Abstract
AbstractStructural characteristics of games have been regarded as important aspects in the possible development of problematic gambling. The most important factors along with individual susceptibility and risk factors of the individual gambler are the structural characteristics such as the speed and frequency of the game (and more specifically event frequency, bet frequency, event duration, and payout interval). To date, the association between structural characteristics and behavior has not been studied in an online gambling environment. The present study investigated the association between structural characteristics and online gambling behavior in an ecologically valid setting using data from actual gamblers. The authors were given access to data from a large European online gambling operator with players from Germany, Austria, UK, Poland, and Slovenia. The sample comprised 763,490 sessions between November 27, 2020 and April 15, 2021 utilizing data from 43,731 players. A machine learning tree-based algorithm with structural characteristics and session metrics explained 26% of the variance of the number of games played in a session. The results also showed that only 7.7% of the variance in the number of bets placed in a session was explained by the game’s structural characteristics alone. The most important structural characteristic with respect to the number of games played in a session was the event frequency of the game followed by the maximum amount won on a single bet in a session.
Publisher
Springer Science and Business Media LLC
Subject
General Psychology,Sociology and Political Science
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