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Record W4410597652 · doi:10.9741/2327-8455.1499

The Nexus of Sports Fandom and Sports Wagering: A Scoping Review

2025· review· en· W4410597652 on OpenAlexaff
Brandon Mastromartino, Michael L. Naraine, Henry Wear

Bibliographic record

VenueUNLV Gaming Research & Review Journal · 2025
Typereview
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsBrock University
Fundersnot available
KeywordsFandomNexus (standard)AdvertisingEngineeringSociologyMedia studiesBusiness

Abstract

fetched live from OpenAlex

This scoping review examines the intersection of sports fandom and sports betting, with a particular focus on the marketing considerations involved in this relationship. Sports fandom, driven by strong emotional investments and team identification, plays a critical role in shaping betting behaviors. As this relationship becomes increasingly complex, it is essential to explore the underlying motivations and behaviors of sports fans who engage in betting, the ethical implications of marketing practices targeting this group, and the methodologies used to study this intersection. To address these relationships, this review examines four key areas: motivations for sports fans to engage in betting, responsible marketing practices, the methodological approaches used in current studies, and future research directions. This review highlights that fans are motivated to bet not only by potential financial gain but also by socialization, excitement, and loyalty to their teams. However, this emotional engagement raises ethical concerns about the normalization of betting in marketing, especially in targeting vulnerable populations. The review also identifies a reliance on quantitative methods in the existing literature and calls for more qualitative and longitudinal research. Finally, the study highlights the need for further exploration of diverse demographics and the impact of new technologies on the relationship between fandom and betting. This review offers insights for researchers, marketers, and policymakers to better understand and navigate the evolving landscape of sports betting and sports fan behavior.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.050
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.703
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0500.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.002
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.172
GPT teacher head0.501
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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