REFERENCE: Sarmento, H., Barbosa, A., Anguera, M.T., Campaniço, J., & Leitão, J. (2013). Regular patterns of play in the counterattack of the FC Barcelona and Manchester United football teams. In D. Peters & P. O´Donoghue (Eds.), Performance Analysis of Sport IX (pp. 59-­‐66). London: Routledge. 59 CHAPTER 9
Regular patterns of play in the
counterattack of the FC Barcelona and
Manchester United football teams
Hugo Sarmento, António Barbosa, Maria T. Anguera, Jorge Campaniço
and José Leitão
9.1 INTRODUCTION
Traditionally, the frequency of occurrence of events (e.g., number of passes made
in a certain area of the field or how many times a team committed an error) have
been used as indicators of performance. Studies based on the analysis of frequency
of certain performance parameters provide important information for coaches and
athletes, enabling advances in training processes. However, the game of football is
characterized by great complexity that make it difficult to objectify its observation
and analysis.
The expression “playing style” is now commonly used by the fans, coaches
and in academic settings. However, this is a complex concept that is influenced by
many factors, like the strategy or philosophy of the playing style (i.e., a plan of
how a team should play), the tradition, identity and history of the club, as well as
the specific environment that characterizes the game (e.g., quality of opposition,
match status). Determining which style of play is more effective has long been
disputed by soccer performance analysts including match-performance researchers.
Initially the published data advocated a direct approach to goal (Reep and
Benjamin, 1968) which has created much debate and rebuttal for those who
suggest possession as a key indicator of success (Hughes and Franks, 2005).
Trying to predict future performance on the basis of previous performances is
an important goal for notation analysts. Typically the basis for any prediction
model is that performance is repeatable, to some degree. In other words events that
have previously occurred will occur again in some predictable manner. This type
of prediction is based on the principle that any performance is a consequence of
factors like prior learning, inherent skills and situational variables (James, 2012).
In order to detect regular structures of behavior, T-patterning has been already
been used to establish playing patterns in football. The basic premise here is that
the interactive flow or chain of behaviour is governed by structures of variable
stability that can be visualized by detecting these underlying T-patterns.
Thus, the aim of the present study is to demonstrate the potential of the
software THEME 5.0, for the detection of behavior temporal patterns (T-pattern) in
Performance Analysis of Sport IX
60 the football game, more specifically, in the actions of counter-attack of the F.C.
Barcelona and Manchester United Football teams.
9.2 METHODS
The sample included 24 games (12 per team) from the sporting season 2009/2010
of the F.C. Barcelona and Manchester United teams. The design used in the present
study was based on the observational methodology applied to the acquisition of
data . The matches were analysed through systematic observation by using a
specific instrument to observe the offensive process (Sarmento et al. 2010). The
reliability of data was calculated by the intra and inter observer agreement (Cohen´s
Kappa), and values above 0.90 for all criteria were achieved: i) Type of attack
(0.99, 0.97, intra-observer agreement and inter observer agreement, respectively);
ii) Start of the offensive process (0.94, 0.91); iii) Development of the OP (0.99,
0.98); iv) End of the OP (0.96, 0.95); v) Area where the action was performed
(0.96, 0.93); vi) Interactions contexts in the centre of the game (0.93, 0.91).
The following criteria were used in this study: 1- Type of attack; 2- Start of
the offensive process (OP); 3- Development of the OP; 4- End of the OP; 5- Area
where the action was performed (Figure 9.2); 6- Interactions contexts in the centre
of the game. To analyse the interaction context, we used the concept of the centre
of the game (Castelo, 1992), that is defined as the zone of the field where the ball
moves at a certain instant, through a context of cooperation and opposition of the
influential players in the game, in the specific zone where the player that is in the
possession of the ball is.
For the detection of temporal patterns, we used the software THÈME 5.0, and
the following criteria were used: the minimum number of times a pattern must
occur to be detected was set at 3 and the level of significance was set at 0.05. In
this context, the software THÈME as a program that detects temporal patterns
assumes a particular importance. The temporal patterns recognised are based on an
algorithm described in several publications (e.g., Magnusson, 2000) that was
developed and extensively tested in non-sporting contexts. We can characterize
this algorithm based on the assumption that the flow of complex human behavior
(e.g., sports performance) is based on sequential structure as a function of the time,
has a discrete nature that is not fully detectable without the use of standardized
statistical methods, as well as by the use of behavioral analysis techniques (Borrie
et al., 2002). In the analysis of actions in football, if we have that registration done
in a systematic way, taking into account the successive units in which it breaks
down the flow of practice runs, it is possible to evidence that there are repetitive
temporal patterns of behavior (T-pattern) (Anguera, 2004).
The most valuable contribution of T-patterns arises from the possibility of
detecting particular types of temporal structures (Borrie et al., 2002). Given that
patterns facilitate the detection of hidden structures, they are of significant
importance in the analysis of the football game. This technique of analysis allows
the representation of a specific diagram (Figure 9.1), which corresponds to the
actions that occur in the same order, with distances (relatively to the number of
frames) that remain relatively invariant, always within the critical interval time
(Anguera, 2004).
Regular patterns of play in the counterattack of FC Barcelona and Manchester United
61 9.3 RESULTS AND DISCUSSION
The data analysis revealed the existence of 787 different T-patterns in the team of
the FC Barcelona, ranging from a minimum of 1 level to a maximum of 6 levels
and a minimum of 2 events to a maximum of 9 events. We selected 8 t-patterns (4
per team), in relation to different phases of the counterattack that were analysed in
a detailed way (each pattern occur at least 3 times). Initially we present the
diagram of the software together with the respective graphical representation of the
obtained T-pattern. Subsequently we will put only the visual representations of the
T-patterns obtained.
The first pattern (Figure 9.1a and 9.1b) represents an incomplete T-pattern (it
does not include the end of the offensive process) in relation to the start of a
counterattack sequence (this pattern occurred three times). This counterattack: 1)
was initiated by an interception of the ball in the left corridor (zone 6) in an
interaction context of numerical superiority, 2) followed by a short pass
(diagonally forward) in the central defensive midfield (zone 5) in a context of
numerical superiority; 3) a player performed the reception/control of the ball (zone
9) in a interaction context of numerical equality, 4) and then, the sequence
developed through a short pass (diagonally forward) performed in zone 5
(numerical inferiority); 5) this pass is followed by a reception/control of the ball by
a colleague in zone 8 (numerical superiority).
Performance Analysis of Sport IX
62 Figure 9.1a Diagram of the T-Pattern 1 – Barcelona
Figure 9.1b T-Pattern 1 – Barcelona
In a general way, there is a similar feature in the selected F. C. Barcelona tpatterns (Figures, 9.1a and b, 9.2, 9.3, 9.4), i.e., the sequences start through an
interception of the ball in the left corridor (zone 6) in terms of numerical
superiority, after that, there was a quick transfer of the game center, from the right
to the left side, trying to take advantage, probably, of the imbalance of the
opposing defensive structure (numerical equality). The sequences are developed
through actions like the conduction of the ball with the intention of displacing the
center of the game in the field of the game, to the areas close to the penalty area. In
relation to the analysis of the sequences that end through a shot with a scored goal
allowed us to understand (beyond the fact that these sequences are developed by
the left corridor) that these shots are performed in the central zone of the offensive
sector (zone 11) in conditions of numerical inferiority. All the presented patterns
are repeated at least 3 times.
Regular patterns of play in the counterattack of FC Barcelona and Manchester United
Figure 9.2 T-Pattern 2 - Barcelona
63 Figure 9.3 T-Pattern 3 – Barcelona
Figure 9.4 T-Pattern 4 - Barcelona
Relatively to the Manchester United team, the data analysis revealed the
existence of 118 different T-patterns (Figures 9.5, 9.6, 9.7, 9.8), ranging from a
minimum of 1 level to a maximum of 5 levels and a minimum of 2 events to a
maximum of 8 events.
In a similar way to the patterns found relatively to the FC Barcelona team, the
selected Manchester United T-patterns showed that the sequences of the
counterattacks start in the central zone of the defensive midfield (zone 5), in a
context of numerical superiority, and are developed in the left corridor through
actions like the short pass to forward, the diagonal pass forward, and
reception/control of the ball, in contexts of numerical equality. The last pass came
from the left corridor (zone 7), and the sequences finished in the central zone of the
Performance Analysis of Sport IX
64 offensive midfielder (zone 8 and 11), through a shot inside or a shot with a scored
goal.
Figure 9.5 T-Pattern 5 - Manchester
Figure 9.6 T-Pattern 6 – Manchester
Figure 9.7 T-Pattern 7 - Manchester
Figure 9.8 T-Pattern 8 - Manchester
When we analyzed the obtained results for the two studied teams we
observed that much more patterns were detected for the team of Barcelona (n =
787) compared with the Manchester United team (n = 118). This suggests that the
offensive sequences of Barcelona have a more defined temporal and sequential
structure than the sequences of counterattack of Manchester, which seem to reveal
a greater variability of the behaviors performed by this team.
On the other hand, when we analyzed the patterns presented above jointly,
we found that there are similar aspects. Though, these counterattack sequences
begin in the central zone (Manchester) or right zone (Barcelona) of the defensive
Regular patterns of play in the counterattack of FC Barcelona and Manchester United
65 midfield in situations of relative numerical superiority, developed subsequently in
the left side of the offensive midfielder. However, while the players of the
Barcelona team used actions like conduction of the ball and dribble to progress on
the field of play, the players of Manchester team make it through the use of short
passes. In both teams, the effectively ending sequences (e.g., goal, shot defended
by the goalkeeper, etc.) are preceded by actions (reception/control of the ball,
shooting) in the central sector of the offensive sector (zone 11) in interaction
contexts of numerical inferiority.
9.4 CONCLUSIONS
The results show that many temporal patterns exist in soccer, namely in the teams
of FC Barcelona and Manchester United The number (787, 188, respectively),
frequency (at least three repetitions for each of the previously mentioned patterns)
and complexity (ranging from 1 to 6 and 1 to 5 levels, respectively) of the detected
patterns indicate that sport behavior is more synchronized than the “human eye”
can detect.
This type of analysis allows us to know and to characterize the regular
structures of offensive sequences in football teams. The T-patterns detected in
these successful teams allowed us to know how that process is developed in an
effective way. This information is relevant, on the one hand for the team itself
because it makes it possible to conceive training exercises in order to increase this
efficiency, and on the other hand it allows, for example, that the opposing coaches
can develop strategies to prevent that the Barcelona and Manchester United teams
perform these transitions effectively.
Through the use of this methodology, the coaches can have new tool to
analyze the game so different from the tools currently available. Now they can
analyze the patterns of play that most often induce to the effectiveness or
ineffectiveness of his team or opposing teams. It becomes thereby possible to
complement in a scientific way the analysis that usually is performed through "the
naked eye”.
9.5 REFERENCES
Anguera, T., 2004, Hacia la búsqueda de estructuras regulares en la obsservación
del fútbol: detección de patrones temporales. Cultura, Ciencia y Deporte, 1(1),
pp. 15-20.
Borrie, A., Jonsson, G.K. and Magnusson, M.S., 2002, Temporal pattern analysis
and its applicability in sport: an explanation and exemplar data. Journal of Sports
Sciences, 20(10), pp. 845 - 852.
Castelo, J., 1992, Conceptualização de um modelo técnico/tático do jogo de
futebol. Identificação e caraterização das grandes tendências evolutivas do jogo
das equipas de rendimento superior. Tese de Doutoramento, (Lisbon, Portufal:
Universidade Técnica de Lisboa).
Performance Analysis of Sport IX
66 James, N., 2012, Predicting performance over time using a case study in real
tennis, Journal of Human Sport and exercise, 7(2), pp. 421-433.
Hughes, M. and Franks, I., 2005, Analysis of passing sequences, shots and goals in
soccer. Journal of Sports Sciences, 23(5), pp. 509-514.
Magnusson, M., 2000, Discovering hidden time patterns in behavior: T-patterns
and their detection. Behavior Research Methods, Instruments & Computers, 32,
pp. 93-110.
Reep, C. and Benjamin, B., 1968, Skill and chance in association football. Journal
of the Royal Statistical Society, Series A, 131, pp. 581-585.
Sarmento, H., Anguera, M.T., Campaniço, J. And Leitão, J., 2010, Development
and validation of a notational system to study the offensive process in football.
Medicina (Kaunas), 46(6), pp. 401-407.