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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.
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