Neural Network Modelling for Sports Performance Classification as a Complex Socio-Technical System

Ivars Namatēvs, Ludmila Aleksejeva, Inese Poļaka


Extraction of meaningful information by using artificial neural networks, where the focus is upon developing new insights for sports performance and supporting decision making, is crucial to gain success. The aim of this article is to create a theoretical framework and structurally connect the sports and multi-layer artificial neural network domains through: (a)     describing sports as a complex socio-technical system; (b)   identification of pre-processing subsystem for classification; (c)   feature selection by using data-driven valued tolerance ratio method; (d) design predictive system model of sports performance using a backpropagation neural network. This would allow identifying, classifying, and forecasting performance levels for an enlarged data set.


Classification; data pre-processing; multi-layer neural networks; sports performance

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