Article Content
In problem gambling research, the structural characteristics of the games, including their design features, were found as influencing players’ behavior and risk factors for the potential gambling harms. Sports betting, as a special form of gambling, evolved rapidly with respect to technology and the range of betting options, and came to have attractive features, like live betting.
Research in problem gambling had to focus on the new features of the games, particularly in sports betting. During the last decade, it has been established that design features of betting platforms that facilitate continuous engagement contribute to gambling harm.
A recent study that investigated the use of live sports-betting features in relation with bettors’ profiles found that these feature also fall within this category.
Sports-betting modern features and gambling harm
The technology of sports betting has evolved much faster than that of the classical casino games and even slots. Based on this technology, betting platforms diversified their range of betting options, especially in a category that makes betting more interactive. Problem gambling researchers had to keep up with this evolution and investigated how the new features affect gambling behavior and relate to gambling harms.
Bettors that experience harm from sports and race betting often report more frequent use of live or in-play betting, micro betting, and instant cash-out. Many theories of gambling harm proposed that these structural and design characteristics can cause gambling harm because they enable high-risk betting behaviors. In particular, the interactive features of sports betting enable cyclical patterns of repeated betting engagement, called the ‘Online Sports Betting Loop’.
For example, most betting applications allow for a frictionless recycling of winnings into subsequent bets, while encouraging further liquidity of funds by immediate deposits, cash out, and withdrawal reversals. Micro and in-play bets support continuous engagement by offering a constant supply of new betting opportunities with short intervals between a bet and its outcome, as well as marketing notifications prompting bettors to reinitiate a session from a mobile device.
Theoretical setup inadequacies, correction, and the case of live sports-betting features
Yet not all the empirical associations between sports-betting features use and gambling harm are relevant and adequately established, and the main argument supporting this claim pertains to the relationships between variables, especially confounding among variables. A confounding variable is an outside influence that correlates with both the supposed cause (independent variable) and the effect (dependent variable) in a study.
For example, young people – in particular young men – tend to experience higher rates of sports betting harm, as several studies confirmed. However, this cohort is also more likely to adopt new digital technologies, including online betting.
To control for potential confounding by age and gender, a recent study carried by psychologists Hugh Farrell, Daniel Bennett, and Dan Myles used a case-control design to test if the association between the use of these structural characteristics and gambling harm remained when comparing two groups of regular bettors, comparable in terms of age and gender, but different in their levels of gambling harm.
They also aimed at testing a novel prediction of the Online Sports Betting Loop theory in regard to the video streaming of live sporting events. Many betting applications offer today this feature, which was supposed to sustain attention on the application, especially because footage may be displayed along side promotions, live odds, or other prompts to place a bet. The authors of the study predicted more frequent use of in-application streaming of live events among those who report riskier betting.
Methods and statistical analysis
The authors of the study used a case-control design to compare bettors who reported more severe gambling problems (5+ on the Problem Gambling Severity Index PGSI) with a demographically matched control group of non-problematic bettors (PGSI 0-4). All participants bet on sports or races at least monthly. After the recruitment of the participants, 169 remained for the analysis: 84 in the lower-risk group and 85 in the higher-risk group.
In regard to sample characteristics: Groups were matched on age and gender by design, and incidentally matched on employment, education, and self-reported masculinity and femininity. In both groups, sports or race betting was the most frequent gambling activity for most participants, while both groups expressed a comparable preference for online wagering. Groups differed in gambling intensity and impact: the higher-risk group reported gambling more frequently, more active betting accounts, and placing impulsive bets more often.
Between-group differences were analyzed using non-parametric statistics.
Results of the study
In regard to product features: The higher-risk group reported more frequent use of both in-play betting and instant cash-out. In regard to multi bets, proposition bets, and social betting features there were no significant differences between groups. The higher-risk group was significantly more likely to watch live-streamed matches within a betting application, but both groups reported comparable rates of watching the events they bet on more generally.
In regard to betting circumstances: Participants in the higher-risk group reported that betting prevented them from getting enough sleep at a higher extent than the lower-risk group. Both groups reported comparable frequencies of betting under the influence of alcohol, and betting socially with friends or family.
In regard to marketing offers: 87.6% of the participants reported receiving a matched-deposit offer in the past year, at comparable rates across groups. Those in the higher-risk group reported being more likely to make an immediate deposit to qualify for these offers, relative to the other group.
87.6% of the participants reported using bonus funds to place a bet in the past year, again with comparable rates across groups.
Overall, 57.4% of the participants reported being more likely to place longshot bets when using bonus funds.
Final remarks
Overall, the findings were consistent with the Online Sports Betting Loop theory, as the higher-risk group reported more frequent use of in-play betting and instant cash out, as well as circumstances associated with gambling harms.
A noteworthy finding was that using a betting application to stream live events was more common among those at higher risk, which supports the hypothesis that this feature could encourage a pattern of cyclical and continuous betting.
The study accounted for potential confounding by age and gender; however alternative confounding patterns could explain the results.
The results confirmed the novel prediction that in-application streaming of live events may contribute to gambling harm, submitting to previous studies that found positive associations between risky or harmful betting and the use of live betting products and marketing offers.
References:
Farrell, H., Bennett, D., & Myles, D. (2026). More frequent use of live sports-betting features is associated with increased risk of gambling harm: Evidence from a case-control design. Journal of Behavioral Addictions, 2006-2025.
Gainsbury, S. M., Abarbanel, B., & Blaszczynski, A. (2020). The relationship between in-play betting and gambling problems in an Australian context of prohibited online in-play betting. Frontiers in Psychiatry, Vol. 11.
Hing, N., Browne, M., Russell, A. M. T., Greer, N., Thomas, A., Jenkinson, R., & Rockloff, M. (2019). Where’s the bonus bets? Assessing sports bettors’ comprehension of their true cost. Journal of Gambling Studies, 35(2), 587–599.
Parke, A., & Parke, J. (2019). Transformation of sports betting into a rapid and continuous gambling activity: A grounded theoretical investigation of problem sports betting in online settings. International Journal of Mental Health and Addiction, 17(6), 1340–1359.
