ABSTRACT
Data mining and knowledge discovery were introduced in earlier chapters, so the role of this chapter is to go into more detail about data mining in sports. The chapter also covers knowledge discovery through data mining techniques. The chapter explains the use of knowledge discovery techniques to create hypotheses using automatic (non-directed) analyses of databases. The philosophical debate between supervised and unsupervised analyses is discussed with reference to some early data mining activities in sports science. The stages of data selection, data cleaning, data analysis, filtering, mapping and visualisation are described using an example of tennis point analysis. This example is also used in considering data modelling and data warehouse design for knowledge discovery environments.
