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. 2021 Sep;37(3):877-897.
doi: 10.1007/s10899-020-09964-z.

Online Problem Gambling: A Comparison of Casino Players and Sports Bettors via Predictive Modeling Using Behavioral Tracking Data

Ivan Ukhov  1 , Johan Bjurgert  2 , Michael Auer  3 , Mark D Griffiths  4
Affiliations

Online Problem Gambling: A Comparison of Casino Players and Sports Bettors via Predictive Modeling Using Behavioral Tracking Data

Ivan Ukhov et al. J Gambl Stud. 2021 Sep.

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.

Keywords: Behavioral tracking; Online casino gambling; Online sports betting; Problem gambling; Remote gambling.

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Figures

Fig. 1
Fig. 1
Contribution magnitudes. The explanatory variables are sorted with respect to the casino-gambling group
Fig. 2
Fig. 2
Contribution distributions. The variables are sorted by the median Shapley value
Fig. 3
Fig. 3
Contribution of demographic and session-related explanatory variables, namely the country of registration (first), self-reported age (second), active days per day since registration (third), and proportion of sessions started on desktop computers (fourth)
Fig. 4
Fig. 4
Contribution of session-related variables, namely the duration of sessions per active day in minutes (first), number of sessions per active day (second), variability in the duration of sessions (third) in minute, and slope of the number of sessions (fourth)
Fig. 5
Fig. 5
Contribution of deposit-related explanatory variables, namely the volume of approved deposits per active day (first), number of approved deposits per active day (second), number of denied deposits per active day (third), and slope of the number of approved deposits (fourth). All financial quantities are in euros
Fig. 6
Fig. 6
Contribution of wager- and result-related explanatory variables, namely the volume of turnovers per active day (first), number of turnovers per active day (second), and volume of positive and negative results per active day (third and fourth). All financial quantities are in euros
See this image and copyright information in PMC

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