In crossover mixed analyses, one form of data is analyzed applying techniques that usually are associated with the alternative paradigm in order to yield a higher level of data integration. This basic principle is implemented in equal-status studies and in quantitative- as well as in qualitative-dominated approaches. Focusing on the latter, data conversion has been a vital issue of mixed methods research for many years, likely because it entails quantitizing narrative data to provide a basis for descriptive and inferential statistical analyses. Referring hereon, this article presents a qualitative-dominated crossover mixed methods study dealing with the problem of honorary work in German sports clubs, an issue that has been intensively discussed in sports and in other areas of society due to some alarming developments in social life. In this process, the issue of honorary work is utilized as an example of demonstrating a methodology. The design presented in this article involved use of a crossover analysis that converts narrative data into numerical data and involves analysis of the new data set using multiple correspondence analysis (MCA) with the aim of discovering patterns among the multidimensional data. In turn, these patterns are interpreted against the background of the first qualitative strand to enhance our understanding. Thus, this study is to be referred to as qualitative-dominated because the sets of qualitative analyses are more comprehensive and important and the researchers have taken a stance that is constructivist, while concurrently believing that quantitative data adds value to this approach.