Application of t-pattern detection and analysis in sports research (original) (raw)
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Application to T-pattern detection and analysis in sport research
Metodología de las ciencias del comportamiento, 2001
The following paper introduces a new approach to the analysis of sports and motor skill performance. The approach, known as T-pattern detection, is explained and preliminary data analyses from soccer, boxing, basketball, swimming and motor skill analysis are presented. The data show that specific temporal patterns can be identified within sports performances. The temporal patterns can relate to performance of specific actions (e.g. passes) or movement patterns. Further analysis showed a significant correlation between coaches' ratings' of performance with the number of temporal patterns exhibited by athletes.
Temporal pattern analysis and its applicability in sport: an explanation and exemplar data
Journal of Sports Sciences, 2002
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 pro® les for both individuals and teams based on the analysis of temporal behavioural patterns detected within the performances.
16. Temporal Pattern Analysis and its Applicability in Soccer
2005
In order to optimize sports performance it is considered necessary to employ sound scientific principles of physical conditioning and coaching. One of the most critical of these scientific principles is the rule of specificity. To elicit a high degree of transfer from training into competitive scenarios in key performance attributes such as physical capabilities, skill acquisition and cognitive learning a high degree of specificity of competition is desired in practice situations. To this end the specific requirements of the performance must be investigated and reported. A popular method of investigating the physical demands is that of time-motion analysis where various modes of motion are subjectively or objectively chosen and each are recorded throughout the performance. To date, researchers in soccer have often chosen fewer than 8 modes of motion in their investigations, however it is arguable that this does not provide enough detail to report the high degree of specificity required to configure the precise physical demands of the sport. However, the Bloomfield Movement Classification is recognized as the most comprehensive time-motion analysis method in dynamic field-based sports such as soccer, which includes a combination of 17 modes of motion, 14 directional categories, 4 intensity types and other specific instantaneous movement and sport-specific events including turns, swerves and on the ball activity. Historically, time-motion analyses have reported frequencies, totals and means of individual motions and failed to recognize the interaction of movements which cause several different physiological demands. Temporal pattern (T-pattern) analysis can be performed to identify hidden sequences of events and has been used successfully to identify complex playing patterns in soccer matchplay. It is therefore desirable to perform the T-pattern analysis with the movement of the players. In this chapter we offer the work done by our research team at the Department of Sport Science, University of Hull and the use of T-Pattern detection through application of THEME 5.0. The aim of the following sections is, firstly, to review and critique the current research into the physical demands of soccer and secondly to offer an alternative method of detailing the movements performed by the players with an objective of re-producing specific patterns of movement through T-patterns which can be used to enhance physical conditioning and coaching practices.
Detección de T-pattern en los partidos de fútbol: relación entre las acciones del equipo y de ataque
Scientific Electronic library online (Sciences Carlos III Health Institute), 2015
Sports performance consists of a multiple series of strategies that tend to follow one another. Performance analysis in team sports is usually focused on primary (fundamental skill execution), secondary (scoring) and tertiary (match result) outcomes. While there is general agreement over measuring secondary and tertiary outcomes, literature does not show a unanimous agreement over a unique measure of the primary level of performance. e aim of this study was to investigate primary performance outcomes through an analysis of temporal patterns. In particular, we were interested in verifying if changes in tertiary performance outcomes may be related to changes in primary ones. We selected three soccer matches played by a top club during the Serie A league over the 2012-2013 season in which there was a change in match result between rst and second half (tertiary level of performance). e methodological approach was based on observational design, supported by digital recordings and computer analysis. Data were analyzed with eme 6 beta software, which detects the temporal and sequential structure of datasets, revealing repeated patterns that may regularly or irregularly occur within a period of observation (Tpatterns). Striking di erences were found comparing rst and second half temporal patterns, especially when the nal match outcome showed an improvement of the rst half 's one. Our results suggest that eme software and T-pattern enhance research opportunities by identifying a useful tool to study the link between primary and tertiary level of performance, making this an e ective research and support instrument for sports analysis.
T-pattern analysis in soccer games: Relationship between time and attack actions
Revista de Psicologia del Deporte
Sports performance consists of a multiple series of strategies that tend to follow one another. Performance analysis in team sports is usually focused on primary (fundamental skill execution), secondary (scoring) and tertiary (match result) outcomes. While there is general agreement over measuring secondary and tertiary outcomes, literature does not show a unanimous agreement over a unique measure of the primary level of performance. e aim of this study was to investigate primary performance outcomes through an analysis of temporal patterns. In particular, we were interested in verifying if changes in tertiary performance outcomes may be related to changes in primary ones. We selected three soccer matches played by a top club during the Serie A league over the 2012-2013 season in which there was a change in match result between rst and second half (tertiary level of performance). e methodological approach was based on observational design, supported by digital recordings and computer analysis. Data were analyzed with eme 6 beta software, which detects the temporal and sequential structure of datasets, revealing repeated patterns that may regularly or irregularly occur within a period of observation (Tpatterns). Striking di erences were found comparing rst and second half temporal patterns, especially when the nal match outcome showed an improvement of the rst half 's one. Our results suggest that eme software and T-pattern enhance research opportunities by identifying a useful tool to study the link between primary and tertiary level of performance, making this an e ective research and support instrument for sports analysis.
Frontiers in psychology, 2017
Research in soccer has traditionally given more weight to players' technical and tactical skills, but few studies have analyzed the motor skills that underpin specific motor actions. The objective of this study was to investigate the style of play of the world's top soccer players, Cristiano Ronaldo and Lionel Messi, and how they use their motor skills in attacking actions that result in a goal. We used and improved the easy-to-use observation instrument (OSMOS-soccer player) with 9 criteria, each one expanded to build 50 categories. Associations between these categories were investigated by T-pattern detection and polar coordinate analysis. T-pattern analysis detects temporal structures of complex behavioral sequences composed of simpler or directly distinguishable events within specified observation periods (time point series). Polar coordinate analysis involves the application of a complex procedure to provide a vector map of interrelated behaviors obtained from prospecti...
This study aims to identify the components of physical fitness related performance pattern of similarities and variation among soccer and hockey amateur players. Amateur soccer (N=31) and hockey players (N=31) were recruited from Johor sports school, Malaysia. Standard battery fitness tests were conducted, and principle component analysis (PCA) was employed to identify the most significant physical related performance components and to determine the similarities and variations of the components between the two sports. The PCA after varimax rotation revealed two varifactors (VF) for both soccer and hockey (eigenvalues>1). The VF with higher positive factor loadings contains four main components which include vertical jump, standing broad jump, sit and reach and velocity of agility while the other VF indicated three components containing maximum pushups, sit–ups and V O2max suggesting the need for lower body strength and endurance for soccer players. Similarly, for hockey, the first VF included speed, vertical jump, standing broad jump and agility. The second VF contained maximum pushups, maximum sit-ups, and V O2max recognizing the requirement of lower limb power and core body strength. Identifying physical fitness patterns for amateur soccer and hockey players might help the coaches to structure training programs to suit the need for each sport.
Movement variability and skills monitoring in sports
Sports Biomechanics, 2012
The aim of this paper was to present a review on the role that movement variability (MV) plays in the analysis of sports movement and in the monitoring of the athlete's skills. MV has been traditionally considered an unwanted noise to be reduced, but recent studies have re-evaluated its role and have tried to understand whether it may contain important information about the neuro-musculo-skeletal organisation. Issues concerning both views of MV, different approaches for analysing it and future perspectives are discussed. Information regarding the nature of the MV is vital in the analysis of sports movements/motor skills, and the way in which these movements are analysed and the MV subsequently quantified is dependent on the movement in question and the issues the researcher is trying to address. In dealing with a number of issues regarding MV, this paper has also raised a number of questions which are still to be addressed.
International Journal of …, 2004
It is critical to employ sound scientific principles of physical conditioning and coaching in order to enhance sports performance. One of the most critical of these principles is the rule of specificity. To this end the specific requirements of the performance must be investigated to elicit a high degree of transfer from competition into a training regime which optimises performance in competition. One useful method of investigating physical requirements of sport is time-motion analysis where various modes of motion are subjectively or objectively chosen and timed throughout the performance. To date, fewer than 8 modes of motion have often been chosen in time-motion investigations, however it is arguable that this does not provide a high enough degree of specificity to detail the physical demands of a sport. In this paper, we outline a new approach to timemotion analysis through a method involving 14 modes of timed-motion, 3 'other' non-timed movements, 14 directions, 4 intensities, 5 turning categories and 7 'On the Ball' activity classifications known as the 'Bloomfield Movement Classification' (BMC). The BMC is performed through computerised video-analysis and is highly specific, accurate and reliable. The details of the method are explained within this paper.
This study aims to identify the components of physical fitness related performance pattern of similarities and variation among soccer and hockey amateur players. Amateur soccer (N=31) and hockey players (N=31) were recruited from Johor sports school, Malaysia. Standard battery fitness tests were conducted, and principle component analysis (PCA) was employed to identify the most significant physical related performance components and to determine the similarities and variations of the components between the two sports. The PCA after varimax rotation revealed two varifactors (VF) for both soccer and hockey (eigenvalues>1). The VF with higher positive factor loadings contains four main components which include vertical jump, standing broad jump, sit and reach and velocity of agility while the other VF indicated three components containing maximum pushups, sit–ups and V O2max suggesting the need for lower body strength and endurance for soccer players. Similarly, for hockey, the first VF included speed, vertical jump, standing broad jump and agility. The second VF contained maximum pushups, maximum sit-ups, and V O2max recognizing the requirement of lower limb power and core body strength. Identifying physical fitness patterns for amateur soccer and hockey players might help the coaches to structure training programs to suit the need for each sport.