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The planning of athletic training based on probabilistic Petri Nets models

The paper proposes and develops a new model based on probabilistic Petri Nets suited to reflect the progress of the athletic performance of one individual and of a group of individuals. The training techniques, their appropriate succession and grouping, the immediate results obtained after applying specific training methods are integrated and reflected by the developed model. The model was elaborated based on the training activities and on the athletic performance evaluation of five national level track and field athletes for a complete training cycle. The maximum isometric force value obtained for 5 seconds long voluntary contractions of the leg extensor muscles of each subject was the main parameter used to evaluate the individual progress after a training sub-cycle. The data resulted after the evaluation sessions were used to estimate the training path followed by each athlete. The training path planning was exemplified in the case of one athlete for a complete training cycle. The model was validated using measured data obtained during evaluation sessions carried on in similar conditions in the case of the same group.