INNOVATIVE METHOD FOR ASSESSING THE COMPETITION ACTIVITY OF HIGHLY QUALIFIED CANOEISTS

During sport competition activities, the physical, technical, tactical and psychological fitness of athletes that forms the foundation for the manifestation of their maximal capabilities becomes evident as a polymodal characteristic. Apart from athletic performance, the competition activity in canoeing is characterized by such parameters as speed, pace, distance per stroke etc. On the one hand, the parameters which characterize different competition activity components may be interconnected; on the other hand, they are often only weakly connected. In addition, the above-listed parameters vary during a canoe race which makes it difficult to assess the competition activity of a canoeist. Therefore, it is necessary to search for innovative approaches for assessment of the competition activity that could provide sufficient objectivity and informative value, and trace a path toward refinement of the training process. Research objective – is to develop a new informative method of assessment of the competition activity of canoeists. Research methods and organization. Video shooting, timing and calculation methods were used in the research. Eleven highly-qualified canoeists were selected as research subjects. Results. An innovative method for assessing the competition activity of highly-qualified canoeists was developed. It is based on converting absolute values (meters, strokes/min, km∙hr-1 etc.) of parameters measured during canoe events (distance, pace, speed) into estimated scores (integral index for each measured split of competitive distance and total distance index) which ensures an objective assessment of canoeists’ competitive activities. Conclusion. The proposed innovative method for assessing the competition activity of canoeists based on calculating integral and total distance indices of their competitive activity by respecting the action sequence will allow researchers and coaches to compare and rate canoeists of different levels and estimate the rating dynamics during time periods (training cycles).

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