Six sporting worlds: a cluster analysis of sports participation in the EU-25

The aim of this study was to identify clusters of European nations grouped by sports participation outcomes (organizational context and intensity of sports participation), in order to provide sensible groupings for international comparisons. Sports participation data for the EU-25 were distracted from the 2004 Eurobarometer survey. Both a hierarchical as a K-means clustering method was used to identify groupings of countries that are homogeneous in terms of sports participation profiles. Six clusters of countries could be identified: (i) non to average fitness countries; (ii) active club countries; (iii) average non-organized countries; (iv) average school countries; (v) active multi-context countries; and (vi) very active countries. Considerable differences in sports participation profiles between European countries are made clearer when viewed across clusters of countries grouped by actual outcomes. This empirically derived taxonomy has advantages over ad hoc systems for comparing sports participation and for deciding which countries appear to have the most comparable participation profiles. Moreover, it shows that policy strategies to increase sports participation in European countries need a differentiated approach and have to take account for the fact that the provision and intensity of sport is at a quite different level in all six sporting clusters.The aim of this study was to identify clusters of European nations grouped by sports participation outcomes (organizational context and intensity of sports participation), in order to provide sensible groupings for international comparisons. Sports participation data for the EU-25 were distracted from the 2004 Eurobarometer survey. Both a hierarchical as a K-means clustering method was used to identify groupings of countries that are homogeneous in terms of sports participation profiles. Six clusters of countries could be identified: (i) non to average fitness countries; (ii) active club countries; (iii) average non-organized countries; (iv) average school countries; (v) active multi-context countries; and (vi) very active countries. Considerable differences in sports participation profiles between European countries are made clearer when viewed across clusters of countries grouped by actual outcomes. This empirically derived taxonomy has advantages over ad hoc systems for comparing sports participation and for deciding which countries appear to have the most comparable participation profiles. Moreover, it shows that policy strategies to increase sports participation in European countries need a differentiated approach and have to take account for the fact that the provision and intensity of sport is at a quite different level in all six sporting clusters.A