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      Request-a-bet sports betting products indicate patterns of bettor preference and bookmaker profits

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          Abstract

          Background and aims

          Request-a-bet services are a modern gambling product delivered via the social network Twitter, which allow sports bettors to design custom bets. The public nature of Twitter data provided a unique opportunity to investigate patterns of bettor preference and the bookmaker profit margin in soccer, the UK’s favorite sport.

          Methods

          Two multi-method studies. Twitter users’ engagement with request-a-bet services was monitored unobtrusively ( n = 1,406), meaning that potential patterns across users’ requests could be observed, and the bookmaker profit margin could be estimated. Twitter users were also surveyed directly ( n = 55), providing self-report measures of request-a-bet usage.

          Results

          Twitter users requested bets with an average potential payoff of £56.5 per £1 risked (median = £9). Overall, 9.7% of requested bets paid-off, but these were mostly bets at short odds. This meant that requests yielded a high bookmaker profit margin of 43.7% (roughly eight times higher than current margins in conventional soccer bets), which increased to 74.6% for bets at longer odds. Requested bets also tended to involve star players from the best teams. Finally, 92.7% of surveyed Twitter users reported placing at least one bet via request-a-bet services (mean = 44.4 bets).

          Discussion and conclusions

          Researchers can use request-a-bet products to increase their understanding of sports betting behavior. Sports bettors should be given information about how much higher the bookmaker profit margin can be in modern sports bets compared to the conventional sports bets that they may be more familiar with.

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          Most cited references28

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          Delayed reward discounting and addictive behavior: a meta-analysis.

          Delayed reward discounting (DRD) is a behavioral economic index of impulsivity and numerous studies have examined DRD in relation to addictive behavior. To synthesize the findings across the literature, the current review is a meta-analysis of studies comparing DRD between criterion groups exhibiting addictive behavior and control groups. The meta-analysis sought to characterize the overall patterns of findings, systematic variability by sample and study type, and possible small study (publication) bias. Literature reviews identified 310 candidate articles from which 46 studies reporting 64 comparisons were identified (total N=56,013). From the total comparisons identified, a small magnitude effect was evident (d= .15; p< .00001) with very high heterogeneity of effect size. Based on systematic observed differences, large studies assessing DRD with a small number of self-report items were removed and an analysis of 57 comparisons (n=3,329) using equivalent methods and exhibiting acceptable heterogeneity revealed a medium magnitude effect (d= .58; p< .00001). Further analyses revealed significantly larger effect sizes for studies using clinical samples (d= .61) compared with studies using nonclinical samples (d=.45). Indices of small study bias among the various comparisons suggested varying levels of influence by unpublished findings, ranging from minimal to moderate. These results provide strong evidence of greater DRD in individuals exhibiting addictive behavior in general and particularly in individuals who meet criteria for an addictive disorder. Implications for the assessment of DRD and research priorities are discussed.
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            Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment.

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              The Gambling Related Cognitions Scale (GRCS): development, confirmatory factor validation and psychometric properties.

              The aims of this study are to develop and validate a measure to screen for a range of gambling-related cognitions (GRC) in gamblers. A total of 968 volunteers were recruited from a community-based population. They were divided randomly into two groups. Principal axis factoring with varimax rotation was performed on group one and confirmatory factor analysis (CFA) was used on group two to confirm the best-fitted solution. The Gambling Related Cognition Scale (GRCS) was developed for this study and the South Oaks Gambling Screen (SOGS), the Motivation Towards Gambling Scale (MTGS) and the Depression Anxiety Stress Scale (DASS-21) were used for validation. Exploratory factor analysis performed using half the sample indicated five factors, which included interpretative control/bias (GRCS-IB), illusion of control (GRCS-IC), predictive control (GRCS-PC), gambling-related expectancies (GRCS-GE) and a perceived inability to stop gambling (GRCS-IS). These accounted for 70% of the total variance. Using the other half of the sample, CFA confirmed that the five-factor solution fitted the data most effectively. Cronbach's alpha coefficients for the factors ranged from 0.77 to 0.91, and 0.93 for the overall scale. This paper demonstrated that the 23-item GRCS has good psychometric properties and thus is a useful instrument for identifying GRC among non-clinical gamblers. It provides the first step towards devising/adapting similar tools for problem gamblers as well as developing more specialized instruments to assess particular domains of GRC.
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                Author and article information

                Contributors
                Journal
                J Behav Addict
                J Behav Addict
                JBA
                Journal of Behavioral Addictions
                Akadémiai Kiadó (Budapest )
                2062-5871
                2063-5303
                08 September 2020
                October 2021
                October 2021
                : 10
                : 3
                : 381-387
                Affiliations
                [1 ] Experimental Gambling Research Laboratory, School of Health, Medical and Applied Sciences, CQUniversity , 120 Spencer St, 3000, Melbourne, VIC, Australia
                [2 ] Applied Psychology, WMG, University of Warwick , Coventry, CV4 7AL, United Kingdom
                [3 ] Department of Psychology, University of Warwick , Coventry, CV4 7AL, United Kingdom
                [4 ] Technische Universität München , Arcisstraße 21, 80333, München, Germany
                Author notes
                [* ]Corresponding author. Email p.newall@ 123456cqu.edu.au
                Author information
                https://orcid.org/0000-0002-1660-9254
                Article
                10.1556/2006.2020.00054
                8997208
                32903204
                e0d6d5f1-6401-4793-9833-e828e4c54652
                © 2020 The Author(s)

                Open Access. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated.

                History
                : 06 May 2020
                : 20 July 2020
                : 13 August 2020
                : 18 August 2020
                Page count
                Figures: 2, Tables: 1, Equations: 0, References: 32, Pages: 15
                Categories
                Article

                modern gambling products,online gambling,sports betting,probability discounting,gambling,social media

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