Advances in Physical Education
2013. Vol.3, No.4, 209-214
Published Online November 2013 in SciRes (
Open Access 209
Patterns of Interpersonal Coordination in Rugby Union: Analysis
of Collective Behaviours in a Match Situation
Marta Rodrigues, Pedro Passos
Department of Sport and Health, Faculty of Human Kinetics,
University of Lisbon, Lisbon, Portugal
Received May 27th, 2013; revised June 27th, 2013; accepted July 4th, 2013
Copyright © 2013 Marta Rodrigues, Pedro Passos. This is an open access article distributed under the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
This study aims to analyze how intra-team coordination patterns in the team sport of rugby union influ-
enced successful performance. We hypothesized that high interpersonal coordination patterns are a crucial
issue to cross (or not) the gain line. Video record and digitizing procedures were used as a method to col-
lect data for further analysis of interpersonal coordination patterns that took place during the formation of
subunits of attack. The results showed the existence of three types of outputs, which differ depending on
the correlations between attackers and defenders. Therefore, for high and positive values of interpersonal
coordination (r values between 0.8 < r < 1), there are possibilities of action that lead to success when the
opponents have inverse or lower values of correlation. The conclusion was that interpersonal coordination
within subunits becomes a relevant factor in analyzing the success in each game situation.
Keywords: Interpersonal Coordination; Running Correlations; Rugby Union
Adaptive behaviors are a crucial issue within social systems
like team sports. The information needed to perform adaptive
behaviours in a continuously changing environment is available
on the context, and subsequently every action has a direct in-
fluence in the changes within that context. This reciprocal in-
fluence between subject and the environment where they per-
form allows constraining the actions of the subject during
competition (Araujo, Davids, & Hristovski, 2006; Gibson, 1979;
Newell, 1986).
In team sports of rugby union, the nonlinear interactions be-
tween the teams (attack and defense) originate from two iden-
tical but functionally opposite goals (scoring tries preventing
the opposing team to do the same), which require adaptive be-
haviours aiming at intra-team coordination in an ever-changing
context, for example, by changing the number of players in-
volved in each sub-phase of the game, or the interpersonal dis-
tances between players in the defense, by constraining different
areas in which the different movements occur (Correia et al.,
2012; Headrick et al., 2012).
Possibilities of Action of Collective Behaviours in
Rugby Uni o n
Rugby union can be characterized as a collective game of
contact, where the attacking team aims to score a try (i.e., plac-
ing the ball on the ground on a specific area for that purpose,
the try zone) while the defending team aims to prevent the at-
tackers from scoring a try and constantly seeks to regain ball
possession. In order to score a try, the attacking team needs to
become closer to the try zone, which demands that every action
aims to continuously cross the gain line (and as a consequence
approach the score line), which is an imaginary line parallel to
the score line, set between the attackers and defenders (Figure
1) every time that attackers and defenders perform a ruck, maul,
scrum or lineout1. There is a causal connection between cross-
ing the gain line and achieving success, and therefore the at-
tacking team continuously struggles to go forward, breaking to
the opposing team’s defensive actions and consequently cross-
ing the gain line. This requires that attackers perform as a single
unit, which demands interpersonal coordination. One question
that emerges from this attacker task constraint is: how do the
attackers coordinate to cross the gain line?
In previous studies, rugby union was characterized as having
a structural organization that was continuously changing with
time, and it was also considered that the decisions and actions
of each player were constrained (i.e., limited) by various causes
responsible for multiple results/solutions (Passos, Milho, Fon-
seca, Borges, Araújo, & Davids, 2011). Therefore, players need
to perform their actions in a context of great variability, that is,
to experience different ways to perform co-adaptive behaviours
(i.e., players with different characteristics play in an integrated
way, adjusting their actions with the behaviour of their team-
mates and opponents), which enables them to be more func-
tional in different game sub-phases (Passos et al., 2011). In
order to be functional, players must create uncertainty in the
defensive lines, which requires that attackers search for differ-
ent opportunities of action (i.e., affordances) (Fajen, Riley, &
Turvey, 2009). Therefore, the constant search for various at-
tacking scenarios becomes a main issue in a rugby match.
In a team sport like rugby union, defense actions to prevent
1 retrieved 4th April 2012.
attackers from succeeding (e.g., to cross the gain line; to score a
greater number of tries) demand cooperation and coordination
among teammates. Previous studies in rugby union show that
adaptive behaviours (e.g., changes in the positions of the play-
ers, changes in running line speed trajectories) originate differ-
ent actions from the players, and therefore enable enlarging the
set of possible actions to achieve the same outcome (e.g., con-
tinuously decreasing the distance to the score line) (Passos,
Cordovil, Fernandes, & Barreiros, 2012). Accordingly to
Araújo, Davids and Hristovski (2006), subtle changes can lead
to multiple variations, implying that the players act in order to
explore multiple affordances towards a certain goal.
Becoming closer to the score line requires conquering terri-
tory from the opponent, therefore attackers should, simultane-
ously, co-adapt to the behaviour of their opponents, but also
co-adapt to their teammates’ behaviours, being able to coordi-
nate each other, and as a single entity explore the possibilities
of action that are more functional to maintain a goal-directed
behaviour, that is to cross the gain line.
However, the interactive behaviour within a social unit (e.g.,
group of athletes) is likely to change over time due to changes
on the running line speeds or changes in the players’ interper-
sonal distance. In competitive contexts (e.g., rugby union
match), the proximity to the opponents creates unstable con-
texts in which athletes continuously co-adapt to the behaviours
of other players in the neighborhood This means that a set of
players (e.g., an attacking subunit) might have the need to
change from a coordinated state to another (Marsh, Richardson,
Baron, & Schmidt, 2006; Passos et al., 2011). In other words,
the decrease of interpersonal distance between attackers and
defenders might cause the attackers to adopt different modes of
interpersonal coordination.
Attacking Subunits in Rugby Union
Knowing that in rugby union the main concern is to go for-
ward in the field, conquering territory from the opponent team
and thus getting closer to the try line, since it is not allowed to
perform a pass forward, and also due to the fact that the defense
lines are more difficult to overcome because of the amount (i.e.,
volume) of training that is given to this component (Passos,
Araujo, Davids, Gouveia, & Serpa, 2006), there is a need to
create new and variable situations of attack. For that purpose,
the connection between attacking players becomes a relevant
issue, i.e., the attacking team must be capable of organizing in
subunits to create new and different functional synergies that
lead to unpredictable collective actions from the defensive
Previous studies in rugby union suggest that contextual de-
pendence increases due to a decrease in interpersonal distance,
which means that, within certain limits of interpersonal distance,
players enter in a critical region in which they have to co-adapt
to the decisions and actions of their opponents and teammates,
to maintain a goal-directed behaviour (e.g., to score a try; to
tackle an opponent) (Passos et al., 2009). Performing as a sub-
unit means that a group of athletes must act collectively to meet
the performance standards that are more appropriate to each
game sub-phase, and also these standards are not available to
each player as a single entity (Bonabeau, Theraulaz, Deneub-
ourg, Aron, & Camazine, 1997; Camazine et al., 2001; Couzin,
Krause, Franks, & Levin, 2005; Deneubourg, Lioni, & Detrain,
2002). This means that a player’s actions within each subunit
must be related. Therefore, a major concern was: who are the
players that belong to each subunit? Previous research in rugby
union had already measured players’ intra-team interactions
using running correlations which proved to be a suitable tool to
measure how strong a player action (e.g., ball carrier) was re-
lated to the action of a teammate (e.g., right side support player)
(Passos et al., 2011). In this study, we aim to analyze how the
strength of intra-team relations between attackers and between
defenders evolves over time, and also how these intra-team
relations influenced the outcome: to cross or not to cross the
gain line.
A previous study in rugby union analyzed how the interper-
sonal coordination patterns of four attackers in a situation of 4
× 2 + 2 in rugby changed over time (Passos et al., 2011). This
study aimed to analyze the pattern-forming dynamics of an
attacking subunit when facing two defensive lines. For the au-
thors, it is through the perception of their teammates and oppo-
nents’ behaviours that each player acts in order to maintain a
goal-directed behaviour (Araujo et al., 2006; Araújo, Sainhas,
& Fernandes, 2002; Correia et al., 2012). This supports the idea
that collective behaviours in team sports of rugby union are
based on co-adaptation and constrained by the need to maintain
a functional position in relation to the other players in the
neighbourhood (i.e., teammates and opponents). The authors
considered that the attackers’ interpersonal distance is a
key-variable to achieve a functional position. Notwithstanding,
attackers’ interpersonal distances may change due to the need
to perform evasive manoeuvres to prevent being tackled by the
defenders and continuously decreasing the distance to the score
line. To measure the changes in the attackers’ interpersonal
distance, the average of the interpersonal distance among the
four players in the attacking subunit was calculated over time.
The results indicate that attackers aim to maintain a functional
interpersonal distance to the teammates. To do this, each at-
tacking player needs to manage their running line speed re-
garding the running line speed of the other attacking players in
the neighbourhood. It was expected that all the players in an
attacker subunit would decrease the distance to the score line in
a similar fashion. Using each player’s distance to the score line
running correlations were used as a tool to measure the inter-
personal coordination of the four players within the attacking
subunit over time (Passos et al., 2011).
It was possible to identify that the interpersonal distances
between the players of the attacking subunit display different
values under different task constraints. When playing before the
first defensive line the attackers displayed shortest interpersonal
distances (2 m to 4 m) and between the first and the second
defensive line there was an increase on the attackers’ interper-
sonal distances (3 m to 5 m). Data from Passos et al. (2011)
highlight the need for co-adaptation between players within the
attacking subunit. Thus, we hypothesized that also in a match
situation the way that attackers interact with each other differs
according to the proximity to the defenders, and different be-
havioural patterns are found.
In team sports of rugby union, the structural organization
between attackers and defenders is continually changing, offer-
ing several possibilities of action (affordances) that arise and
decay due to players’ continuous interactions. In order to suc-
ceed, players need to cooperate in a coordinated fashion which
requires that each player continuously co-adapts to the behav-
iour of others in the neighbourhood. Thus, collective behav-
iours based on intra-team interpersonal coordination become a
Open Access
crucial issue to success during a match. Teams invest a consid-
erable amount of training to increase the level of success of
attacking subunits (to support this argument, nowadays most of
the teams have an assistant coach who is an expert for the at-
tack). Nevertheless, there are teams in which subunits are more
functional than others, and also the same subunit can be func-
tional only in specific moments of the match. We suggest that
the level of functionality of each subunit could be related to the
number of players involved in it. A subunit that permanently
has the three support players (i.e., right side, left side and axial)
available to receive the ball, thus ensuring game continuity,
gathers the required task constraints to be functional. Therefore,
we aim to answer two different questions with this study: 1)
How can we determine which players are involved in each at-
tacking subunit? 2) How do the players within an attacking
subunit coordinate so they can gain advantage over the defend-
ers? Therefore, we intend to capture interpersonal coordination
patterns when players run in the same direction, at the same
speed toward the score line, fulfilling the first principle of a
rugby union match: go forward in the playing field. For that
purpose we used running correlations. We considered that there
was a decrease on interpersonal coordination not only when the
correlation value was null (i.e., r = 0 values) but also when the
correlation values changed from high (i.e., r values from 0, 8 <
r < 1) to r values below 0.7. We hypothesized that the estima-
tion of high values of correlation between players is a relevant
aspect to succeed in rugby union.
The Human Ethics Research Committee of the Faculty of
Human Kinetics/Technical University of Lisbon approved the
study. The sample consists of 15 collective movements (N =
15) performed by rugby union teams, selected from three games
of the Portuguese National Championship during the 2010/2011
season. The criteria to choose the movements under analysis
were: 1) the movements under analysis should begin in a static
moment (e.g., scrum, lineout, or ruck) and end in another static
moment (e.g., from scrum to ruck; or from ruck to ruck); and 2)
in these movements, players used only the hands to pass the
ball to the teammates, meaning that we did not consider for this
study movements with the foot; 3) each player must move in
the same direction as a teammate.
We divided the data analysis in two stages. For the first stage
of analysis, we considered that not all the players within the
rugby pitch were directly involved in the attacking or defending
movements, thus the criteria to select the players who might
belong to each attacking subunit depended on the position of
players related with the ball carrier, i.e., the players in the right
side support; the left side support and the rear (axial) support.
Therefore, for the first stage of data analysis, we ran the corre-
lations between the ball carrier and the players closest to the
ball carrier (i.e., ball carrier and support players that received a
pass; the defender closest to the ball carrier and the defender
closest to the support player that received the pass). A 0.4-s
window size (i.e., 10 data-point window) was shifted frame by
frame (i.e., every 0.04 s) and, at each shift, a correlation value
was calculated. In this way, we obtained a continuous correla-
tion function that continuously described the players interper-
sonal coordination tendencies over time (Meador, Ray, Echauz,
Loring, & Vachtsevanos, 2002). Notwithstanding, teams typi-
cally organize to afford the ball carrier not a single but several
solutions to pass the ball. In order for this to happen, the others
players in neighbourhood should remain close to the ball carrier,
maintaining pace and running line direction. For the second
stage of analysis, we hypothesized that when this happened the
remaining players (e.g., the support players that did not receive
a pass) were positively correlated with the ball carrier and were
also within the attacking subunit. Therefore, it was relevant to
analyze the remaining players involved in the attacking and
defending movements; more specifically, on the second stage
of analysis, we aimed to measure who were the players that also
belonged to each subunit (i.e., those who also had strong and
positive correlation values with the ball carrier or supporting
player despite the fact that they do not touch the ball).
The images were collected using a single video camera Pa-
nasonic VDR-D310, fixed on a tripod Manfrotto, and placed in
a higher plane laterally to the field. The images were stored on
a personal computer as “wmv” files. The images were digitized
using the software TACTO 8.0 at a frequency of 25 Hz (Fer-
nandes & Malta, 2007). The procedure to measure players’
trajectories consisted in tracking the players’ movements using
a mouse peripheral device. For that purpose, we defined a
working point at ground level located between the feet of each
player. This point was tracked, allowing us to get the coordi-
nates in the two-dimensional plane (x and y) of time. Using
four calibration points, the coordinates were then converted
from virtual coordinates (i.e., pixels) to real world coordinates
(x and y), using the method of Direct Linear Transformations
(Abdel-Aziz & Karara, 1971). For that purpose, we used a rou-
tine that runs on MATLAB® R2009b software. As stated before
for the measurement of interpersonal coordination between
players from the same team (i.e., that belong to each attacking
subunit) we resorted to the running correlations (Corbetta &
Thelen, 1996). Results
As previously stated for the first stage of data analysis, we
ran correlations between: 1) the ball carrier and the support
player that received a pass; 2) the defender closest to the ball
carrier and the defender closest to the support player that re-
ceived the pass. Based on the correlation values between at-
tackers as well as on the correlation values between defenders,
the results revealed three types of outputs. In Figure 1(a) the
attackers display a strong and positive correlation (i.e., r values
between 0.8 < r <1) approximately between 3.28 s and 7.16 s,
and simultaneously the closest defenders display lower/oscil-
lating interpersonal correlation values. The attackers cross the
gain line close to 10 s.
We named the first output Play Type I, and it was character-
ized by a strong and positive correlation between attackers and
a fluctuating correlation between defenders. This type of play is
consistent with the attackers success (i.e., crossing the gain
line), getting closer to the score line.
In Figure 1(b) it is possible to observe the opposite of the
previous play type, that is, the defenders achieved strong and
positive correlation values (i.e., r values between 0.8 < r <1)
approximately between 0.32 s and 2.44 s, unlike the attackers
that displayed fluctuations on correlation values. This type of
play was named Play Type II where the defenders prevented the
attackers from crossing the gain line at approximately 2 s. Thus,
the Play Type II was characterized by a strong and positive
correlation between defenders (i.e., r values between 0.8 < r <1)
and fluctuating correlation between attackers, which is consis-
Open Access 211
Figure 1.
Values of interpersonal coordination between attackers and between
defenders. (a) Player’s movement illustrative of success for the attack-
ing team—characteristic of a Play Type I. (b) Player’s movement illus-
trative of failure for the attacking team—characteristic of Play Type
II.tent with an advantage for the defenders. In this type of play the
attackers do not cross the gain line.
Finally, in Figures 2(a) and (b), there is a different behav-
iour from the previous interpersonal coordination patterns, and
even from the same type of play. Still, it is possible in both
figures to observe close correlation values between attackers
and also between defenders. This pattern was defined as the
Play Type III.
In Figure 2(a), both subunits (i.e., attackers and defenders)
display strong and positive intra-team correlation values. Both
subunits (i.e., attackers and defenders) displayed similar inter-
personal coordination patterns and both were in position to
succeed. In Figure 2(b), we did not find a clear pattern of cor-
relation between the attackers or between the defenders. None
of the subunits displayed strong correlation values, as depicted
in Figure 2(b). Concerning the outcome, again none of the
subunits was in a clear position to succeed.
Analysis of Interpers onal Coordinati on V alues of the
Remaining Players Involv ed in the Attacking Subunit
In this second stage of analysis, the correlation values for the
other players not directly involved (i.e., the support players that
do not touch the ball) were also analyzed. In Figure 3(a), in
relation to Play Type I, we verified a strong and positive corre-
lation between the remaining players of the attacking subunit,
and simultaneously a low or inverse correlation between the
defenders closest to each pair of attackers (approximately at
3.28 s to 7.16 s).
Figure 3(b) was related with Play Type II movements and it
is possible to verify that the defenders’ correlations were
strongly positive, while there is a decrease in the attackers’
Figure 2.
(a) and (b) Player’s movement illustrative results of uncertainty for the
attacking team—values of interpersonal coordination between attackers
and between defenders—characteristic of Play Type III.
correlation values between 0.76 s and 2.24 s.
The correlation values in Play Type III (Figures 2(a) and (b))
tend to approach each other, suggesting a similar pattern of
interpersonal coordination between key players of attacking and
defending subunits. The correlation values between the re-
maining players involved in each subunit reinforced the results
mentioned above (Figures 4(a) and (b)) So, the results were
consistent with those for the key players (i.e., ball carrier; sup-
port player that received the ball; closest defenders), meaning
that these key players are representative of their own subunit of
For the three types of play, data revealed that the remaining
players displayed a similar pattern of interpersonal coordination
with the ball carrier than the ball carrier and the support player
that received the ball.
It was possible to recognize the resemblance between these
results and the previous studies mentioned earlier in this paper,
including the fact that there are several coordination patterns to
accomplish the same task solution (Passos et al., 2011). In other
words, there is a large variability of solutions for the same goal.
We observed that, aiming to cross the gain line, the attacker
subunit reorganized in different ways which are captured by the
oscillation in the running correlation values.
Data revealed that when the defenders achieved a strong in-
terpersonal coordination (i.e., captured with correlation values
between 0.8 < r <1), they succeed in preventing the attackers’
progress in the field. However, disturbances in the interpersonal
coordination within the defender subunit (captured with corre
Open Access
Figure 3.
Values of correlation of the remaining players involved in the subunit
movements. (a) Player’s movement illustrative of success for the at-
tacking team in Play Type I. (b) Player’s movement illustrative of fail-
ure for the attacking team in Play Type II.
lation values between 1 < r < 0.8) due to the attackers’ subunit
movements create opportunities for the attackers to cross the
gain line. Nevertheless, when players within both subunits (i.e.,
attackers and defenders) remain equally coordinated, that does
not reveal a tendency to succeed for any team, so in these situa-
tions players must be in constant search for the moment that the
opposite team loses coordination (please see Figure 2(a)).
Thus we may conclude that high and positive values of cor-
relation between players of the same team (i.e., r values be-
tween 0.8 < r < 1) create possibilities for action that lead a set
of players to succeed, when the opponents display lower or
negative values of correlation (Figure 1).
In order to perceive the possibilities of action that are avail-
able in a particular context, athletes should actively explore the
context resulting in non-linear interactions between players.
This constant search for the best solution to succeed may cause
disturbances in the interpersonal coordination tendencies in the
opposite team, but may also lead to intra-team disturbances,
because players need to continuously adjust to each other.
Based on the data, we may conclude that a breakdown on the
interpersonal coordination within a subunit allows the opposing
team to succeed.
It was possible to confirm the importance of the support
players (even if they do not touch the ball), because they keep
other possibilities of action available for the ball carrier, thus
contributing to a high level of interpersonal coordination within
each subunit, which seems to be a relevant aspect for success in
rugby union. However, we know that new solutions emerged
when players disturbed the interpersonal coordination of the
opposite team, i.e., when the opposing team displayed lower or
Figure 4.
(a) and (b) Player’s movement illustrative of uncertainty results for the
attacking team—values of interpersonal coordination of the remaining
players involved in Play Type III.
inverse values of interpersonal coordination. Based on previous
studies, it only makes sense to search for new solutions within
the so-called critical regions, which were characterized by short
interpersonal distances (Passos et al., 2008). Within these criti-
cal regions, variables such as changes in running line speed or
adjustments in interpersonal distances may be useful tools that
players have to disturb the opponent coordination patterns
(Correia et al., 2012; Passos et al., 2008; Passos et al., 2011).
Therefore, coaches, instructors or teachers should be encour-
aged to create learning environments that promote variations of
relative velocity, or the management of players’ interpersonal
distances enhancing the odds to succeed.
As a take-home message, we may conclude that interpersonal
coordination is an important variable to succeed in rugby union.
However, it is not the only variable that leads to success, espe-
cially when both attackers as well as defenders were strongly
correlated, in these situations there are other “unknown” or
“hidden” variables that might also seem to constrain players’
behavioural outcome.
Further Research
In this section we want to encourage the extension of scien-
tific research in this same area, suggesting, however, new
problems: 1) to extend this study to different age groups, as
well as different levels of performance, in order to reveal the
possible existence of different behavioural patterns; 2) to relate
the interpersonal coordination with a coordinative variable that
describes the interactive behaviour between attackers and de-
fenders; in that way, which will probably be possible to observe
how the intra-team coordination patterns disturb the attacker-
Open Access 213
Open Access
Figure Captions
Data revealed for the results achieved
orrelation values be-
personal correlation values
black line—the moment the attacking sub-team
e moment the defence stops the at-
es between
Abdel-Aziz, Y. I., & Kat linear transformation
Aristovski, R. (2006). The ecological dy-
defender balance.
subsequent analysis of
the interpersonal coordination between players, and it is
necessary to clarify the figures showing:
1) dashed black line—interpersonal c
een attackers (between the ball carrier and the supporting
player—the last one is the player that passes the line of advan-
tage or is stopped from doing so);
2) continuous gray line—inter
tween defences (defined for this analysis as the direct de-
fences of each of the attackers selected, i.e. those who are clos-
er to them);
3) vertical
sses the advantage line;
4) vertical gray line—th
cking sub-team from crossing the advantage line;
5) solid black line—interpersonal correlation valu
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