engleski

Structural Analysis of Knowledge Based on Specific Atributes of the Game of Basketball

The purpose of this work was to determine the structure of latent factors, to identify and analyse groups of game tasks under specifi c attributes and variables, to classify the tasks into relatively homogenous groups, and to determine the differences between the acquired groups of tasks. In order to achieve the above mentioned it was necessary to construct a measuring instrument (questionnaire) for the registration of knowledge in the game of basketball. For the characterisation of entities, 16 specifi c attributes were chosen, according to which ten competent experts performed the assessment. Within the research space, factor analysis under component model was used, along with Guttman-Kaiser criterion and OBLIMIN rotation. Three latent dimensions in the space of specifi c game attributes were isolated: information component, energy component (game intensity) and socio-motor interaction. Along with factor analysis, hierarchical method of classifi cation was used, where the tasks in the space of specifi c game attributes were classifi ed into three homogenous groups. In the space of specifi c attributes three groups were acquired and they were interpreted as A, B and C. • Group A – tasks that demand high energy component, low socio-motor interaction and low information component, • Group B – tasks that demand above average information component, a bit lower energy component and below average socio-motor interaction and, • Group C – tasks that demand high level of socio-motor interaction, low energy component and medium information component. Objectively scientifi cally arranged groups of associated data can directly infl uence the creation of curriculum and syllabus for basketball players training, evaluation of players’ performance, and they make the foundation for the realization of further researches in the fi eld of team sports games analysis.

Tasks; Attributes; Experts; Factor analysis; Cluster analysis; Discriminant analysis

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