The extent to which soccer players construct and share analogous mental models when interacting together to reach the same goal

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Human Movement Sciences
Master Research Project 2016-2017
The extent to which soccer players construct and share
analogous mental models when interacting together to reach
the same goal
Vrije Universiteit
Department of Human Movement Sciences
Specialization: Sport Psychology
Qualification: MSc in Human Movement Sciences
Research internship
Author: Francesca Maria Gargiulo + 2583034
Supervisors:
Prof. Dr. Geert J.P. Savelsbergh
and
Dr. R.I. Vana Hutter
August 2017

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Abstract
In recent years, researchers have increasingly studied how cognitive processes
influence sport performance, in order to help athletes accomplish higher results not only
physically, but also psychologically. In particular, one of the main factors that influences, in a
positive way, the teams’ performance and has begun to be subject to studies is the sharedness
of team mental models (TMMs). The more a mental model is shared within team members,
the more the performance of a team will be successful. While it is acknowledged that it is
necessary, for the team members, to be “on the same page”, it is still unclear which is the best
method to detect and analyse a team mental model.
The aim of this study was to identify the mental representation of a female football
team that competes in the first national football division, through the comparison of the data
from small-sided games, an online questionnaire and individual interviews. In particular, the
study focused on detecting whether there was congruence between what the players said
during the interviews and in the questionnaires and their practical behaviour while playing in
small-sided games. We were interested in testing the methodology described, and in
understanding to what extent the TMM of this female football team is shared within the
group. It emerged that, through the methodology applied, it is indeed possible to detect the
degree of sharedness of the team mental model within the players of a team, and in this
specific case, the TMM shared by the players resulted to be low.
The present findings could have important implications for coaches and others close to
the athletes, who can benefit from these results to detect their team’s own mental model and
work on it, in order to reach the best performance. Further research is necessary to determine
whether the same results can be found in lower football teams divisions and in younger teams,
in order to verify the possibility to generalise this type of research method.
Keywords: mental model, team mental model, team performance, football, match
analysis.

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Introduction
In the last decades, a great number of researchers have begun to look at sport from a
psychological perspective, as it is today acknowledged that an athlete’s performance depends
not just on his or her physical abilities, but also on her psychology. Of special interest is the
study of team sports, where an athlete’s behaviour is particularly complex, as it is influenced
by her relations to her teammates, in addition to her coaches and opponents.
According to Cannon-Bowers, Tannenbaum, Salas and Volpe (1995), the performance
of a team should be higher when the team members share the same perception of the task,
team, equipment and situation. Indeed, sport teams require an elevated degree of coordinated
behaviour and actions in order to be successful. Teams are interdependent systems
characterised by dynamism and complexity, which are “united” when their players share the
same vision of the goal, task and environment. The way in which each member of a team
thinks about all these elements is the Team Mental Model (TMM) (Reimer, Park, & Hinsz,
2006). A mental model is indeed the cognitive structure of people’s internal associations of
concepts and representations about the reality that surrounds them, which they use to
interrelate with others in the environment in which they are immersed (Mathieu et al., 2000,
2005). It is also defined as the capacity of the team members to share the same representations
of knowledge about the most important elements belonging to the team’s environment
(Mohammed, Ferzandi, & Hamilton, 2010).
An example of how important it is, for the success of the team, that the actions,
thoughts and behaviours are coordinated and as synergic as possible can be seen in no-look
passes (Kelley & Thibaut, 1978). While to an external spectator they may seem to be
performed by the players without effort and by chance, they are in reality an example of how
the players can and should read the game situation and anticipate and predict correctly the
other team members’ and the opponents’ positions and behaviour. TMMs thus emerge from
the way in which teams play in a match. It is a variable that can be improved and
manipulated, in order to enhance the performance of the individuals and of the whole team
(Mathieu et al., 2000).
While psychologists are increasingly studying sports as a specific discipline, there is
still little literature on TMMs in sports, and this concept is today mostly researched within the
business sector (Johnson et al., 2007). It is also not clear which is the best method for
measuring TMMs (Mohammed et al., 2000). The methodology utilised to detect the TMM for
this study, which focused on analysing the degree to which a TMM was shared within the

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Lugano Female Football team, was a combination of three different tools: small-sided games
analysis, an online questionnaire and individual interviews. We hypothesised that there would
be congruence within the results of the three tools and that if the mental model is shared
among the team members and staff, the team objectives will coincide and will be reached with
the same commitment (Reimer, Park, & Hinsz, 2006).
Team Mental Models
In 1990, Cannon-Bowers and Salas introduced for the first time the term Team Mental
Model, in order to detect the implicit coordination frequently observed in effective teams and
to account for how teams function in situations that are multifaceted, dynamic and uncertain.
The mental model refers to the organized understanding of the group and of the surrounding
environment, if it is shared within the team members.
At first, team mental models were studied in organizational teams and only in recent
years, researchers have begun asking why and to what extent are these models relevant in
sport contexts (Johnson et al., 2007). A common conceptualization of TMM has not been
found among authors yet, but it is accepted that, whatever its definition may be, the TMM is
a construct with specific characteristics: “the (a) purpose, (b) forms, (c) content, (d) nature,
and (e) coordination of [a team’s] underlying mechanisms” (Filho & Tenenbaum, 2012). The
purpose of TMMs is to afford the team members with heuristic routes, or rapid decisions, and
the capacity to make predictions. There are three main forms of knowledge that teammates
must share: what to do (declarative knowledge), how to do it (procedural knowledge), and
what action to perform next (strategic knowledge). Regarding the content of TMMs,
teammates must share task-specific and team-related knowledge, altogether with shared
knowledge on “equipment, tools, and technologies associated with team performance in a
given domain” (Cannon-Bowers et al., 1993). Another important element to be shared by
team players is coordination, which is essential to achieve the desired aims (Eccles, 2010 in
Filho & Tenenbaum, 2012). TMMs also rely on the implicit or explicit division of labour
among team members.

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Small-sided games
Small-sided games (SSGs) are soccer-specific activities for the training of elite players
(Hill-Haas et al., 2011). They consist of modified games played on pitches whose playing
area is reduced, as well as the number of the players involved in the matches. Small-sided
games are utilised a lot in trainings as they have the advantage of improving technical and
tactical skills as well as decision-making. As they represent authentic game situations and can
display the players’ ability in an accurate way, they motivate the players to perform well. In
addition, through the small-sided games method, psychological abilities of footballers can be
improved (Williams & Hodges, 2005). It has been demonstrated from previous research that
utilizing this training method can enhance technical skills faster and more enjoyably, giving
the players the possibility to practice most football elements at the same time, such as passing,
shooting, dribbling, turning and heading (Tessitore et al., 2006). By varying some factors of
the SSGs, it is possible to manipulate the intensity of the exercises, for example by modifying
the rules, the use of the goalkeepers, the size of the pitch and the goals or the number of
players as well as the role of the coaches (Hill-Haas et al., 2011). Small-sided games exalt
involvement in real football situations, allow for more touches on the ball, and demand higher
mental concentration. In these games, athletes need to cooperate to work out problematic
situations. Furthermore, they can play in every position using their spontaneity and creativity
at best, having fun and enjoyment. In this study, we used small-sided games also for their
capacity to present concurrently physical and technical skills, along with psychological
implications, such as the players’ team mental model (Owen et al., 2004, 2011).
Aims and hypothesis
This study aims to identify to what extent the team mental model in the Lugano
Female Football team is shared among the players. Prior to the start of the research, some
hypotheses are formulated.
A. Level of expertise and on-pitch behaviour
According to Ericsson et al. (1993), the more an athlete trains, the higher is his performance.
Starting from this statement, we wanted to test the following hypotheses:
Hypothesis 1: More years of football practice of a player lead to a higher number of correct
passes in small-sided games, meaning that the more a player has been practicing football, the
more she will perform better.

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Hypothesis 2: The players who have been playing for more years are the most sought players
by teammates, measurable by the number of successful or unsuccessful passes received. A
highly trained player should thus be perceived, by her teammates, as the best athlete to pass
the ball to.
Hypothesis 3: The number of passes received varies according to the number of months the
player has spent practicing within the Lugano football team. In other words, a footballer who
has played in the team for a longer period will be more esteemed than others will.
Hypothesis 4: The player with the highest number of passes performed is also the player who
receives the highest number of passes. The best players would thus be also the most sought
athletes during a match.
B. Social Evaluation and on-pitch behaviour
The self is particularly relevant for athletes as it is considered to be “a main determinant for
athletes’ motivation, decision making, behaviour and performance” (Fox, 2000). According to
Baumeister (1999), the self is a social construct, for this reason it is crucial how each athlete
constructs his self. It is relevant to understand how athletes see themselves also in relation to
how the other team members perceive them (Trouilloud & Amiel, 2011). In this study, we
wanted to detect if self-evaluation and social appreciation affected the players’ behaviour.
Hypothesis 5: The self-evaluation that each player gave herself regarding different game
situations matched the other team members’ evaluation of their performance.
Hypothesis 6: Social appreciation affects the players’ decisions and their behaviour during a
match. The more a player is valued and appreciated in and off the field, the more she is sought
by her teammates during the games.
C. The sharedness of TMM within the players
Hypothesis 7: It is possible to find out how much the sharedness of the team mental model
exists within the team, through the Task Network Analysis method using online
questionnaires. The more a player is considered the most important in a specific game
situation by the majority of her team members, the more the team mental model is shared.
Hypothesis 8: It is possible to find out to what degree the sharedness of the team mental
model exists within the team, through interviews with the players. The more an athlete is
identified by the other team members as the most relevant player given a specific game
situation, the more the team mental model is shared.

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Hypothesis 9: There is sharedness of the TMM if there is a high percentage of respondents
who share the same view in the various game situations, such as: a corner in favour of the
team, a corner for the opponents, a line out in favour of the team in their side of the pitch, a
line out for the opponents in the team’s side of the pitch, a line out in favour of the team in the
opponents’ side of the pitch, a line out for the opponents in opponents’ side of the pitch, a free
kick in favour of the team and a free kick in favour of the opponents.
D. Congruence within the three methods of investigation
Hypothesis 10: There is congruence between the answers to the questions in the online
questionnaire and the answers to the same questions during the oral interview.
Hypothesis 11: There is congruence between the players who are considered the most
relevant to act in a specific game situation through the online questionnaires, the interviews
and the players who were the most important in the same situation on the field.
Method
Participants
To test the hypotheses we studied the “Football Femminile Lugano 1976”, a Swiss
team composed of twenty-three highly talented female football players, ranged in age from 16
to 29 years, with a mean age of 22.27 years (SD = 3.39) and a mean football experience of
14,18 years (SD = 4,9). The average team experience as players in the Lugano team was
41,95 months meaning 3 years and 5 months (SD = 58,8), from a minimum of 1 month to a
maximum of 260 months. The team members were from different nationalities, Americans (n
= 8), Italians (n = 5), Swiss (n = 9), and Albanians (n = 1). They trained about eight hours a
week and played in the first national team division.
The experiment was approved by the local ethics committee of Vrije Universiteit. All
participants were informed of the investigation design and they gave their informed consent
before starting.
Samples and procedures
One participant did not take part in the practical session and was not interviewed
because she got injured while we were collecting the data. 21 participants filled in the online
questionnaire, 22 participants were interviewed, and 15 of them took part in the small-side
games. A trainer substituted one of the two goalkeepers, as she was called away to train with

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the Italian National Team. The data collection took place during the month of March 2017, at
the Cornaredo Sport Centre in Lugano. The investigation of the small-sided games was
conducted in a training session during the season, while the online questionnaire was sent to
the participants one week before their interview.
Measures
It is difficult to measure mental models as they are cognitive processes and it is even more
difficult to measure team mental models (Langan-Fox et al., 2004). To overcome these
difficulties, the present study focused on identifying the mental representation of the female
football team through three approaches:
- Task Network Analysis, to discover the perception of the players’ task structure;
- Individual interviews, to obtain a mental representation of specific task situations;
- Small-sided games video analysis, to detect the actual behaviour of each player.
These three methods are interconnected. The Task Network Analysis was used to visually
reflect the results emerged from the online questionnaire, and to analyse whether the TMM
was the same during different game situations as well as to what extent the TMM was shared
among the players. The players’ interpretation of the task structure and their effective mental
representation of specific task situations, studied through the online questionnaire, were also
investigated through individual interviews. In the small-sided games, the results of the Task
Network Analysis and the individual interviews were tested, by studying whether the players’
behaviour was in line with their answers to the online questionnaire. To do so, all behaviours
that are performed during a match were coded, so each player’s actions could be assessed.
All players were asked to fill in the Task Network Analysis Questionnaire online and, one
week later, they were interviewed. During the interview (see Appendix A), the players were
asked to look at a picture of a football field, on which specific game situations were recreated.
They were also given 23 stickers, representing the t-shirts of each team member. Given a
specific game situation (for example a corner for the team), the respondents had to visualize
themselves in the pitch and to stick their own t-shirt in their position in the field. Furthermore,
they were asked to indicate who they believed to be the most relevant player(s) in that game
situation, by sticking her t-shirt on the picture of the pitch. This visual stimulus helped the
players visualize their own and their teammates’ role in each game situation, and to better
explain their mind representation, in a visual way.

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The final version of the online questionnaire consisted of 31 items (see Appendix B)
through which to calculate the sharedness of the mental model regarding the task knowledge.
Items numbered 2, 3, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, and 30 utilized a 5-point
Likert scale ranging from 1 to 5 (1= a little to 5= a lot). The participants were given oral
instructions during the presentation of the research project at the beginning, two days before
receiving the questionnaire. The individual interviews consisted of 35 questions, some to
detect the players’ background, others to detect the most important players in different
situations, as through the online questionnaire, but this time they could use the visual aid of
the football pitch.
To detect to what extent the team shared the TMM, we utilised the Task Network
Analysis, a new tool used to discover and visually represent the task relations within a team.
This method represents the groups in networks: the nodes represent the players and the ties
represent the relationship between the players (see Figure 32-Appendix E) (Wasserman &
Faust, 1994).
Small-sided games were performed 6 vs 6, including the goalkeepers. The games took
place on an outdoor pitch. The dimensions of the field were 48x40 m and the borders were
marked out with small cones. A great number of balls was provided, to be continuously
replaced to keep the game flowing. The balls used were size 5 balls. The goals used were
eleven-a-side football type 7,32x2,24 m. The games were video recorded using a video
camera (Canon SX40HS) and a mobile phone camera (Iphone 7) on two different sides of the
pitch in order to analyse the passes between players from both angles. There were no specific
rules used in the games, and the players followed the usual football game rules. The small-
sided games were played as the last part of the training session. To analyse all the players,
everybody played against all the other players, so 8 matches of 5 minutes each were
performed.
A comparison was made between the players who were considered to be the most
important in a specific game situation through the online questionnaire, during the interview
and on the field, in order to detected any congruence or lack of.
Data Analysis
The answers to the interviews and the questionnaires were collected in an Excel
document and put in SPSS (Statistical Package for Social Science) to be analysed statistically.

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The data from the small-sided games were analysed through VideoMatch2017, a match
analysis software made by SICS (Software and services development and productions for
the Sport Industry).
The match analysis focused on:
- The percentage of correct passes performed by each player;
- Whom the player passed the ball to;
- The most sought players for each team, in each game and overall;
- The players who were present in specific situations, to see the congruence between their
behaviour on the ground and what emerged from the answers to the interviews and the online
questionnaires.
To test the hypotheses, correlations analyses were conducted.
Results
The percentages of TMM sharedness were calculated for the results emerging from the
online questionnaire, to which 21 out of 23 players were able to participate. It was not
possible to calculate the sharedness of the TMM through the results emerged from the
interviews because each player gave a different number of answers to each question. For
example, when asked who they believed to be the best player(s) in a specific game situation,
some players gave one name, while others gave more than one. The possibility to answer
more than one name was given in order to better understand the complex dynamics within the
team, and have a representation that would more closely reflect the players’ behaviour during
the small-sided games. However, the fact that the players could indicated a different number
of relevant players and it was thus not possible to calculate the percentage of TMM as for the
online results represents a limitation of the study.

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Table 1. Correlation results between the years of football practice, the correct passes
performed and the passes received
Variables 1. 2. 3.
Pearson correlation
1. Years of football practice 1
2. Correct passes -.168 1
3. Passes received .044 -.118 1
Note: r significant at p< 0.05 level
Table 1 shows the correlation of three variables: the years of football practice, the
number of correct passes performed and the number of passes received. It emerges that the
number of correct passes does not vary as the years of football practice increase, as there is no
correlation between the two variables (r = -.168, p= .549). The hypothesis that more years of
football practice lead to a higher number of correct passes is thus not confirmed.
The variation of the number of years of football practice is also not correlated to the
number of passes received (r = .044, p= .876). The hypothesis number 2 stating that players
who have been playing for more years are the most sought players, as measured by the
number of successful or unsuccessful passes received, is also negative. Moreover, the player
with the highest number of passes performed is not the same player who received the highest
number of passes (r = -.118, p= .675). There is no correlation between the number of correct
passes performed and a higher number of passes received. The initial hypothesis n.4 stating
that the player with the highest number of passes performed is also the player who receives
the highest number of passes is thus unconfirmed.
Table 2. Correlation results between the months of football practice in Lugano and the
passes received
Variable 1.
Pearson Correlation
1. Months in Lugano 1
2. Passes received -.397

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Table 2 reports that the number of passes received does not vary depending on how
long a player has practiced for within the Lugano team (r = -.397, p= .143). Hypothesis 3,
enouncing that the players who have been playing with the team for a longer period are also
the most sought player, as measured by the number of successful and unsuccessful passes
received, is unconfirmed.
Overview of the Krippendorff’s Alpha Reliability coefficient result
To calculate the inter-coder reliability within the score a player gave herself and the
scores the other players assigned to her in the online questionnaires and in the interviews, the
Krippendorff’s Alpha test was used. The results show that the inter-coder reliability was very
low (α = 0.52), i.e. the three coders did not agree. From the analysis, it emerged that there is
an estimated 98.13 percent chance that the alpha would be below 0.67, if the whole
population had been tested.
Table 3. Correlation results between the number of passes received and the social
appreciation scores
Variable 1.
Pearson Correlation
1. Passes received 1
2. Social appreciation
Q2+Q3 total
.183
Table 3 shows that the player with the highest number of passes received is not the same
player who received a higher score on the social appreciation questions from the
questionnaires (r = .183, p= .513). The correlation is indeed not significant, as the number of
passes received does not vary in correlation with the social appreciation.
The hypothesis number 6 that social appreciation affects the players’ decisions and their
behaviour during a match is not confirmed.

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Table 4. Task Network Analysis, Interviews and Small-sided games results
Game
situation
Relevant players
according to the
online
questionnaire
Percentage of
Sharedness of
TMM emerging
from the online
questionnaire
Relevant
players
emerging
from the
interviews
Relevant
players
according to
the small-sided
games analysis
Congruence
The Lugano
team has to
score a goal
Player n.13 86% Player n.13 Players n.13 and
18
yes
A corner
situation for
Lugano team
Players n.10 and
15
48% Players n.13,
14 and 15
Players n.10, 13
and 14
partially
A corner for
the opponents
Players n.12 and
15
38% Players n.15,
22 and 23
n/a no
A free kick for
the Lugano
team
Players n.10 and
22
43% Players n.13,
15 and 18
Players n.11 and
20
no
A free kick for
the opponents
Player n.12 33% Players n.10
and 12
n/a yes
A line out for
the Lugano
team, in their
side of the
field
Player n.14 33% Players n.11,
13 and 18
Players n.20, 26
and 28
no
A line out for
the opponents’
team, in the
Lugano side of
the field.
Player n.14 33% Players n.10
and 11
n/a no
A line out for
the Lugano
team, in the
opponents’
side of the
field.
Players n.13 and
14
33% Players n.13,
14 and 19
Players n.20, 26
and 28
no
A line out for
the opponent
team, in the
opponents'
side of the
field.
Players n.13 and
14
38% Players n.10,
11 and 18
n/a no

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The table above shows the results emerged from the Task Network Analysis, the
Interviews and the Small-sided games, for each game situation.
Discussion
In recent years, studies in cognitive psychology focused on team sports are of
increasing interest. There is a flourishing line of research rooted to organizational theorists,
which have demonstrated that teams whose members share “the same team mental models
will outperform teams whose members differ in their team mental models” (Klimoski &
Mohammed, 1994). Our aim was to find to what extent the TMM of the Lugano female
football team was shared. Our findings suggest that it is possible to calculate the sharedness of
the TMM of a team through the three methods applied and that the Lugano team has generally
a low sharedness of the team mental model, although different results may arise according to
the specific game situation.
A. Level of expertise and on pitch behaviour
In considering our study hypotheses, there is evidence that, regarding the level of
expertise and on pitch behaviour, it is not obvious that the more an athlete trains, the higher is
her performance. The first hypothesis does not hold true according to the data collected. A
study from Fransen et al. (2012) states that athletes can reach the same performance by
training fewer hours in different sports instead of more hours in only one sport. It would be
interesting for future research to focus on the hypothesis that a player who has done different
sports during her childhood becomes a better player, compared to those who only played
football. Hypothesis 2 is also not confirmed. More years of football practice do not lead to a
greater number of ball received.
Hypothesis 3, stating that the players who have been playing in Lugano for a longer period
are the most sought players, is negative. According to the data collected, as the number of
months that a player has spent in the Lugano team increase, the number of passes received
decreases. In fact, the American players who arrived in Lugano 1 month or 6 months into the
start of the season were the most sought players for the passes. This information emerged also
from the interviews, during which the non-American players stated that they believe their
American team members to be better performing both physically and technically. The initial
hypothesis number 4, assuming that the player with the highest number of passes performed
was also the player who received the highest number of passes, is unconfirmed.

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B. Social Evaluation and on pitch behaviour
According to our findings, there is no agreement within the three coders taken into
account: the score a player gives herself, the score the other players assign to her in the online
questionnaire and the score the other players assign to her during the individual interview.
The inter-coder reliability emerged from the analysis is very low. This means that the self-
evaluation that each player gave to herself regarding different game situations did not
correspond to the other team members’ evaluation. Hypothesis 5 is thus unconfirmed,
meaning that the subjective perception of the players was misrepresented or differently
interpreted by the other team members. There was a tendency within the team to overestimate
their own performance, as confirmed by Dunning (2003) who states that there is a general
tendency in people to overestimate themselves. For what concerns the Hypothesis n.6, the
results regarding the social appreciation and the players’ behaviour suggest that the number of
passes received was not affected by the players’ social appreciation. As there is no correlation
between the social evaluation and the on pitch behaviour of the players, Hypothesis n.6 is also
not confirmed. Instead, it emerged that the players passed the ball to those who were situated
in the best position in the field in that particular moment. This behaviour could be explained
by the fact that the team plays in the first division, so the players are willing and able to
separate their social appreciation towards their team members from their strategic on-pitch
decisions. Future research could detect whether the social appreciation is more influential in
affecting decisions in teams playing in lower categories.
C. The sharedness of TMM within the players
Hypothesis 7 is confirmed, as it is possible to calculate the percentage of mental model
sharedness through the answers of the online questionnaire and this sharedness can be
represented through the Task Network Analysis. Hypothesis 8, which stated that it is possible
to find out to what extent the sharedness of the team mental model exists within the team
through individual interviews, is also confirmed. Indeed, it was possible to calculate how
many players gave the same answers during the interviews and to classify the players
according to how often they had been nominated by the other team members. In hypothesis 9,
it was assumed that there would be sharedness of the TMM if there was a high percentage of
respondents who shared the same view in the various game situations (for example, when the
team has to score a goal). There was a high sharedness of the TMM in the first two game
situations (the team has to score a goal and to kick a corner in favour of the team), but not in

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the other game situations. In general, therefore, the TMM is not highly shared within the
Lugano team.
D. Congruence within the three methods of investigation
Hypothesis 10 stated that there is congruence between the answers to the questions in
the online questionnaire and the answers to the same questions in the oral interviews. This
hypothesis is confirmed. Indeed, it was verified that there was congruence between the
answers collected through these two methods. Finally, the last hypothesis (n.11) stated that
there would be congruence between the players who were considered the most important in a
specific game situation through the online questionnaires, the interviews and the small-sided
games on the field. This hypothesis is sometimes, but not always confirmed. Indeed,
according to the observations, it emerges that there was not always congruence in the data
collected through these three methods, as demonstrated in table 4.
This study presents some limitations. Firstly, as mentioned before, not all players
participated to all interviews (online and in person) and to all small-sided games. Indeed, 21
out of 23 players of the team filled in the online questionnaire; one player was not interviewed
due to an injury while the data was collected; and during the small-sided games, the players
who were able to play were 15 out of 23. The whole presence of the team would have led to a
higher amount of data, and the results could have been more consistent. Future research
should verify whether the results of the study hold true should the whole team be able to
participate in the small-sided games.
Secondly, during the small-sided games, many of the game situations needed for the
research (such as free kick and corners) were difficult to occur. As they might occur more
frequently during a normal football match, future researchers could observe both small-sided
games and regular championship football games, in order to have a clearer overview of the
team performance.
Thirdly, the Football Femminile Lugano team is a particular one, as it is characterized
by the presence of many international athletes. Some players, coming from the United States,
arrived in the team in the beginning of the season, while others had joined the team more
recently, in January 2017. When the data was collected, some of the new players might have
had an unclear understanding of the team dynamics. Future research could investigate teams
in which the players have been together for a longer and more consistent period, in order to

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verify whether, after seven months of football practice together, there is a higher sharedness
of TMM.
Conclusion
The purpose of the present study was to detect to what extent the Team Mental Model
of the Lugano team was shared among the team members and to test a combined
methodology to measure the TMM within a sport team. Indeed, we hypothesized that through
three different methods (Task Network Analysis, face-to-face interviews and small-sided
games), never used before in this type of study to our knowledge, the sharedness of the TMM
would emerged. The findings confirmed this principal hypothesis. Through small-sided games
players can live game situations that are very similar to competitive matches. Small-sided
games were thus considered to be the most suitable method to conduct this research and to
observe the behaviour of the players in different scenarios.
We found that in the Lugano football team there is generally a low sharedness of the
team mental model, although different results may emerge according to the specific
circumstance. The fact that a first division team has a low TMM sharedness is a worrying
result, as studies show that the more a TMM is shared within a team, the better the team
performs. A practical example of how low the TMM resulted to be in some game situations
emerged from the interviews, during which the goalkeepers had to think longer when asked
who were the most relevant players in a defensive situation or in a corner for the opponents.
Their uncertainty in giving a confident answers was justified with the fact that the team line
up had been changing frequently in recent games. On a positive note, the fact that the TMM
sharedness results were low also leads to believe that there is a high potential for
improvement. During the season when the research was conducted, the team confirmed its
position in the first division, but its ranking was not high. It will be interesting to study
whether the team’s ranking position will increase in the future, should action be taken to
improve the TMM sharedness within the team.
In contrast with our initial predictions, the analyses of the data revealed that there was
not always congruence within the data collected through the three different methods: the task
network analysis from the online questionnaire, the interviews and the small-sided games.
The present findings have important implications for future research interested in studying

18
TMM in sports teams through a combination of these methods. The results might differ and
these tools might prove to be more consistent when observing teams characterized by
different dynamics and a higher cohesion.
Through this study, football coaches have the opportunity to realise how important it is
to have the players share the team mental model, to avoid changing continuously the line-up
for each game, or to accept new players in the team after the season has already begun.
Understanding how team mental models can be detected at the individual and team level can
have implications beyond the field of sports: it can help researchers and educators to learn
how to understand and develop TMM in schools and communities and, within the business
sector, it can help human resources managers understand how employees behave and how to
improve the work environment.

19
Appendix
Appendix A
Interview for the players
I am Francesca Gargiulo, a Sport Psychology student at the Vrije University here in
Amsterdam. This interview is part of my Master Research Project for the Master program and
it is about how you perceive and think about your team and your team members.
I will ask you some questions, you will not be judged, feel free to take time and reflect before
answer.
Questions
1. When did you arrive in the Lugano team?
2. How old are you?
3. How long have you been playing football?
4. Did you practice other sports before football? Which one?
5. In which position do you usually play?
6. How do you feel in this position?
7. Have you ever played in different positions since you have started to play?
8. In your opinion, if you think about accomplishing a task, such as to score a goal, who
are the most effective players in your team? Why?
9. In your opinion, if you think about accomplishing a task, such as to stop an opponent
in defence, who are the most effective players in your team? Why?
at centre field, who are the most effective players in your team? Why?
close to the opponent goal, who are the most effective players in your team? Why?
12. When do you take decisions on what to do with the ball?

20
13. Which criteria do you use to take this decision?
14. Which criteria do you use to decide to pass the ball?
15. When do you decide not to pass the ball and to continue the action by yourself?
16. Do you prefer to pass the ball in front/to the right side/to the left side/behind you/far
from you (a cross)? (use the stickers)
17. Try to visualize yourself in your position in the field, with the ball between your feet.
Who are the players you usually look for when you are in possession of the ball in an
attack situation? (use the stickers)
18. Try to visualize yourself in your position in the field, with the ball between your feet.
Who are the players you usually look for when you are in possession of the ball in a
defensive situation? (use the stickers)
19. Do you think that the players in your team have the same technical level?
20. Do you usually pass the ball to the person who is in the best position in that exact
moment, or do you look for another teammate for other reasons?
21. Have you ever passed the ball to one of your teammate who was not in the best
position compared to another one, but you chose to pass the ball anyway because that
player was stronger than the other one?
22. Do you think that there are smarter players compared to others in carrying out a
specific task?
23. In which behaviours do they show to be smart?
24. If the player you thought was the best one to receive the ball is not suddenly available,
what do you do?
25. Imagine there is a corner for your team, where do you place yourself? Where do you
place 2 or 3 important players for you? When you receive the ball, what do you do?
(use the stickers)
26. Imagine there is a corner in favour of the opponents, where do you place yourself?
Where do you place 2 or 3 important players for you? If you receive the ball what do
you do? (use the stickers)

21
27. Imagine there is a free kick for your team in the opposite side of the field, where do
you place yourself? Where do you place 2 or 3 important players for you?
If you receive the ball what do you do? (use the stickers)
28. Imagine there is a free kick in favour of the opponents, where do you place yourself?
Where do you place 2 or 3 important players for you?
29. Imagine there is a line out for your team in your side of the pitch, where do you place
yourself? Where do you place 2 or 3 important players for you?
30. Imagine there is a line out for the opponents in your side of the pitch, where do you
place yourself? Where do you place 2 or 3 important players for you?
If you receive the ball what do you usually do? (use the stickers)
31. Imagine there is a line out for your team in the opposite side of the pitch, where do
you place yourself? Where do you place 2 or 3 important players for you?
32. Imagine there is a line out for the opponents in their side of the pitch, where do you
place yourself? Where do you place 2 or 3 important players for you?
33. Are your decisions influenced by the coach’s advice while playing?
34. Are your decisions influenced by a team member’s advice while playing?
Which ones?
35. Do you usually say something to the other players? What?

22
Appendix B
Online questionnaire questions:
1- What is your name?
2- How much do you enjoy playing football with this player? (Discard your own name)
3- How much do you like spending time outside the football field with this person? (Discard
your own name)
4-If the team has to score a goal, how relevant do you think is your role?
5- If your team has to score a goal, who are the most effective players in your team? (Discard
your own name)
6- If your team has to kick a corner, how relevant do you think is your role in this task
execution?
7- If your team has to kick a corner, who are the players who are most relevant for you?
(Discard your own name)
8- How relevant is your role in a corner in favour of the opponents?
9- If the opponents have to kick a corner, who are the players who are most relevant for you?
10- How relevant is your role in a free kick situation for your team?
11- If your team has to do a free kick, who are the players who are most relevant for you?
12- How relevant is your role in a free kick situation for the opponents?
13- If the opponents have to do a free kick, who are the players who are most relevant for
you? (Discard your own name)
14- How relevant is your role in a kick off situation for your team?
15- If your team has to do a kick-off, who are the players who are most relevant for you?
16- How relevant is your role in a kick off situation for the opponents?

23
17- If the opponents have to do a kick-off, who are the players who are most relevant for you?
18- How relevant is your role in a line out for your team, in your side of the field?
19- If your team has to do a line out in your side of the field, who are the players who are
most relevant for you? (Discard your own name)
20- How relevant is your role in a line out for the opponents, in your side of the field?
21- If the opponents have to do a line out in your side of the field, who are the players who
are most relevant for you? (Discard your own name)
22- How relevant is your role, when there is a line out for your team, in the opponents’ side of
the field?
23- If your team has to do a line out in the opponents’ side of the field, who are the players
who are most relevant for you? (Discard your own name)
24- How relevant is your role, when there is a line out for the opponents, in the opponents’
side of the field?
25- If the opponent team has to do a line out in the opponents' side of the field, who are the
players who are most relevant for you to achieve your personal task? Discard your own name
26- If your team has to stop an opponent in the defence area, how relevant is your role in this
task execution?
27- If your team has to stop an opponent in the defence area, who are the players who are
28- If your team has to stop an opponent close to the goal, how relevant is your role in this
task execution?
29- If your team has to stop an opponent close to the goal, who are the players who are
30- If your team has to stop an opponent at the centre of the field, how relevant is your role in
this task execution?
31- If your team has to stop an opponent at the centre of the field, who are the players who are

24
Appendix C
Interviews data tables
• Age
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
age 22 16 29 22,27 3,397
Valid N (listwise) 22
Frequency Percent
Valid 16 1 4,3
18 3 13,0
19 1 4,3
20 3 13,0
21 1 4,3
22 2 8,7
23 2 8,7
24 3 13,0
25 2 8,7
26 2 8,7
27 1 4,3
29 1 4,3
Total 22 95,7
Missing 999 1 4,3
Total 23 100,0

25
• Months of Football practice in Lugano
Months_Lugano 22 1 260 41,95 58,859
Frequency Percent
Valid 1 1 4,3
2 3 13,0
7 3 13,0
8 2 8,7
9 1 4,3
20 3 13,0
38 1 4,3
44 1 4,3
56 1 4,3
68 3 13,0
92 1 4,3
116 1 4,3
260 1 4,3
0
0.5
1
1.5
2
2.5
3
3.5
16 18 19 20 21 22 23 24 25 26 27 28 29
Age pf the players
Age pf the players

26
Total 22 95,7
Missing 999 1 4,3
Total 23 100,0
• Years of football practice
years of football practice 22 8 22 14,18 4,934
Frequency Percent
Valid 8 3 13,0
9 1 4,3
10 4 17,4
11 2 8,7
12 1 4,3
15 2 8,7
17 1 4,3
18 2 8,7
19 2 8,7
20 2 8,7
22 2 8,7
Total 22 95,7
Missing 999 1 4,3
Total 23 100,0

27
Appendix D
Match Analysis results
Match 1:
Figure 1 – Correct passes of the red team

28
Figure 2 – wrong passes of the red team
Figure 3 – correct passes of the yellow team

29
Figure 4 – wrong passes of the yellow team
Match 2:
Figure 5 – correct passes of the red team

30

31
Figure 7 – passes of the yellow team
Match 3:

32

33

34
Match 4:

35

36
Match 5:

37
Figure 18 – correct passes pf the yellow team
Figure 19 – wrong passes of the team

38
Match 6:

39

40
Match 7:

41

42
Match 8:

43

44
Figure 33 – The results of question n. 8 from the interview
Appendix E
Task Network Analysis results
Figure 32 – The results of question n.5 from the online questionnaire, represented through the Network

45
Figure 34 – The results of question n. 25 from the interview

46
Figure 37 - The results of question n.26 from the interview

47
Figure 38 - The results of question n.11 from the online questionnaire, represented through the Network
Figure 39 - The results of question n. 27 from the interview

48

49

50

51

52

53
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