PHYSIOLOGICAL RESPONSES AND TIME-MOTION
CHARACTERISTICS OF 4-A-SIDE SMALL-SIDED GAME
IN YOUNG SOCCER PLAYERS: THE INFLUENCE OF
DIFFERENT TEAM FORMATION METHODS
YUSUF KÖKLÜ,1 GÜLFEM ERSÖZ,2 UTKU ALEMDAROĞLU,1 ALPER Asxc
xı,3
AND
ALI ÖZKAN4
1
School of Sport Sciences and Technology, Pamukkale University, Denizli, Turkey; 2School of Physical Education and Sports,
Ankara University, Ankara, Turkey; 3School of Sport Sciences and Technology, Hacettepe University, Ankara, Turkey; and
4
Department of Sport Sciences, Basxkent University, Ankara, Turkey
ABSTRACT
Köklü, Y, Ersöz, G, Alemdaroğlu, U, Asxc
xı, A, and Özkan, A.
Physiological responses and time-motion characteristics of
4-A-side small-sided game in young soccer players: The
influence of different team formation methods. J Strength Cond
Res 26(11): 3118–3123, 2012—The purpose of this study was
to examine the influence of different team formation methods on
the physiological responses to and time-motion characteristics
of 4-a-side small-sided games (SSG4) in young soccer players.
Thirty-two young soccer players (age 16.2 6 0.7 years; height
172.9 6 6.1 cm; body mass 64.1 6 7.7 kg) voluntarily
participated in this study. Anthropometric measurements,
technical tests, and maximum oxygen uptake (V_ O2max) tests
were carried out on the players. The SSG4 teams were then
created using 4 different methods: according to the coaches’
subjective evaluation (CE), technical scores (TS), V_ O2max (AP),
and V_ O2max multiplied by TSs (CG). The teams thus created
played 4 bouts of SSG4 at 2-day intervals. During the SSG4,
heart rate (HR) responses, distance covered, and time spent in
HRmax zones were recorded. In addition, rating of perceived
exertion (RPE) and blood lactate level (La2) were determined at
the end of the last bout of each SSG4. Percent of HRmax
(%HRmax), La2, and RPE responses during SSG4 were
significantly higher for teams chosen according to AP and
CG compared with that according to CE and TS (p , 0.05). In
addition, teams chosen by AP and CG spent significantly more
time in zone 4 (.90% HRmax ) and covered a greater distance in
the high-intensity running zone (.18 kmh21) than did teams
formed according to TS. Moreover, AP teams covered significantly greater total distance than TS teams did (p , 0.05). In
Address correspondence to Yusuf Köklü, [email protected].
26(11)/3118–3123
Journal of Strength and Conditioning Research
Ó 2012 National Strength and Conditioning Association
3118
the
conclusion, to spend more time in both the high-intensity
HR zone and the high-intensity running zone, the teams in
SSG4 should be formed according to the players’ V_ O2max
values or the values calculated using both the V_ O2max and
technique scores.
KEY WORDS aerobic endurance, heart rate, blood lactate, rating
of perceived exertion, time-motion analysis
INTRODUCTION
E
ffective performance in soccer, a game that
requires jumping, shooting, challenges, turns,
dribbles, sprints, controlling the ball under pressure, running at different speeds, and sliding
tackles is dependent on both aerobic and anaerobic metabolism (1,29). Because various movements are involved in
this sport, a number of factors, such as technical ability and
endurance capacity, are thought to affect the players’ performance on the pitch. Traditionally, most coaches have used
running drills without the ball to develop soccer players’
physical endurance (23). However, small-sided games (SSGs)
are thought to be more suitable than this traditional interval
training for the development of the particular physical
characteristics required for matches because they involve the
actual movement types and patterns used in soccer (21).
A number of studies have examined exercise intensity in
SSGs (2,7,8,13,19,20,22,26–28). For example, Aroso et al. (2)
found that increasing the number of players without changing the pitch size resulted in lower La2 levels over 3 bouts of
2-a-side, 3-a-side, and 4-a-side games, whereas the HR response in 3-a-side games was lower than that in both 2-a-side
and 4-a-side games. In another study, Rampinini et al. (28)
revealed that exercise intensity during SSGs can be
influenced by both the field dimensions and coach encouragement by studying 3 bouts of 3-a-side, 4-a-side, 5-a-side,
and 6-a-side games involving amateur soccer players. In
contrast to Rampinini et al.’s results, Kelly and Drust (19)
reported that changes in pitch size did not alter the HR
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response over 4 bouts of SSGs involving the same number of
players. In addition, Hill-Hass et al. (13) found that changes
to playing rules in SSGs influenced physiological and timemotion responses in young elite soccer players, whereas
Mallo and Navarro (26) reported that the inclusion of
goalkeepers in SSGs reduced the tempo of the game because
this led to less high-intensity running and increased lowintensity activities.
In summary, previous studies have shown that factors such
as field dimensions, the number of players, game rules, coach
encouragement, and training regime can lead to changes in
physiological responses, time spent in high-intensity exercise,
and differences in distance covered during the SSGs
(14,16,28). In addition to these parameters, the means of
formation of opposing teams can influence exercise intensity
during SSGs.
Previous studies have used various methods for the
formation of teams in SSGs. In most studies, SSG teams
selected according to the coach’s subjective evaluation
(7,13,18,20). More recently, some studies have taken issues
of skill and fitness mismatches into account in the formation
of SSG teams and have instead attempted to achieve a
balance across opposing teams in terms of individual players’
composite skill and fitness ranking (4,14,16). However, the
influence on SSG performance of different team formation
methods is an issue that no previous studies have examined.
Findings resulting from such a study are likely to be useful to
soccer coaches who are interested in using SSGs to develop
simultaneously the technical capacity and soccer-specific
aerobic endurance of the players that they train. Therefore,
the purpose of this study was to examine the influence of
different team formation methods on the physiological
responses to and time-motion characteristics of 4-a-side
small-sided games (SSG4) in young soccer players.
METHODS
Experimental Approach to the Problem
A number of studies have been conducted to investigate the
various factors that can influence exercise intensity during
SSGs. However, the influence of different team formation
methods is a factor that has been largely overlooked, despite
the fact that disregarding differences in players’ technique and
fitness levels when selecting SSG teams may create
imbalances between the players and the teams in terms of
exercise intensity. With this gap in our current knowledge in
mind, this study aimed to examine the influence of different
team formation methods on SSG4 performance amongst
young soccer players. This study was carried out over
a 2-week preseason training period in September 2010–2011,
during which the 32 young soccer players who participated
were not involved in any other training or matches. On the
first day, anthropometric measurements (height, body mass,
skinfold thickness, circumference measurements) were carried out on the players. On the third day, a series of technical
tests were carried out, including ball control using the body,
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ball control with the head, slalom dribbling with passing,
slalom dribbling, passing accuracy, and shooting accuracy, to
determine each player’s technical score (TS). On the fifth and
sixth days of the study, each player’s V_ O2max was determined
using an incremental test on a treadmill. After these tests, the
SSG4 teams were created using 4 different methods, coaches’
subjective evaluation (CE), TS, AP, and TG: CE rankings
were established according to the CE; TS rankings considered each player’s technical test scores; the AP method
ranked players according to their V_ O2max scores obtained
from the incremental treadmill test; TG rankings were
created by multiplying each player’s V_ O2max score by his TS.
Once an overall ranking had been obtained for all 32 players
according to the CE, TS, AP, and TG methods, the players
could be divided into 4 groups of 8 from ÔbestÕ to ÔworstÕ (1–8;
9–16; 17–24; 25–32), after which each group of 8 was divided
into 2 teams of 4 using alternate rankings for the SSG bouts,
as shown in Table 1. On the eighth, tenth, twelfth, and
fourteenth days of the study, the players played 4 SSG4 bouts
in teams formed using the AP, TS, CE, and TG methods,
respectively.
Subjects
Thirty-two young soccer players (average age 16.2 6 0.7
years; height 172.9 6 6.1cm; body mass 64.1 6 7.7 kg; average
training age 6.2 6 2.0 years; percentage of body fat 7.5 6 3.0%;
HRmax 198.1 6 5.7 bmin21) voluntarily participated in this
study. All the players were the members of the same youth
team competing in an elite academy league and trained for
2 hours 5 dwk21. All the players and parents were notified of
the research procedures, requirements, benefits, and risks
before giving informed consent. Written informed consent
was obtained from all the subjects and parents. The study was
approved by the Ankara University Ethics Committee and
was conducted in a manner consistent with the institutional
ethical requirements for human experimentation in accordance with the Declaration of Helsinki.
Procedures
Incremental Treadmill Test. All the players completed an
incremental treadmill test on a motorized treadmill (Cosmed,
Gambettola, Italy) at an incline of 1% to determine maximal
oxygen uptake (V_ O2max) and maximum heart rate (HRmax).
The test began at 9 kmh21 and the speed was increased by
1 km h21 every minute with exhaustion being reached in
8–12 minutes (28). Achievement of V_ O2max was considered
as the attainment of at least 2 of the following criteria: (a)
a plateau in V_ O2max despite increasing speed, (b) a respiratory
exchange ratio above 1.10, and (c) HR 6 10 bmin21 of
age-predicted maximal HR (220 2 age) (3). During the test,
expired gases were analyzed using a breath-by-breath
automated gas-analysis system (Oxycon Mobile; Viasys
Healthcare, Hoechberg, Germany). The flow, volume, and
gas analyzer were calibrated before each test according to the
manufacturer’s instructions. The HR was measured and the
measurements stored using HR monitors (Polar Electro OY,
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Characteristics of 4-A-Side Small-Sided Game
Small-Sided Games. A 36-m 3
24-m pitch size (length 3
TABLE 1. SSG4 team formation using CE, TS, AP, and CG rankings.*
width) was used for the SSG4
(20,28). Each SSG4 consisted
First teams (player ranks) Second teams (player ranks)
of 4 bouts of 4 minutes’ duraFirst SSG4 match
1st, 3rd, 5th, 7th
2nd, 4th, 6th, 8th
tion with 2 minutes’ passive
Second SSG4 match
9th, 11th, 13th, 15th
10th, 12th, 14th, 16th
recovery time between the
Third SSG4 match
17th, 19th, 21st, 23rd
18th, 20th, 22nd, 24th
bouts. No specific rules were
Fourth SSG4 match
25th, 27th, 29th, 31st
26th, 28th, 30th, 32nd
used in the games to influence
*CE = coaches’ subjective evaluation; TS = technical scores; AP = V_ O2max; CG = V_ O2max
their intensity, but spare balls
multiplied by technical score; SSG4 = 4-a-side small-sided games.
were kept all round the pitch to
ensure that the game would
restart immediately if the ball
left the field of play. Moreover,
Kempele, Finland) throughout the test. The stored data were
the coaches continually offered verbal encouragement to the
transferred to the computer and filtered by Polar Precision
players during the games. The SSG4s were played without
Performance SoftwareTM (PPP4, Finland). The highest HR
a goalkeeper, and used small goals on a synthetic grass soccer
measurement was recorded as HRmax.
pitch. All the SSG4s were performed at the same time of the
day to avoid any effect of circadian rhythms on the measured
variables (9), with at least 2 days separating each session.
Each SSG4 was performed after a 20-minute warm-up
Technical Skill Tests. The technical skill test battery used by
consisting of low-intensity running, striding and stretching.
Malina et al. (24,25) was used to calculate the players’
technical skill scores. This test battery consists of 6 technical
tests: ball control with the body, ball control with the head,
slalom dribbling with passing (focusing on speed and
accuracy), slalom dribbling (focusing on speed), passing
accuracy, and shooting accuracy (24,25). After all the
technical skill tests, Z scores were calculated for each test;
the scores were reversed for the 2 timed items because lower
times reflect better performance (25). The Z scores were
summed to provide a composite soccer skill score for each
player. The intraclass correlations for repeated measures
(analysis of variance) indicated reasonable reliability: 0.72 for
passing, 0.72 for ball control with the head, 0.73 for shooting,
0.88 for dribbling speed, 0.85 for ball control with the body,
and 0.86 for dribbling with passing.
Heart Rate Monitoring. The HR was recorded at 1-second
intervals during the SSG4 bouts using short-range radio
telemetry (Polar Team Sport System, Polar Electro). Exercise
intensities during the SSG4 bouts were assessed using HR,
expressed as a percentage of HRmax as measured in the
treadmill test and classified into 4 previously defined intensity
zones: zone 1 (,75% HRmax), zone 2 (75–84% HRmax),
zone 3 (85–89% HRmax), and zone 4 (.90% HRmax) (14).
Both the actual time and percentage of the total time spent in
each zone for each player during all the SSG4s were
recorded. The data were categorized into HR zones using
Team AMS software (GPSports, Canberra, Australia).
TABLE 2. Physiological responses associated with 4-a-side games according to different methods of team formation.*†
CE
%HRmax
Time spent at ,75 % HRmax (s)
Time spent at 75–84.9% HRmax (s)
Time spent at 85–89.9% HRmax (s)
Time spent at .90 %HRmax (s)
La2 (mmolL21)
RPE
88.3
65.1
130.2
239.5
525.1
6.41
5.0
6 1.7‡
6 23.1‡
6 32.4§
6 55.6
6 79.9
6 0.6§
6 0.8§
TS
88.1 6
62.0 6
131.8 6
263.2 6
502.9 6
6.2 6
5.5 6
3.5‡
19.3‡
31.9§
50.4
65.4§
0.7§
1.0§
AP
CG
90.1 6 1.8
43.7 6 27.1
95.6 6 35.3
235.9 6101.6
584.8 6133.8
7.0 6 0.7
6.1 6 1.0
89.2 6 2.8
52.2 6 29.1
105.4 6 46.6
222.0 6 88.3
580.2 6 136.6
6.8 6 0.6
6.1 6 1.0
*CE = coaches’ subjective evaluation; TS = technical scores; AP = V_ O2max; CG = V_ O2max multiplied by technical scores;
%HRmax = percentage of maximum heart rate; La2 = blood lactate; RPE = rating of perceived exertion.
†Values are given as mean 6 SD.
‡Significant difference from AP, p , 0.05.
§Significant difference from AP and CG, p , 0.05.
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TABLE 3. Time-motion characteristics associated with 4-a-side games for different methods of team formation.*†
CE
Total
Total
Total
Total
Total
distances
distances
distances
distances
distances
21
743.8 6
at 0–6.9 kmh (m)
888.6 6
at 7–12.9 kmh21 (m)
at 13–17.9 kmh21 (m) 300.6 6
at .18 kmh21 (m)
66.4 6
(m)
1,999.5 6
TS
AP
CG
79.2ठ815.8 6 100.2
683.6 6 88.6§ 723.7 6
200.5‡ 872.4 6 199.0‡ 994.0 6 198.9 939.5 6
89.0§
215.3 6 87.4
304.1 6 93.5§ 301.8 6
37.9
47.1 6 31.3
78.5 6 39.8§
74.7 6
194.7 1,950.6 6 222.8‡ 2,060.3 6 199.6 2,039.7 6
122.2§
160.9
103.7§
32.7§
151.7
*CE = coaches’ subjective evaluation; TS = technical scores; AP = V_ O2max; CG = V_ O2max multiplied by technical scores.
†Values are given as mean 6 SD.
‡Significant difference from AP, p , 0.05.
§Significant difference from TS, p , 0.05.
Blood Sampling. Blood lactate samples were taken at 3 minutes
after the end of the last bout. The twenty-five-microliter blood
samples, taken from the ear lobe, were kept in YSI
Preservative Kits (Code 2315, YSI Incorporated Life Sciences,
Yellow Springs, OH, USA). Blood samples were taken from all
the players; lactic acid analyses were carried out the same day
using the YSI 1500 SPORT lactate analyzer (YSI Incorporated Life Sciences). The calibration of the analyzer was
conducted according to the manufacturer’s instructions.
characteristics. A Bonferroni post hoc test was applied to make
a pairwise comparison between the different levels of withinplayer factors. The level of statistical significance was set at
p # 0.05. Effect sizes (h2) were also calculated for physiological
responses and time-motion characteristics.
RESULTS
Time-Motion Characteristics. Player movements during the
SSG4s were measured using portable global positioning
system (GPS) units (SPI ProX; GPSports) and were analyzed
using Team AMS software (GPSports, Canberra, Australia).
The SPI ProX equipment with a 15-Hz sampling rate was
placed into a harness that positioned the device between each
player’s shoulder blades; they were worn by all players during
the SSG4 bouts. This technology has been previously
determined as reliable and validated for monitoring players’
high-intensity and sprinting activities during soccer matches
(5,17). For data analysis purposes, 4 speed zones were
selected: speed zone 1 (standing and walking, 0–6.9 kmh21),
speed zone 2 (low-intensity running, 7.0–12.9 kmh21), speed
zone 3 (medium-intensity running, 13.0–17.9 kmh21), and
speed zone 4 (high-intensity running, .18 kmh21) (4,16).
Table 2 shows the physiological characteristics associated
with SSG4 for the different team formation methods.
Compared with teams selected according to CE and TS,
SSG4 teams formed considering AP and CG measures
showed a significantly higher percent of HRmax (F = 8.283;
p , 0.05 and h2 = 0.211), La2 (F = 7.205; p , 0.05 and h2 =
0.473), and RPE (F = 15.150; p , 0.05 and h2 = 0.328)
responses. In addition, AP and CG teams spent significantly
more time than those formed considering TS measures at
zone 4 (F = 7.177; p , 0.05 and h2 = 0.188 ), whereas TS and
CE teams spent more time at zone 1 (F = 7.927; p , 0.05
and h2 = 0.204 ) than did AP teams and at zone 3 (F = 11.968;
p , 0.05 and h2 = 0.279 ) than did AP and CG teams.
Table 3 shows the time-motion characteristics associated
with SSG4 for the different methods of team formation. The
AP and CG teams covered significantly greater distances
at speed zone 4 (F = 7.264; p , 0.05 and h2 = 0.190) than did
TS teams. Moreover, SSG4 teams created according to
AP covered significantly greater total distances (F = 4.155;
p , 0.05 and h2 = 0.118) than did TS teams. Furthermore, TS
teams covered greater distances at speed zone 1 (F = 14.265;
p , 0.05 and h2 = 0.315) but less distance at speed zone 3
(F = 13.413; p , 0.05 and h2 = 0.302) than did teams selected
using CE, AP, and CG methods.
Statistical Analyses
DISCUSSION
The data are reported as means and SDs. Before using
parametric tests, the assumption of normality was verified
using the Shapiro-Wilk test. A 1-way repeated-measures analysis of variance was performed on each dependent variable,
including percentage of HRmax, rating of perceived exertion
(RPE), blood lactate concentration, and the time-motion
The purpose of this study was to examine the influence of
different team formation methods on physiological responses
and time-motion characteristics during SSG4s in young soccer
players. The main finding is that type of team formation
method does have an influence on physiological responses and
time-motion characteristics for these players in these games.
Rating of Perceived Exertion. A perceived exertion rating scale,
CR-10 (11), was completed by each player no more than 2
minutes after the end of the last bout. Before the SSG4s, all the
players were informed about, and familiarized with, the CR-10
scale, which has been validated as an indicator of training
intensity in intermittent bouts of small-sided games (6,14).
VOLUME 26 | NUMBER 11 | NOVEMBER 2012 |
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Characteristics of 4-A-Side Small-Sided Game
Small-sided games are thought to be suitable for developing
the particular physical characteristics that players need to be
able to perform under conditions of pressure and fatigue (12).
This is because these types of game include high-intensity
activities (short sprints, tackling, and sliding) involving
various movement types and patterns similar to those used
in soccer matches (21). These games are played on different
pitch sizes, with a different number of players and periods of
time. Factors such as enlarging or decreasing the playing area,
increasing or reducing the number of players, changing the
rules (e.g., 1 touch play, controlled passing), and the coach
encouragement are thought to affect physiological responses
during SSGs (28). For example, Köklü et al. (20) demonstrated that a decreased number of players results in
increased La2, HR, and % HRmax responses over 6 bouts
of SSGs. Moreover, Aroso et al. (2) reported that an increase
in the number of players with a constant pitch size results in
significantly different HR, %HRmax, and La2 responses
among the SSGs. Similarly, Williams and Owen (30) found
that an increased number of players with a constant pitch size
results in a decrease in physiological responses during SSGs.
Fanchini et al. (10) demonstrated that exercise intensity in
3-a-side SSG is influenced by bout duration, with a reduction
in the HR for SSGs of 6-minute duration. Rampinini et al.
(28) reported that %HRmax, La2, and RPE responses during
small-sided games can be influenced by varying the exercise
type, the field dimensions, and presence of coach encouragement. Moreover, Hill-Haas et al. (13) found that changes
to SSG rules or game formats may influence the %HRmax
and RPE responses independently. In this study, physiological responses are determined according to %HRmax (22,28),
time spent on different HRmax zones (4,16), La2 (2), and
RPE (6) during the SSG4s. The findings of this study are that
the highest physiological responses to SSG4s are produced in
teams created according to AP scores, followed by CG, CE,
and TS scores, respectively. This study also demonstrates
that the players in teams created using AP and CG formation
methods have significantly higher %HRmax, La2, and RPE
responses compared with CE and TS in SSG4 bouts. In
addition, teams created according to AP and CG spent more
time than those selected by TS at zone 4 Moreover, players in
teams created according to TS and CE spent more time at
zones 2 and 3 than did those in teams created by AP and CG
methods. These findings indicate that type of team formation
method can influence the physiological responses in SSG4.
In addition to the physiological measures of exercise intensity
during SSGs, recent technological advances now allow for
data relating to the movement of soccer players to be collected
(15). Previous studies have shown that factors such as pitch
area and rule modifications can influence such time-motion
characteristics during SSGs. For example, Hill-Haas et al. (14)
examined acute time-motion characteristics of youth players in
3 different small-sided soccer game formats (2-a-side, 4-a-side,
and 6-a-side) when the pitch area per player was kept constant.
Their results indicated that both mean and maximal sprint
3122
the
durations and distances increased with larger SSG formats.
Similarly, Casamichana and Castellano (4) showed that when
the individual playing area increased, the effective playing time,
total distance covered, distance covered per minute, maximum
speed, work-to-rest ratio, and sprint frequency all also
increased. Hill-Haas et al. (13) also found that SSG rule
modifications or changes in game format may influence timemotion characteristics. The results of this study demonstrate
that teams created according to TS covered more distance at
speed zone 1 compared with those created using CE, AP, and
CG methods, whereas those created according to AP and CG
covered greater distances at speed zones 3 and 4 than did TS
teams. Thus, young players created according to AP and
CG methods covered significantly greater distances at highintensity running speeds. It is therefore possible to conclude
that type of team formation method can influence the timemotion characteristics in SSG4. This suggests that future
studies in this area should take team formation factors into
account in a more systematic way.
PRACTICAL APPLICATIONS
This study indicates that different formation methods in SSG4
can influence %HRmax, time spent in different HRmax zones,
La2, RPE responses, and time-motion characteristics. Previous studies have reported that factors such as pitch size (28),
the number of players (30), rule modifications (13), absence or
presence of a goalkeeper (26), and coach encouragement (28)
influence exercise intensity in SSGs. In addition to these
factors, the findings of this study indicate that coaches and
sports scientists should also take into consideration ways that
teams are selected in SSG training. The findings suggest that
when the aim of SSGs training is to improve the maximum
oxygen uptake, SSG teams should be selected either according
to the players’ relative V_ O2max values or by considering the
rankings calculated from both the players’ V_ O2max and
technique scores because these methods appear to lead to
greater physiological responses and superior time-motion
characteristics compared with other team formation methods,
such as those that only consider the players’ technique test
scores or that rely on the coach’s subjective evaluation alone.
Therefore, coaches who want their teams to spend more time
in the high-intensity zone should form teams according to
players’ V_ O2max or both V_ O2max and technique scores.
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