Quantitative analysis of sports performance has been shown to produce information that coaches can use within the coaching process to enhance performance. Traditional methods for quantifying sport performances are limited in their capacity to describe the complex interactions of events that occur within a performance over time. In this paper, we outline a new approach to the analysis of time-based event records and real-time behaviour records on sport performance known as T-pattern detection. The relevant elements of the T-pattern detection process are explained and exemplar data from the analysis of 13 soccer matches are presented to highlight the potential of this form of analysis. The results from soccer suggest that it is possible to identify new profiles for both individuals and teams based on the analysis of temporal behavioural patterns detected within the performances.

A basic tenet in the realm of modern behavioral sciences is that behavior consists of patterns in time. For this reason, investigations of behavior deal with sequences that are not easily perceivable by the unaided observer. This problem calls for improved means of detection, data handling and analysis. This review focuses on the analysis of the temporal structure of behavior carried out by means of a multivariate approach known as T-pattern analysis. Using this technique, recurring sequences of behavioral events, usually hard to detect, can be unveiled and carefully described. T-pattern analysis has been successfully applied in the study of various aspects of human or animal behavior such as behavioral modifications in neuro-psychiatric diseases, route-tracing stereotypy in mice, interaction between human subjects and animal or artificial agents, hormonal–behavioral interactions, patterns of behavior associated with emesis and, in our laboratories, exploration and anxiety-related behaviors in rodents. After describing the theory and concepts of T-pattern analysis, this review will focus on the application of the analysis to the study of the temporal characteristics of behavior in different species from rodents to human beings. This work could represent a useful background for researchers who intend to employ such a refined multivariate approach to the study of behavior

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Traditional approaches to the quantification of team sports have proved to be limited in their ability to identify complex structural regularities that, despite being unobservable, nonetheless underlie the development of the sporting contest between opposing teams. This paper describes a method for detecting the dynamics of play in professional soccer through the analysis of temporal patterns (T-patterns). The observation instrument used was SOF-5, which is especially designed for studying the dynamics of the game in soccer. The recording consisted of within-session monitoring using the MATCH VISION STUDIO 3.0 software, while the THEME software was used to detect and analyse T-patterns. These T-patterns revealed regularities in the playing style of the observed team, FC Barcelona. The structures detected included a ball possession pattern, whereby the ball was first kept in the central zone before being played forward, through several moves, into the zones closest to the opposing team's goal in order to disrupt the latter's equilibrium. The results obtained show that it is possible to identify stable temporal structures that provide information about concurrent interaction contexts with respect to lateral position and zone. As such, the proposed methodology appears to be useful in detecting complex structures within the game of soccer, structures which may help coaches to design attacking and defensive strategies.

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Traditional methods for quantifying sport performances are limited in their capacity to describe the complex interactions of events that occur within a performance over time. The following article outlines a new approach to the study of actions between players in team sports-mainly, soccer. Since the observational design is nomothetic, point, and multidimensional, an observational and data-collecting instrument has been developed. The instrument is mixed and combines a field format with a category system for game events, as well as an ad hoc instrument that considers the game actions of one or both teams, each recorded according to the same criteria. The article also outlines a new approach to the analysis of time-based event records-in this case, sports performance-known as T-pattern detection. The relevant elements of the T-pattern detection process are explained, and exemplar data from analyses of soccer matches are presented to highlight the potential of this form of data analysis. The results suggest that it is possible to identify new kinds of profiles for both individuals and teams on the basis of observational criteria and a further analysis of temporal behavioral patterns detected within the performances.

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