Gudberg K. Jonsson

Temporal pattern analysis and its applicability in sport: an explanation and exemplar data

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.

Hidden patterns of play interaction in soccer using SOF-CODER.

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.

Dynamics of the game in soccer: Detection of T-patterns

Abstract 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 teams goal in order to disrupt the latters 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.

Identifying and analyzing motor skill responses in body movement and dance.

The present article analyzes the diversity of motor skills related to three different kinds of instructions: descriptive, metaphoric, and kinesic, with a special emphasis on the detection of temporal patterns (T-patterns). Twelve undergraduates studying sport and physical education, but without experience in dance, were observed during 24 lessons of Body Movement, a discipline based on creative dance, mime dance, and motor skill improvisation. Using observational methodology and technology applied to movement, the aim of this article was to adapt the Observational instrument of Motor Skills (OSMOS) (Castañer, Torrents, Anguera, & Dinušová, 2008) so as to create an instrument capable of analyzing the motor skill responses generated in lessons of Body Movement and Dance. The results, as reflected by the T-patterns detected, show that (1) participants try to generate their own motor skills but copy some fundamental components of the instructions, and (2) the criterion of stability in two configurations (support and axial) is the predominant category. Sequential and coordinated locomotion also appears to be very relevant.

Identifying and analyzing the construction and effectiveness of offensive plays in basketball by using systematic observation.

In the field of sports research, there is a growing need for the rigorous collection of data that provide empirical evidence about the complex reality they refer to. Although sports psychology research has advanced considerably in recent years, in both extent and quality, one area of research that remains relatively unexplored is the dynamics of the sports group and the influence of the group on its members (George & Feltz, 1995; Widmeyer, Brawley, & Carron, 1992). Key aspects in this regard include the presence of regularities that are not detectable through visual inference or traditional methods of data analysis, the lack of standard observation instruments, and, assuming priority, the need to develop powerful, computerized coding systems, all of which must form part of an approach that is suitable for natural and habitual contexts. The present study is part of a broader research project concerning ACB teams (first Spanish basketball division) and considers the interaction context before teams try to score (where this is understood as how teams create scoring opportunities) as the core aspect that links team play. This investigation proposes a new model of analysis for studying the effectiveness and construction of offensive basketball plays in order to identify their outcomes, thus providing coaches with an important device for improving or consolidating them.

T-pattern analysis for the study of temporal structure of animal and human behavior: A comprehensive review

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.

Observing the paraverbal communication of coaches in competitive match situations

The present study examines the relationship between the verbal communication skills and paraverbal communication (both kinesic and proxemic) of indoor soccer coaches in competitive match situations, senior womens competitive level. T-patterns detection analysis provides a sequential analysis of data, illustrating the communicative style and flow of each coach.

Identification of vertical and horizontal movement patterns in cod behavior

The Atlantic cod is one of the most important commercial species known. The behavior of this species, important for fisheries, research and stock assessment, is in many ways masked by extensive horizontal and vertical dispersion in its habitat. The potential of using the Theme software in behavior studies of commercial fish stocks was tested using data from tagging experiments with adult cod in Icelandic waters. The time series were prepared for T-pattern analysis, including detection and delimitation of tidal influence in the data and event basing raw data according to predefined events. A high number of temporal patterns were detected, patterns of repeated vertical movements and speed and acceleration changes. A number of specific temporal patterns were also identified within and across vertical movements of individual cod. Future objective is to explore these patterns in relation to environmental factors and horizontal location.

Evaluating multimodal human-robot interaction: a case study of an early humanoid prototype

Multimodal natural behavior of humans presents a complex yet highly coordinated set of interacting processes. Providing robots with such interactive skills is a challenging and worthy goal and numerous such efforts are currently underway; evaluating the progress in this direction, however, continues to be a challenge. General methods for measuring the performance of artificially intelligent systems would be of great benefit to the research community. In this paper we describe an approach to evaluating human-robot multimodal natural behavior. The approach is based on a detailed scoring and spatio-temporal analysis of the structure and patterning of live behavior, at multiple temporal scales, down to the decisecond level. The approach is tested in a case study involving an early virtual robot prototype, Gandalf, which is capable of real-time verbal and non-verbal interaction with people. Our analysis includes a comparison to a comparable human-human dyadic interaction scenario. Our main objective is to develop a methodology for comparing the quality and effectiveness of human-robot interaction between a wide variety of such systems. Early results indicate that our approach holds significant promise as a future methodology for evaluating complex systems that have a natural counterpart.

How Game Location Affects Soccer Performance: T-Pattern Analysis of Attack Actions in Home and Away Matches

The influence of game location on performance has been widely examined in sport contexts. Concerning soccer, game-location affects positively the secondary and tertiary level of performance; however, there are fewer evidences about its effect on game structure (primary level of performance). This study aimed to detect the effect of game location on a primary level of performance in soccer. In particular, the objective was to reveal the hidden structures underlying the attack actions, in both home and away matches played by a top club (Serie A 2012/2013—First Leg). The methodological approach was based on systematic observation, supported by digital recordings and T-pattern analysis. Data were analyzed with THEME 6.0 software. A quantitative analysis, with nonparametric Mann–Whitney test and descriptive statistics, was carried out to test the hypotheses. A qualitative analysis on complex patterns was performed to get in-depth information on the game structure. This study showed that game tactics were significantly different, with home matches characterized by a more structured and varied game than away matches. In particular, a higher number of different patterns, with a higher level of complexity and including more unique behaviors was detected in home matches than in the away ones. No significant differences were found in the number of events coded per game between the two conditions. THEME software, and the corresponding T-pattern detection algorithm, enhance research opportunities by going further than frequency-based analyses, making this method an effective tool in supporting sport performance analysis and training.