The motives and behaviour of sports fans are heavily researched. Past work has distinguished "fans" and "supporters" on engagement with teams or athletes and identified "non-fans" who have little interest in sport; the latter are rarely investigated further. Sport's ubiquity, both socially and in media, means that, unusually, disinterested people are often interacting with sport. A better understanding of non-fans could assist strategies to grow sports markets and encourage engagement. This paper describes a study, using both theory-driven and machine learning approaches, of types of self-identified non-fans of a professional sport. A nationally representative sample of 3,496 adults enabled investigation of non-fandom. Five segments of non-fans are identified, differing in terms of consumption of and passion for professional sport. There is a clear hierarchy of likelihood to consume, driven by social contacts, experiences and access to the product, and impeded by satisfying alternatives. To enable easier practical application of this work, a simplified (four question) segmentation process is also presented. This simplified process maintains a high degree of classification accuracy.