Swimmer Assessment Model (SWAM): Expert System Supporting Sport Potential Measurement

Abstract

A swimmer’s potential can be exploited to the full if an individual approach is applied to training early enough. In the initial stage of a competitor’s career, it is hard to say whether the person will reach the world level. It is influenced by factors related to physical and mental characteristics, swimming technique, or the current skills level of the athlete. Some of them cannot be improved by swimmers; however, a few of these factors can be affected and upgraded by working on them. The data from 30 swimmers were collected in the research. Then, adopting the COMET method, the values of attributes characteristic for the athletes were entered into the proposed model to determine the predispositions of each of them. The applied method proved to be effective in assessing the parameters of competitors, and at the same time, it is a modern approach free of the rank reversal phenomenon. In addition, the model obtained allows for the study of input data to check how the change of a given criterion will affect the overall rating. The model developed is forward-looking. The results are satisfactory but can be improved to analyze somatic traits better and achieve more accurate predictions.

Keywords

• COMET
• decision analysis
• decision support systems
• decision theory
• expert systems
• fuzzy systems