Citation: Machado, J.C.; Góes, A.;
Aquino, R.; Bedo, B.L.S.; Viana, R.;
Rossato, M.; Scaglia, A.; Ibáñez, S.J.
Applying Different Strategies of Task
Constraint Manipulation in
Small-Sided and Conditioned Games:
How Do They Impact Physical and
Tactical Demands? Sensors 2022, 22,
4435. https://doi.org/10.3390/
s22124435
Academic Editor: Gregorij Kurillo
Received: 17 May 2022
Accepted: 9 June 2022
Published: 11 June 2022
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sensors
Communication
Applying Different Strategies of Task Constraint Manipulation
in Small-Sided and Conditioned Games: How Do They Impact
Physical and Tactical Demands?
João Cláudio Machado 1, Alberto Góes 2, Rodrigo Aquino 3
, Bruno L. S. Bedo 4, Ronélia Viana 1,
Mateus Rossato 1
, Alcides Scaglia 2,5
and Sérgio J. Ibáñez 6,*
1
Faculty of Physical Education and Physiotherapy, Federal University of Amazonas, Manaus 69067-005, Brazil;
jclaudio@ufam.edu.br (J.C.M.); ronelia.viana@gmail.com (R.V.); mateusrossato@ufam.edu.br (M.R.)
2
Faculty of Physical Education, State University of Campinas, Campinas 13083-859, Brazil;
algj1421@gmail.com (A.G.); alcides.scaglia@fca.unicamp.br (A.S.)
3
LabSport, Post-Graduate Program in Physical Education, Center of Physical Education and Sports,
Federal University of Espírito Santo, Vitória 29075-910, Brazil; aquino.rlq@gmail.com
4
Biomechanics and Motor Control Laboratory, School of Physical Education and Sports of Ribeirão Preto,
University of São Paulo, São Paulo 04024-002, Brazil; brunosbedo@gmail.com
5
Laboratory of Sport Pedagogy (LEPE), School of Applied Sciences (FCA), State University of Campinas,
Limeira 13484-350, Brazil
6
Optimisation of Training and Sport Performance Research Group, Faculty of Sports Sciences, University of
Extremadura, 06006 Badajoz, Spain
*
Correspondence: sibanez@unex.es
Abstract: This study aimed to investigate how different strategies of task constraint manipulation
impact physical and tactical demands in small-sided and conditioned games (SSCG). Ten recreational
U-17 soccer players participated in this study (16.89 ± 0.11 years). We used different strategies of task
manipulation to design two 4 vs. 4 SSCG: Structural SSCG and Functional SSCG. In Structural SSCG,
pitch format and goal sizes were manipulated, while in Functional SSCG, players were allowed to
kick the ball twice and at least 5 passes to shoot at the opponent’s goal. Players participated in four
Structural and Functional SSCG, of ﬁve minutes duration with a two-minute interval in between.
Players’ physical performance and tactical behavior were assessed using the WIMU PROTM inertial
device. Structural SSCG stimulated players to cover more distance in sprinting (p = 0.003) and
high-speed running (p < 0.001). Regarding tactical behavior, Structural SSCG stimulated players to
explore game space better (p < 0.001). Moreover, Functional SSCG stimulated players to be closer to
the ball, decreasing the effective playing space (p = 0.008). We conclude that these strategies of task
constraint manipulation impact physical and tactical demands of the game.
Keywords: soccer; task design; rules; physical demands; tactical behavior
1. Introduction
Small-sided and conditioned games (SSCG) are training tasks commonly used by
coaches and trainers to provide representative practice scenarios to their players and
team [1]. Therefore, several studies have highlighted the importance of SSCG to improve
players’ and teams’ performance, where coaches and trainers can manipulate key task con-
straints to emphasize specific training contents during the training sessions [2–7]. However,
for these games to be considered representative training tasks, the coaches should main-
tain the dynamic and functional relationships between crucial sources of information and
players’ actions present in the competitive environment [8]. In addition, SSCG need to be
carefully adjusted to players’ skill levels and the training content emphasized by coaches
and trainers [9–11]. Therefore, the representative training task design needs to respect
Sensors 2022, 22, 4435. https://doi.org/10.3390/s22124435
https://www.mdpi.com/journal/sensors
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the adjustment of task difﬁculty, complexity, and intensity levels to the player’s intrinsic
dynamics [9,11–13].
Previous studies reported acute effects of task manipulation (e.g., number of players,
the dimension and shape of the pitch, the quantity and location of goals) on players’ and
teams’ performance during SSCG [2–4]. In addition, the impact of rule constraints can
be considered a determinant to achieving the physical and tactical stimulus [12,14]. As
an example, Machado et al. [12] highlighted two different strategies of task constraint
manipulation: (i) modiﬁcation of structural elements of the game (e.g., number of players,
pitch dimension, goal sizes, etc.), and (ii) rule manipulation. The authors [12] observed that
these strategies have a different impact on the tactical behavior of teams, because they were
composed of players of different ages and levels of tactical skills. The teams composed
of younger players and players with low tactical skills were demonstrated to have more
difﬁculty dealing with SSCG with manipulated rules. In this regard, coaches and trainers
must carefully design SSCG using the strategy of rule manipulation.
Moreover, Machado and Scaglia [15] highlighted that when the coaches and trainers
manipulate structural elements of the game, the key sources of information that regulate
players’ actions emerge from the game itself, i.e., from the positioning and movement of
teammates and opponents, among others. However, when the coaches manipulate the
rules, besides this game information, the players need to manage information from outside
the game, which originates from the practitioner’s direct intervention (e.g., players can only
kick the ball twice, etc.). Therefore, when the game rules are manipulated inappropriately
(e.g., without considering the players’ skills level), the task difﬁculty and complexity
may increase [12,15].
Considering that these different strategies of task manipulation might have other
impacts on players’ and teams’ performance, it becomes important to understand the
effects of using these different strategies on physical performance and the way players and
teams structure the game space. Therefore, this study aimed to investigate how additional
task constraint manipulation strategies impact physical and tactical demands in SSCG.
2. Materials and Methods
2.1. Participants
Ten U-17 recreational soccer players (16.89 ± 0.11 years) participated in this study. The
players belong to a sports participation program and train together twice a week. All the
procedures in this research were in accordance with the Resolution of the National Health
Council (466/2012) and the Declaration of Helsinki (2013). In addition, this study was ap-
proved by the Ethics Committee in Research with Human Beings (N. 73222617.0.0000.5404).
2.2. Design
We applied two SSCG speciﬁcally designed to emphasize the tactical problem of
maintaining ball possession, using different strategies of task constraint manipulation:
(i) modiﬁcation of structural elements of the game (i.e., Structural SSCG) and (ii) modiﬁca-
tion of the game through functional elements (i.e., Functional SSCG). Both SSCG have been
previously used, with an emphasis on maintaining and circulating ball possession [12].
In the Structural SSCG, we manipulated pitch shape (wider) and goal size, and lo-
cation. A 4 vs. 4 game conﬁguration was used on a pitch measuring 47.72 m × 29.54 m
(width × length), with two small goals (2.5 m × 1 m) located on both wings (Figure 1).
Classical soccer rules were applied, except for offside. In the Functional SSCG, the game
functional elements were modiﬁed by manipulating the rules to emphasize the tactical
problem of maintaining ball possession. We used a Gk + 4 vs. 4 + Gk conﬁguration on
a pitch measuring 29.54 m × 47.72 m (width × length), with two centralized 7-a-side
goals (Figure 1).
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The following rules were manipulated: (i) the players were allowed to kick the ball 
once or twice (an extra point was awarded to the opponent’s team every time players 
kicked the ball more than twice); (ii) teams needed to exchange at least five passes to shoot 
at the opponent’s goal; (iii) an extra point was awarded to the team every time the players 
managed to move the ball from one wing to the other, identified from demarcated areas 
on the field (see Figure 1). 
 
Figure 1. Research experimental design: (A) shows the order of the games applied; (B) shows the 
small-sided and conditioned games used in this study.  
Goalkeepers were not allowed to participate in offensive actions, in an attempt to 
maintain a similar individual playing area between the two SSCG conditions (i.e., 176.2 
m2). Four SSCG were performed in each of the conditions, with four minutes duration and 
two minutes interval between games. The order of the games played was randomized, as 
shown in Figure 1. 
2.3. Analysis of Players’ Physical Performance 
Figure 1. Research experimental design: (A) shows the order of the games applied; (B) shows the
small-sided and conditioned games used in this study.
The following rules were manipulated: (i) the players were allowed to kick the ball
once or twice (an extra point was awarded to the opponent’s team every time players
kicked the ball more than twice); (ii) teams needed to exchange at least ﬁve passes to shoot
at the opponent’s goal; (iii) an extra point was awarded to the team every time the players
managed to move the ball from one wing to the other, identiﬁed from demarcated areas on
the ﬁeld (see Figure 1).
Goalkeepers were not allowed to participate in offensive actions, in an attempt to
maintain a similar individual playing area between the two SSCG conditions (i.e., 176.2 m2).
Four SSCG were performed in each of the conditions, with four minutes duration and
two minutes interval between games. The order of the games played was randomized, as
shown in Figure 1.
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2.3. Analysis of Players’ Physical Performance
Players’ physical performance was analyzed through positional data collected using
inertial devices (WIMU ProTM, RealTrack System, Almería, Spain), which have been shown
to be valid and reliable [16]. This device is composed of an accelerometer, gyroscope,
magnetometer, and 10-Hz global position system (GPS—RealTrack System, Almería, Spain).
Each participant wore a t-shirt provided by the manufacturer with a pocket to hold the
GPS unit between the scapulae.
The software SPROTM (RealTrack System, Almería, Spain) was used to extract the
following variables: (i) total distance covered (meters); (ii) distance covered (m) sprinting
(>18 km/h−1); (iii) distance covered (m) in high-speed running (HSR—13 km/h−1 to
18 km/h−1); (iv) high acceleration (m) (>2 m/s2); (v) high deceleration (m) (<−2 m/s2);
(v) the number of actions performed at a sprint. The ranges of speed were based on a
previous study [17].
2.4. Tactical Behaviour
Studies have already used these devices to analyze tactical behaviour [18,19]. The
actions performed during the games were tracked in real-time at each instant. Following
the matches, data were downloaded and exported to a .csv ﬁle using the same version of
the appropriate software (SPROTM—RealTrack System, Almería, Spain) for further analysis
in MATLAB scripts (The MathWorks Inc., Natick, MA, USA). Hence, the geographic coor-
dinates were transformed to cartesian coordinates (x,y) and smoothed with a Butterworth
digital ﬁlter (third-order; cut-off frequency: 0.4 Hz).
The following individual and collective tactical variables were analyzed: (i) spatial
exploration index (SEI) [20]; (ii) effective playing space for each team (EPS) [20]; (iii) team
width and length [20]; (iv) LpW, used to determine the length-per-width ratio per team [21];
(v) stretch index [22]. The SEI indicates players’ exploratory behavior, where higher values
highlight those players that were able to explore more game space [20]. EPS considers the
polygonal area of players located on the periphery of play of each team [23]. Team length
represents the longitudinal distance between the most distant players, while team width
represents the lateral dispersion of players [24]. The stretch index considers the average
distance of each player to the team centroid, indicating how much more dispersed players
are on the pitch [24]. These variables represent the individual and team space organization
during the games, including the way in which players occupy game spaces through their
positions and movements.
2.5. Statistical Procedures
Data normality distribution and homoscedasticity were veriﬁed through Shapiro–
Wilk’s and Levene’s tests. To compare external load between Structural SSCG and Rules
SSCG, we used a pairwise t-test. Moreover, we used both pairwise t-tests and Wilcoxon’s
test to compare players’ and teams’ tactical behavior. Effect size was calculated for each
pairwise comparison as follows (ES = z.√n): (i) negligible (<0.1), small (0.1–0.29), medium
(0.3–0.49), and large (>0.5) [25]. We used SPSS 21.0 (Chicago, IL, USA) for statistical analysis,
and the level of signiﬁcance was 5% (p < 0.05).
3. Results
Regarding physical performance (Table 1), we found that players covered more dis-
tance at a sprint (p = 0.003) and HSR (p < 0.001), and also performed a greater number of
sprints in Structural SSCG (p = 0.004). However, we did not ﬁnd signiﬁcant differences
between game conditions (Structural and Functional SSCGs) for total distance covered
(p = 0.301), high acceleration (p = 0.168), and high deceleration (p = 0.331).
Sensors 2022, 22, 4435
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Table 1. Players’ physical performance in different small-sided and conditioned game conditions.
Physical Performance
Structural SSCG
Functional SSCG
p-Value
Effect Size
Total distance covered (m)
501.94 (48.14)
493.95 (46.12)
0.301
0.389 (medium)
Distance covered (m) at a sprint (>18 km/h−1)
30.52 (17.56)
10.36 (7.69)
0.003
1.554 (large)
Distance covered (m) in high-speed running
(HSR—13 km/h−1 to 18 km/h−1)
121.82 (42.81)
77.82 (36.78)
<0.001
2.602 (large)
High accelerations (m) (>2 m/s2)
75.76 (28.67)
69.09 (19.74)
0.168
1.476 (large)
High decelerations (m) (<−2 m/s2)
61.31 (25.65)
56.63 (15.83)
0.331
1.141 (large)
Number of sprints
2.19 (1.22)
0.87 (0.61)
0.004
1.464 (large)
Regarding players’ tactical behavior (Table 2), we observed that Structural SSCG
stimulated players to explore more game space (SEI = p < 0.001). Moreover, observing EPS
(p = 0.008) and stretch index (p < 0.001) variables, it was possible to note that Functional
SSCG stimulated players to be closer to each other. Through team length (p = 0.001),
width (p < 0.001), and LpW ratio (p < 0.001) measures, we observed that Structural SSCG
stimulated teams to better explore the width of the pitch.
Table 2. Players’ and teams’ tactical behaviors in different small-sided and conditioned game conditions.
Tactical Behavior
Structural SSCG
Functional SSCG
p-Value
Effect Size
Spatial exploration index (SEI)
8.55 (1.45)
7.72 (1.43)
<0.001
0.584 (large)
Effective playing space (EPS)
85.97 (35.94)
67.06 (25.21)
0.002
0.46 (medium)
Team width
21.64 (5.09)
13.56 (3.10)
<0.001
1.243 (large)
Team length
16.48 (4.31)
13.56 (3.18)
<0.001
0.184 (small)
LpW ratio
0.78 (0.15)
0.93 (0.13)
<0.001
0.62 (large)
Stretch index
8.50 (2.01)
6.52 (1.25)
<0.001
0.761 (large)
4. Discussion
This study aimed to investigate how different strategies of task constraint manipu-
lation impact physical and tactical demands in SSCG. We observed that Structural SSCG
stimulated players to explore game space better and stimulated teams to expand the EPS
further. The rules manipulated in Functional SSCG made it difﬁcult for the players to
explore the game space, and as a result, they were able to get closer to other players. The
stretch index variable also helped us to verify that players tend to get closer relative to each
other in SSCG, which was designed using the strategy of rules manipulation.
Praça et al. [14] designed SSCG to emphasize progression to the target and found that
players presented higher exploratory behaviors. Machado et al. [10,12] found that these
manipulated rules contribute to players having more difﬁculty exchanging passes, keeping
possession of the ball, and inhibiting players’ and teams’ exploratory behavior. The greater
difﬁculty for players to respond to the manipulated rules resulted in players moving closer
to their teammates, and behaving more statically on the ﬁeld.
Regarding players’ physical performance, we found that Structural SSCG provoked
more sprints than Functional SSCG. Moreover, players covered greater distances in sprint-
ing and H.S.R. in Structural SSCG. The behavior of the prementioned tactical variables
might help to understand the external load presented in these games (Structural and
Functional SSCG). As players move further away from each other and as the effective
playing space increases, players have more space to move in high-speed running. Other
studies highlighted that when playing space increases, the distances covered by the players
in different speed zones also increases [26,27]. Nunes et al. [26] observed that U-15 and
U-23 players performed more sprints in SSCG with a larger playing area. Moreover,
Sensors 2022, 22, 4435
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when rules were manipulated to emphasize tactical content of progression to the target,
players covered greater distances in different speed zones, especially in sprinting and
high-speed running [14].
In Structural SSCG, the pitch was wider, and two small goals were located on both
wings. Modifying these structural elements of the game (pitch shape, goal sizes, and
location) stimulated teams to expand the playing space in width. This happens as players
tend to manage game space to move the ball from one wing to another to create spaces
and score a goal. Even with areas restricted on both sides and with the rule that sought to
stimulate the ball circulation from one wing to the other, Functional SSCG did not stimulate
players to expand the game space in width.
This study aimed to raise an important discussion about the design process of SSCG in
soccer, highlighting the impact of different task manipulation strategies on players’ physical
performance and tactical behavior. Although it presents important information about this
design process, this study has limitations that can be highlighted: a small number of players
participated and it did not analyze players’ technical performance, considering whether
they solved the game problems. Moreover, this study does not consider players’ initial
condition, regarding their tactical skills and physical ﬁtness. However, the results of this
study are important to highlight that the exaggeration of rule manipulation negatively
impacts the way players structure and move through the game space. Therefore, the design
process of a representative task must consider both the strategies of task manipulation and
the training content that the coach intends to emphasize.
5. Conclusions
We conclude that the strategies of task manipulation used impact players’ physical
performance and players’ and teams’ tactical behavior differently. Structural SSCG pro-
vided a greater adequate playing space, especially in width, encouraging players to explore
the pitch more. Moreover, in Structural SSCG, players performed more sprints and covered
greater distances in sprinting and high-speed running speed zones. However, Functional
SSCG stimulated players to get closer to their teammates. Therefore, the strategy of task
modiﬁcation by functional element manipulation can be used to increase game complexity
level, impacting the way players and teams manage the game space. This study provides
important information regarding the impact of different strategies of task manipulation,
highlighting the need to carefully modify the structural elements and rules of SSCG to
adjust these tasks to players’ skills level, and to the training content that coaches intend
to emphasize.
Author Contributions: Conceptualization, J.C.M. and R.A.; methodology, J.C.M., R.A., B.L.S.B. and
A.G.; software, J.C.M. and A.G.; validation, B.L.S.B. and A.G.; formal analysis, J.C.M., R.V. and A.G.;
investigation, J.C.M., R.V. and M.R.; resources, J.C.M.; data curation, J.C.M.; writing—original draft
preparation, J.C.M.; writing—review and editing, J.C.M., R.A. and B.L.S.B.; visualization, A.S. and
S.J.I.; supervision, S.J.I.; project administration, J.C.M.; funding acquisition, J.C.M. All authors have
read and agreed to the published version of the manuscript.
Funding: This research was funded by the Secretaria Nacional de Futebol e Defesa dos Direitos
do Torcedor (SNFDT), Secretaria Nacional de Esportes do Ministério da Cidadania (grant num-
ber TED No. 01/2020). This study has been partially subsidized by the Aid for Research Groups
(GR21149) from the Regional Government of Extremadura (Department of Economy, Science and
Digital Agenda), with a contribution from the European Union from the European Funds for
Regional Development.
Institutional Review Board Statement: The study was conducted in accordance with the Declaration
of Helsinki, approved by the Institutional Ethics Committee of UNICAMP (protocol code 2.250.881),
and approved on 31 August 2017.
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Not applicable.
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Conﬂicts of Interest: The authors declare no conﬂict of interest.
References
1.
Davids, K.; Araújo, D.; Correia, V.; Vilar, L. How small-sided and conditioned games enhance acquisition of movement and
decision-making skills. Exerc. Sport Sci. Rev. 2013, 41, 154–161. [CrossRef] [PubMed]
2.
Clemente, F.M.; Sarmento, H. The effects of small-sided soccer games on technical actions and skills: A systematic review. Hum.
Mov. 2020, 21, 100–119. [CrossRef]
3.
Clemente, F.M.; Afonso, J.; Castillo, D.; Los Arcos, A.; Silva, A.F.; Sarmento, H. The effects of small-sided soccer games on tactical
behavior and collective dynamics: A systematic review. Chaos Solitons Fractals 2020, 134, 109710. [CrossRef]
4.
Sarmento, H.; Clemente, F.M.; Harper, L.D.; da Costa, I.T.; Owen, A.; Figueiredo, A.J. Small sided games in soccer–a systematic
review. Int. J. Perform. Anal. Sport 2018, 18, 693–749. [CrossRef]
5.
Clemente, F.M.; Ramirez-Campillo, R.; Sarmento, H.; Praça, G.M.; Afonso, J.; Silva, A.F.; Rosemann, T.; Knechtle, B. Effects of
small-sided game interventions on the technical execution and tactical behaviors of young and youth team sports players: A
systematic review and meta-analysis. Front. Psychol. 2021, 12, 1501. [CrossRef]
6.
Clemente, F.M.; Afonso, J.; Sarmento, H. Small-sided games: An umbrella review of systematic reviews and meta-analyses. PLoS
ONE 2021, 16, e0247067. [CrossRef]
7.
Gómez-Carmona, C.D.; Gamonales, J.M.; Pino-Ortega, J.; Ibáñez, S.J. Comparative Analysis of Load Proﬁle between Small-Sided
Games and Ofﬁcial Matches in Youth. Sports 2018, 6, 173. [CrossRef]
8.
Travassos, B.; Duarte, R.; Vilar, L.; Davids, K.; Araújo, D. Practice task design in team sports: Representativeness enhanced by
increasing opportunities for action. J. Sports Sci. 2012, 30, 1447–1454. [CrossRef]
9.
Machado, J.C.; Scaglia, A.J. Pedagogia não linear no futebol: Uma busca por estratégias pedagógicas que possam nortear o
processo de criação de tarefas representativas. In O Futebol nas Ciências Humanas no Brasil; Giglio, S.S., Proni, M.W., Eds.; Editora
da UNICAMP: Campinas, Brazil, 2020; pp. 570–585.
10.
Machado, J.C.; Ribeiro, J.; Palheta, C.E.; Alcântara, C.; Barreira, D.; Guilherme, J.; Garganta, J.; Scaglia, A.J. Changing rules and
conﬁgurations during soccer small-sided and conditioned games. How does it impact teams’ tactical behavior? Front. Psychol.
2019, 10, 1554. [CrossRef]
11.
Machado, J.C.; Barreira, D.; Teoldo, I.; Travassos, B.; Júnior, J.B.; dos Santos, J.O.L.; Scaglia, A.J. How Does the Adjustment of
Training Task Difﬁculty Level Inﬂuence Tactical Behavior in Soccer? Res. Q. Exerc. Sport 2019, 90, 403–416. [CrossRef]
12.
Machado, J.C.; Barreira, D.; Teoldo, I.; Serra-Olivares, J.; Góes, A.; Scaglia, A.J. Tactical behaviour of youth soccer players:
Differences depending on task constraint modiﬁcation, age and skill level. J. Hum. Kinet. 2020, 75, 225. [CrossRef] [PubMed]
13.
Ibáñez, S.J.; Pérez-Goye, E.; García-Rubio, J.; Courel-Ibáñez, J. Effects of task constraints on training workload in elite women’s
soccer. Int. J. Sports Sci. Coach. 2020, 15, 99–107. [CrossRef]
14.
Praça, G.M.; Andrade, A.G.P.; Bredt, S.d.G.T.; Moura, F.A.; Moreira, P.E.D. Progression to the target vs. regular rules in Soccer
small-sided Games. Sci. Med. Footb. 2022, 6, 66–71. [CrossRef] [PubMed]
15.
Machado, J.C.; Scaglia, A.J. Pedagogia do Esporte e o ensino com jogos. In Pequenos Jogos para Treinar em Grande; Prime Books:
Lisbon, Portugal, 2022; pp. 161–190.
16.
Bastida Castillo, A.; Gómez Carmona, C.D.; de la Cruz Sánchez, E.; Pino Ortega, J. Accuracy, intra-and inter-unit reliability, and
comparison between GPS and UWB-based position-tracking systems used for time–motion analyses in soccer. Eur. J. Sport Sci.
2018, 18, 450–457. [CrossRef]
17.
Castagna, C.; Impellizzeri, F.; Cecchini, E.; Rampinini, E.; Alvarez, J.C.B. Effects of intermittent-endurance ﬁtness on match
performance in young male soccer players. J. Strength Cond. Res. 2009, 23, 1954–1959. [CrossRef]
18.
Clemente, F.M.; Castillo, D.; Los Arcos, A. Tactical analysis according to age-level groups during a 4 vs. 4 plus goalkeepers
small-sided game. Int. J. Environ. Res. Public Health 2020, 17, 1667. [CrossRef]
19.
López, L.M.G.; Olivares, J.S.; Vicedo, J.C.P.; Pérez, J.A.S.; Córdoba, C.P.; del Campo, D.G.D. Formatos Competitivos en Fútbol
Sub-12. Un Análisis desde el Punto de Vista Táctico, Condicional y del Compromiso Deportivo del Joven Futbolista. Kronos Rev.
Univ. de la Act. Física y el Deporte 2019, 18, 7.
20.
Clemente, F.M.; Sequeiros, J.B.; Correia, A.; Silva, F.G.M.; Martins, F.M.L. Computational Metrics for Soccer Analysis: Connecting the
Dots; Springer: Berlin/Heidelberg, Germany, 2018.
21.
Folgado, H.; Lemmink, K.A.P.M.; Frencken, W.; Sampaio, J. Length, width and centroid distance as measures of teams tactical
performance in youth football. Eur. J. Sport Sci. 2014, 14, S487–S492. [CrossRef]
22.
Silva, P.; Duarte, R.; Sampaio, J.; Aguiar, P.; Davids, K.; Araújo, D.; Garganta, J. Field Dimension and Skill Level Constrain Team
Tactical Behaviours in Small-Sided and Conditioned Games in Football. J. Sports Sci. 2014, 32, 1888–1896. [CrossRef]
23.
Low, B.; Coutinho, D.; Gonçalves, B.; Rein, R.; Memmert, D.; Sampaio, J. A systematic review of collective tactical behaviours in
football using positional data. Sports Med. 2020, 50, 343–385. [CrossRef]
24.
Coito, N.; Davids, K.; Folgado, H.; Bento, T.; Travassos, B. Capturing and Quantifying Tactical Behaviors in Small-Sided and
Conditioned Games in Soccer: A Systematic Review. Res. Q. Exerc. Sport 2022, 93, 189–203. [CrossRef] [PubMed]
25.
Fritz, C.O.; Morris, P.E.; Richler, J.J. Effect size estimates: Current use, calculations, and interpretation. J. Exp. Psychol. Gen. 2012,
141, 2. [CrossRef] [PubMed]
Sensors 2022, 22, 4435
8 of 8
26.
Nunes, N.A.; Gonçalves, B.; Davids, K.; Esteves, P.; Travassos, B. How manipulation of playing area dimensions in ball possession
games constrains physical effort and technical actions in under-11, under-15 and under-23 soccer players. Res. Sports Med. 2021,
29, 170–184. [CrossRef] [PubMed]
27.
Casamichana, D.; Castellano, J. Time–motion, heart rate, perceptual and motor behaviour demands in small-sides soccer games:
Effects of pitch size. J. Sports Sci. 2010, 28, 1615–1623. [CrossRef]

Applying Different Strategies of Task Constraint Manipulation in Small-Sided and Conditioned Games: How Do They Impact Physical and Tactical Demands?
Machado, João Cláudio,Góes, Alberto,Aquino, Rodrigo,Bedo, Bruno L S,Viana, Ronélia,Rossato, Mateus,Scaglia, Alcides,Ibáñez, Sérgio J