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Published in: Journal of Gambling Studies 2/2013

01-06-2013 | Original Paper

Gamblers’ Habits: Empirical Evidence on the Behavior of Regulars, Newcomers and Dropouts

Author: Ingo Fiedler

Published in: Journal of Gambling Studies | Issue 2/2013

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Abstract

Electronic gambling offers the opportunity to analyze huge and unbiased data sets of automatically recorded actual gambling behavior. This study refers to data on 2,127,887 poker playing identities from the Online Poker Database of the University of Hamburg (OPD-UHH) to analyze three subgroups of gamblers: regulars, newcomers, and dropouts. Their gambling habits over 6 months are analyzed in total, as well as over time. Regulars show a much higher involvement than non-regulars and increase their playing volume slightly over the observation period. Newcomers have a lower involvement than non-newcomers and most of them decrease their playing volume over time. Still, there is a small group of newcomers which increases their playing volume sharply and is, hence, very interesting for the industry as well as for the early prevention of pathological gambling. Dropouts have a higher gambling involvement than newcomers but play less than players who have not stopped stop gambling. Most dropouts also show a decreasing playing volume before dropping out. An analysis of the correlations between different variables of gambling habits shows that most of them reinforce each other, for example: gamblers with a higher total playing time tend to play at more tables simultaneously. Only playing frequency is a moderating variable of gambling involvement.
Appendix
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Footnotes
1
This is important to note as other operators like for example bwin are mainly sports betting operators and people playing poker there might do so only as their second or third game. People playing at Pokerstars are representative for the group of online poker players, though.
 
2
The period of data collection was extended due to technical problems such as downs of the server, software updates and disconnections.
 
3
Since poker is a zero sum game among the players where the operator keeps a part of the wagered bets, players are expected to lose more the longer they play. Thus, the longer they play the more losses there are to chase..
 
4
Sessions: K–S = .322, session length: K–S = .117; total playing time: K–S = .350; number of tables: K–S = .382; playing intensity: K–S = .296; playing volume: K–S = .467; betting days: K–S = .186; sessions/day: K–S = .177; playing time/day: K–S = .236; rake/day: K–S = .432.
 
5
The average total playing time is less than the product of the sessions and the average session length. This indicates that people with more sessions tend to play longer; note that numerator for the average total playing time is the total number of players while it is the total number of sessions for the average session lengths.
 
6
Note that the percentile players of the relative playing volume are not identical to those of the average playing volume.
 
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Metadata
Title
Gamblers’ Habits: Empirical Evidence on the Behavior of Regulars, Newcomers and Dropouts
Author
Ingo Fiedler
Publication date
01-06-2013
Publisher
Springer US
Published in
Journal of Gambling Studies / Issue 2/2013
Electronic ISSN: 1573-3602
DOI
https://doi.org/10.1007/s10899-012-9306-0

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