Taking the match data of world elite male players as samples and using the powerful self-learning functions of artificial neural network, the present paper constructs the diagnostic model of the winning factors in table tennis matches. Based on the major technical and tactical indexes of table tennis matches, this model could be used to effectively diagnose the winning probabilities of matches. It could also be used to calculate the weight values of major technical and tactical indexes of the winning factors, providing scientific guidance for training.
© Copyright 2008 Proceedings of First Joint International Pre-Olympic Conference of Sports Science and Sports Engineering. Volume I: Computer Science in Sports.. Veröffentlicht von World Academic Union. Alle Rechte vorbehalten.