Abstract

Sports clubs are often objects of investigation in European research on sport and society. Usually descriptive analyses are carried out and sport clubs are differentiated by structural factors such as size, age, and number of offered sports. However, these factors do not always have to be the distinctive ones as sports clubs are very heterogeneous and have many other features. Therefore, a more explorative analysis was applied using Data Mining for the analysis of the four main problems in German sports clubs. These problems are the adherence and acquisition of volunteers, adolescent competitive athletes, coaches, and members. The data base for the analysis of problems is the Sport Development Report 2007/2008 (n=13,068). Decision trees were estimated for all four problems. The findings suggest that, beside the size of the club, the share of members participating in convivial gatherings and the offered sports are decisive for the severity of these problems. Some problems were higher in soccer, tennis, shooting, and equestrian clubs. With regard to further research, a comparison of Data Mining results in European sports club research would be interesting. Verf.-Referat