Appliance of neural networks in Basketball - Basketball board for Basketball Referees

Abstract

What is presented in this paper is a solution that bears large applicable values depending on implementation and realization. The paper describes the methods and the developed software which, based on the action and the movement of the ball, using the neural network, determines the movement of a basketball referee on the court, in order to gain the best view of the action. The solution is developed in Microsoft Visual Studio 2010, written in the programming language C#, reffering to AForge .NET Framework for the support in the aspects of configuring, training and usage of neural networks. AForge .NET Framework is published with LGPL v3 licence. The developed solution is named BBFBR, which stands for Basketball Board for Basketball Referees. Current implementation of the solution is based on drawing the ball's movement on the court, which is the input vector of the neural network, whilst the output vector of the neural network consists of movement coordinates of the referees.The current solution enables calculating optimal ways of the referees movement in the case that the movement of the ball in an action consists of not more than 15 key points, e.g. guiding the ball from one point to another, passing the ball to another player, shooting etc. Applicable value of the current solution bears only the educative purpose because it is possible to apply it for training young basketball referees in the terms of their movement to enable them to be aware of an action and to be able to analyze it.

Using Neural Networks in Preparing and Analysis of Basketball Scouting

“…This other player must score, for two or three points. Until recently, assists were noted only if a player is alone in the paint, but presently they are valid wherever the player is in a position to shoot and score two or three points [10]. In USA, this is quite different, whether in NBA, NSA or WNBA.…”