Discovering Hidden Temporal Patterns in Behavior and Interaction by Magnus S. Magnusson Judee K. Burgoon & Maurizio Casarrubea

Discovering Hidden Temporal Patterns in Behavior and Interaction by Magnus S. Magnusson Judee K. Burgoon & Maurizio Casarrubea

Author:Magnus S. Magnusson, Judee K. Burgoon & Maurizio Casarrubea
Language: eng
Format: epub
Publisher: Springer New York, New York, NY


2.5 Procedure

The performance of the technique under study (the Ouchi-gari) was filmed after a training period lasting approximately 4 months, involving 3 h of practice per week. Overall, a total of 17 throws were learnt. During the video recording each participant performed five of all the techniques that had been learnt, all without opposition from the other judoka and starting from a static position (i.e. it was technical work). Stratified random sampling was used to assign participants and techniques. The quality of the data registered by two observers was assessed by means of Cohen’s kappa [25], with values of this coefficient above 0.8 being regarded as indicative of reliability (inter-observer agreement). This test was conducted using the software GSEQ v.5 for Windows [26, 27] and yielded a kappa value of 0.82. Having ensured the quality of the data, an initial descriptive analysis of the frequency and percentage of occurrence of technical errors was then conducted.

After recording all the throws performed the Match Vision Studio software produces a series of Excel files containing the successive configurations formed by the lines of codes that have changed, with their temporality and duration expressed in frames (25 frames is equivalent to 1 s). These Excel (.xls) files, which provide frequencies for all the registered occurrences of codes, were then transformed successively in order to enable various analyses to be carried out.

The codes of the SOBJUDO-OU observation instrument were then exported to the THEME software [28–30] with the aim of detecting temporal patterns (T-patterns). These T-patterns, which were obtained by means of the algorithm incorporated within THEME v.5 [29], can help to reveal hidden structures and unobservable aspects in sports techniques. The application of the THEME software has proved to be highly effective for studying both team and individual sports [21, 31, 32].



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