benefit the most
from their physical capacities. This has important applications,
for the detection of talented players, as well as the development
of position-specific training strategies in developing players.
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