ArticleJournal of gambling studies2021
Online Problem Gambling: A Comparison of Casino Players and Sports Bettors via Predictive Modeling Using Behavioral Tracking Data.
Article in Journal of gambling studies, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Sports betting around the world: A systematic review.Journal of behavioral addictions · 2022Pooled it
- Integration of artificial intelligence-based solutions into electronic gaming machines for responsible gambling: a case study of South Africa.Frontiers in artificial intelligence · 2026Article
- Insights into the temporal dynamics of identifying problem gambling on an online casino: A machine learning study on routinely collected individual account data.Journal of behavioral addictions · 2025Article
- Overtime: Long-Term Betting Trajectories Among Highly-Involved and Less-Involved Online Sports Bettors.Journal of gambling studies · 2024Article
- Unmasking Risky Habits: Identifying and Predicting Problem Gamblers Through Machine Learning Techniques.Journal of gambling studies · 2024Article
- Self-reported Deposits Versus Actual Deposits in Online Gambling: An Empirical Study.Journal of gambling studies · 2024Article
- Behavioural Tracking and Profiling Studies Involving Objective Data Derived from Online Operators: A Review of the Evidence.Journal of gambling studies · 2024Review
- Development of the Online Problem Gaming Behavior Index: A New Scale Based on Actual Problem Gambling Behavior Rather Than the Consequences of it.Evaluation & the health professions · 2024Article
- An Empirical Attempt to Operationalize Chasing Losses in Gambling Utilizing Account-Based Player Tracking Data.Journal of gambling studies · 2023Article
- Using artificial intelligence algorithms to predict self-reported problem gambling with account-based player data in an online casino setting.Journal of gambling studies · 2023Article
- Gambling harm prevention and harm reduction in online environments: a call for action.Harm reduction journal · 2023Review
- The relationship between structural characteristics and gambling behaviour: An online gambling player tracking study.Journal of gambling studies · 2023Article
- Applying the DSM-5 Criteria for Gambling Disorder to Online Gambling Account-Based Tracking Data: An Empirical Study Utilizing Cluster Analysis.Journal of gambling studies · 2022Article
- Development and validation of a prediction model for online gambling problems based on players' account data.Journal of behavioral addictions · 2022Article
- Consumer Profile Segmentation in Online Lottery Gambling Utilizing Behavioral Tracking Data from the Portuguese National Lottery.Journal of gambling studies · 2022Article
- Real-Time Tracking Method for Sports Targets in Smart Cities under the Internet+ Background.Computational intelligence and neuroscience · 2022Article
- A casino in my pocket: Gratifications associated with obsessive and harmonious passion for mobile gambling.PloS one · 2021Article
- Transitioning Between Online Gambling Modalities and Decrease in Total Gambling Activity, but No Indication of Increase in Problematic Online Gambling Intensity During the First Phase of the COVID-19 Outbreak in Sweden: A Time Series Forecast Study.Frontiers in public health · 2020Article
Corrections and comments
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Authors and funding
4 authors.
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Abstract
In this study, the differences in behavior between two groups of online gamblers were investigated. The first group comprised individuals who played casino games, and the second group comprised those who bet on sports events. The focal point of the study was on problem gambling, and the objective was to identify and quantify both common and distinct traits that are characteristic to casino and sports problem gamblers. To this end, a set of gamblers from the gaming operator LeoVegas was studied. Each gambler was ascribed two binary variables: one separating casino players from sports bettors, and one indicating whether there was an exclusion related to problem gambling. For each of the four combinations of the two variables, 2500 gamblers were randomly selected for a thorough comparison, resulting in a total of 10,000 participants. The comparison was performed by constructing two predictive models, estimating risk scores using these models, and scrutinizing the risk scores by means of a technique originating from collaborative game theory. The number of cash wagers per active day contributed the most to problem-gambling-related exclusion in the case of sports betting, whereas the volume of money spent contributed the most to this exclusion in the case of casino players. The contribution of the volume of losses per active day was noticeable in the case of both casino players and sports bettors. For casino players, gambling via desktop computers contributed positively to problem-gambling-related exclusion. For sports bettors, it was more concerning when the individual used mobile devices. The number of approved deposits per active day contributed to problem-gambling-related exclusion to a larger extent for sports bettors than casino players. The main conclusion is that the studied explanatory variables contribute differently to problem-gambling-related exclusion among casino players and sports bettors.
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