Population trends in Internet sports gambling

doi:10.1016/j.chb.2008.02.015

Computers in Human Behavior

Volume 24, Issue 5, September 2008, Pages 2399-2414

https://doi.org/10.1016/j.chb.2008.02.015 Get rights and content

Abstract

The Internet is a controversial new medium for gambling. This study presents the first longitudinal analysis of online gambling participation and activity among a population of newly subscribed Internet bettors. Our analyses indicate that this population of gamblers adapted to the new subscription service rapidly, as evidenced by quickly developing declines in population participation, number of bets, and size of stakes. Adaptation was not uniformly evident in our population. Among subgroups of heavily involved bettors, adaptation was generally slower or not apparent. Rather than adapt, involved bettors often maintained the high level of betting they escalated to in the days following subscription. This was particularly evident for one type of game: live-action betting. These involved individuals and the effect of live-action play require close scrutiny and ongoing examination.

Section snippets

Population trends in Internet sports gambling

Ten years ago, the division on addictions published the first meta-analytically derived estimates of lifetime and past year pathological gambling for the United States and Canada (Shaffer and Hall, 2001, Shaffer et al., 1997, Shaffer et al., 1999). Those point-in-time estimates indicated that 1–2% of the adult population met criteria for lifetime pathological gambling. Subsequent updates incorporating international research (Stucki & Rihs-Middel, 2007) indicate little change in these rates.

Sample

This research cohort included all persons (N = 47,603) who registered with the Internet betting service provider, bwin Interactive Entertainment AG (bwin), during February 2005. In this cohort, some players received promotional funds, but everyone in the sample deposited and played with their own monies. We monitored bettors for the next 18 calendar months, until August 31, 2006. We excluded persons who did not start to gamble until one month before the end of the study period (i.e., started

Betting activity: full sample

We examined the monthly and daily patterns for the total monies wagered (i.e., Stake), total number of bets (i.e., Bets), and total number of active persons (i.e., N Valid) using the full sample. The various measures of betting activity within game (i.e., FO and LA) all correlated at greater than .91 (Table 1), indicating that patterns of activity on all three measures were very similar. Fixed-odds and live-action betting in the full sample also correlated with each other for the various

Discussion

This study presents the first longitudinal analysis of real time Internet sports gambling behavior for a large sample of newly subscribed gamblers. Patterns of gambling behavior in our population were consistent for activity (i.e., number of bets and size of stakes) and for games (i.e., FO and LA). There were, however, notable magnitude differences over time for games: the number of bets people made for FO always exceeded those for LA, and by the third month of the study period, the amount of

Acknowledgement

The company bwin Interactive Entertainment AG provided primary support for this study. The Division on Addictions also receives support from the National Center for Responsible Gaming, National Institute on Alcohol and Alcohol Abuse, National Institute of Mental Health, National Institute on Drug Abuse, the Massachusetts Council on Compulsive Gambling, the Nevada Department of Public Health, the Massachusetts Family Institute, and others. The authors extend special thanks to Christine Reilly,

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This subdivision resulted in 20,891 users in the “normally-involved in-play bettor” (NIB) group, and 3,890 users in the “most-involved in-play bettor” (MIB) group. This approach is comparable to previous analyses of “most-involved bettors” defined as the top 1% of bets made within the study period (Broda et al., 2008; LaPlante et al., 2008; LaBrie et al., 2007). Here, our subdivision allows for a larger number of bettors in the most-involved group, which enables us to examine this group in more detail.
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Finally, because many of our analyses are parallel with a similar study of online sports bettors (LaPlante et al., 2008), the current study shares many of the same limitations as that study, including the possibility that users might be active on other DFS or gambling websites, and the idea that different operationalizations and examined associations might reveal different trends. While our study period was longer than that of LaPlante et al. (2008) (i.e., 27 months vs. 18 months) we found that adaptation occurred more slowly over the long term among less involved players. For some groups of most involved players, adaptation might develop as well, but over an even more extended period of time.
Research suggests that populations of gamblers can adapt rapidly to online sports betting services after subscribing. This pattern of adaptation typically shows an initial play increase followed by a sharp overall betting (e.g., amount wagered and number of bets) decline. Such trends are consistent with models of exposure and adaptation. Although exposure and adaptation effects are observable in a variety of situations, currently we know very little about whether these trends are evident for daily fantasy sports. Understanding this is important because many have compared daily fantasy sports with traditional gambling. To examine this issue, we conducted a longitudinal analysis of daily fantasy sports play on the DraftKings website. We followed 11,338 unique DraftKings players, tracking their overall levels of engagement (i.e., total contest entries, total contest entry fees, and total participation) for 27 months. In this paper, we present daily and monthly trends for these activities. We observed increasing engagement over time among a minority of the most involved players (MIP; i.e., the top 1% of players on each engagement metric). Less involved players (LIP), who comprised the majority of the player pool (i.e., the remaining 99% of players on each metric), tended to exhibit elevated initial engagement followed by decreasing engagement over time. Aggregate playing trends for all groups of players were seasonal, with more engagement during National Football League seasons and less engagement during off-seasons. The results of this study suggest that models of exposure and adaptation, in addition to characterizing the population trends of online gambling activities such as online sports betting, likewise can help to explain population trends of most daily fantasy sports players.
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Population trends in Internet sports gambling

Abstract

Section snippets

Population trends in Internet sports gambling

Sample

Betting activity: full sample

Discussion

Acknowledgement

Feeling luck? Electronics is bringing gambling into homes, restaurants and planes

Wall Street Journal.

Relationships between poverty and psychopathology: A natural experiment

JAMA: Journal of the American Medical Association

First year impacts of casino gambling in a community

Journal of Gambling Studies

Internet gambling: Issues, concerns, and recommendations

CyberPsychology and Behavior

Internet gambling: An overview of psychosocial impacts

UNLV Gaming Research and Review Journal

Gambling technologies: Prospects for problem gambling

Journal of Gambling Studies

Prevalence of excessive gambling before and after introduction of a national lottery in the United Kingdom: Another example of the single distribution theory

Addiction

A prospective study of the impact of opening a casino on gambling behaviours: 2- and 4-year follow-ups

Canadian Journal of Psychiatry

Impact of availability on gambling: A longitudinal study

Canadian Journal of Psychiatry

Assessing the playing field: A prospective longitudinal study of internet sports gambling behavior

Journal of Gambling Studies