Appliance of Neural Networks in Basketball Scouting

These days, data mining is frequently used as a technology for analysing the hugeamounts of data collected in sport. Basketball is one of most popular sports. Due to itsdynamics, a large number of events happen during a single game. Basketball statisticianshave the task of noting as many of these events as possible, in order to provide for theiranalysis. These data are collected by special software applications. In this paper, we useddata from the First B basketball league for men in Serbia, for seasons 2005/06, 2006/07,2007/08, 2008/09 and 2009/2010. During these five seasons, a total of 890 games wereplayed. These data were analyzed using the feedforward technique in neural networks,which is the most often used technique in analyzing nonlinear sports data. As a final result,we concluded that the most important elements in basketball are two-point shots under thehoop and the defensive rebound, i.e. game "in the paint".