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Articles

Fantasy sport: a systematic review and new research directions

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Pages 558-589 | Received 25 Sep 2015, Accepted 07 Jun 2017, Published online: 07 Aug 2017
 

ABSTRACT

Research questions: Fantasy sport is an increasingly significant social phenomenon. But what do we actually know about participation in fantasy sport? We examined the extant literature to ask: how has fantasy sport participation been conceptualised; what theoretical frameworks and research approaches have been used; what are their strengths and weaknesses; and what further research is needed to improve our understanding?

Research methods: We conducted a systematic review of academic journal articles relating to fantasy sport participation. Seventy-one articles met the inclusion criteria and we analysed them on several dimensions. We then conducted a meta-evaluation of the research approaches used in the 71 studies and extended this through critical discussion and analysis of future research possibilities.

Results and findings: Fantasy sport participation has been conceptualised in several ways, but most commonly as a form of consumer behaviour. Studies have used various theoretical frameworks and methodologies, but a majority, to date, have employed quantitative, survey-based approaches. These have advantages, enabling researchers to build on each other’s work, but also have certain conceptual and methodological limitations.

Implications: If we are to understand the social significance of fantasy sport and develop appropriate managerial policies around it, we require a well-developed understanding of fantasy sport participation. This research synthesis highlights the strengths and weaknesses of existing research and offers suggestions for how future researchers can advance knowledge in this area. In particular, the synthesis suggests we need to offer more multi-level, critical analysis.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. We did not consider pre-publication online versions in this search. Previous systematic reviews are split on whether or not to include such articles. We decided not to and mention this here to aid replicability.

2. In only including articles that focused directly on academic analysis of fantasy sport, we excluded articles that primarily analysed forms of mediated sport communication, such as sport blogs and fan websites, because, although they incorporated some discussion of fantasy sport, they did not focus directly on it as the principal subject of analysis. In addition, we excluded articles focusing on the educational uses of fantasy sport and articles published in law journals, focusing on specific legal aspects of fantasy sport.

3. We split this category broadly into: (i) ‘consumer behaviour’ and (ii) ‘other’. While finer distinctions could have been made, this categorisation represented the main ‘split’ in the literature and provided the most useful framework for discussion.

4. In some articles, the author(s) explicitly stated their theoretical framework, provided a detailed explanation of the framework and used it clearly to inform data collection and/or analysis and/or discussion. For example, Dwyer (Citation2013) explicitly drew on the ‘attitude-behaviour relationship framework’ in his survey-based study of fantasy sport participants’ attitudes and behaviour toward the National Football League (NFL). In others, the author(s) explicitly developed a theoretical framework through their analysis and clearly articulated this framework. For example, Halverson and Halverson (Citation2008) drew on a multiple case study of three fantasy sport leagues to develop a framework of ‘competitive fandom’. In other articles, authors often discussed some relevant theory, or concepts, but did not articulate a clear theoretical framework. We categorised these as quasi-theoretical.

5. In examining samples, we assigned articles to the following categories: (i) Random; (ii) Purposive; (iii) Convenience; and (iv) Snowball. As sampling terminology is not consistent across studies, we sought to establish as clear criteria as possible. We categorised studies as ‘random’ when they employed a specific random sample from a larger pool. For example, Dwyer (Citation2011a) used a random sample of 1600 from a pool of 5000 randomly selected Fantasy Sport Trade Association member participants. We categorised studies as ‘purposive’ when they deliberately targeted participants. For example, Billings and Ruihley (Citation2013) used trained recruiters to contact, through interpersonal means, ‘adult traditional sport consumers (that had not played fantasy sport in the last 12 months)’ and ‘adult fantasy sport consumers’. We categorised studies as ‘convenience’ when they either surveyed students, or posted links to surveys on websites or message-boards. Where studies used a combination of purposive and convenience sampling with snowball sampling, they were categorised accordingly.

6. It is difficult to make direct comparisons about authorship across systematic reviews. However, Weed (Citation2006), in his systematic review of sports tourism research, found only five authors that had been involved with three or more articles, across a total of 80 articles, compared to 14 authors here, across a total of 71 articles. This suggests a much higher concentration of authorship in fantasy sport than in sports tourism, something that might well be expected for a comparatively new research area.

7. It is worth noting here, as discussed earlier, that this high incidence is due, in part, to the work of a sub-set of authors in the field. For example, one author wrote, or co-wrote seven of the eight articles using the AB-R framework. In addition, five of the seven articles using the U&G framework involved three authors.

8. These findings are not unusual for a meta-evaluation on a social science topic, especially when a large proportion of that literature falls within the discipline of management/marketing. For example, while Weed’s (Citation2006) meta-evaluation of sports tourism research found a slightly lower proportion of studies using primary data (68%, compared to 85% here), the proportion of studies using quantitative data was very similar (67%, compared to 62% here).

9. We would particularly like to thank one of the anonymous reviewers for this suggestion.

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