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Out of sports: The influence of structural and situational characteristics in online sports betting

In a paper that I recently co-wrote in the Journal of Sport and Social Issues with Hibai Lopez-Gonzalez and Ana Estevez, we argued that the growing conversion of sports betting into an online activity has prompted two types of transformations in the way companies market their betting products. Firstly, the Internet has not only extended the opportunities to bet but has also changed the characteristics of the betting practice itself. Such product characteristics can be divided into two categories, namely situational and structural characteristics, that appear to be associated with factors influencing the onset and maintaining of betting as well as the difficulty of discontinuing it (the focus of this blog). Secondly, the online dimension has also enabled the proliferation of cross-marketing strategies leading to a convergence between previously independent markets or the tightening of the relationship between those with already established synergies (which I will examine in a future blog).

The internet has substantially transformed the situational and structural characteristics of sports betting. Situational factors comprise all environmental features that might make gamblers feel comfortable (both psychologically and physically) while gambling including sensory factors like colour, music, and smell in the environment, novelty of the activity, accessibility or proximity to a gambling venue, social facilitation and intrinsic association, which is defined as ‘the degree to which gambling is associated with other interests and attractions’.

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New situational factors in online sports betting include: (i) easier and faster accessibility to betting opportunities; (ii) ubiquity of bettable competitions around the globe and seamless availability of those competitions around the clock; (iii) anonymity (in terms of social stigma traditionally attached to gambling) and comfortable betting from home or elsewhere via mobile devices; (iv) greater social facilitation via online communities of bettors or betting leagues organized between groups of friends; and (v) an enhanced intrinsic association of sports betting with sporting values such as health, competition, team identification and loyalty, further facilitated by the proliferation of live sport content on television and social media.

Structural factors refer to the specific characteristics or design of the gambling activity such as win probability, sound and lighting effects of the game, bet frequency (how many bets a person can place in a given period of time), loss chasing facilitation (gambling to recover lost money), jackpot size, price structure, near-miss opportunities (the psychological bias of interpreting losses as nearly wins or anticipatory of a winning streak).

New structural factors in online betting include: (i) a greater frequency of bets, with shorter intervals between bets, and shorter event durations (e.g., virtual sports), meaning faster reward mechanisms; (ii) in-play betting, which encompasses a closer connection between watching sport and betting; (iii) contextual betting, with live markets that open after specific actions (e.g. betting on the outcome of a penalty kick seconds after being awarded by the referee); (iv) greater illusion of control over the bets with new functionalities that emphasize the skills involved and diminish the role of luck, such as cash out (the person can withdraw the bet before the end of the event at the price stipulated by the betting site), accumulators (a person can aggregate multiple events in a single bet, increasing the potential return), exchange (betting against other people instead of the bookmaker); and (v) a greater integration in the betting process of the knowledge about the sport (e.g., daily fantasy sports), resulting in the gamification of the betting experience.

In a 2013 scoping study that I published with Dr. Abby McCormack in the International Journal of Cyber Behavior, Psychology and Learning, we noted that new situational and structural factors associated with Internet gambling could influence the onset of problem gambling in non-sporting gambling contexts. The relative novelty of these situational and structural characteristics affecting the wagering on sports is reflected in the scarcity of research devoted to understanding them. However, there are a few studies.

An analysis of 47,603 Bwin betting website subscribers (by Dr. Debi LaPLante and colleagues in the journal Computers in Human Behaviors) showed some interesting results in the direction of the importance of structural factors determining excessive gambling. The most involved bettors (those comprising the most active 1% of the user sample) who gambled on final outcomes did not escalate their gambling behaviour over time whereas those who gambled in-play did so. In a 2014 follow-up study in the journal Psychology of Addictive Behaviors, LaPlante and her colleagues examined the effect of in-play betting in the development of problem gambling. The researchers expanded the sample to other forms of gambling and compared the role of breadth (i.e., many different gambling forms) and depth involvement (i.e., more frequent betting) in problem gambling onset. They hypothesised that more involved users would be more likely to become problem gamblers (which was shown to be the case). For every form and gambling, when controlling for depth and breadth involvement, the model was not able to predict gambling-related problems, with one exception: in-play betting. The study suggested that a structural characteristic of a game, the live betting action, could be a precipitant, in conjunction with other determinants, of gambling disorders.

Another study by Dr. Richard LaBrie and Dr. Howard Shaffer (in a 2011 issue of Addiction Research and Theory) found that self-limiting features – in which the bettor determines a maximum amount of money to be bet – made problem gamblers bet less frequently but, in turn, increased the stakes of the bets placed. Bettors who scored high on problem gambling scales chased their losses by implementing a risk aversion strategy, placing high bets conservatively on short odds events (i.e., events with unbalanced contenders in which the outcome can more likely be determined beforehand but with a lower monetary return).

While there has been an increasing amount of research that has examined the influence of situational and structural characteristics in gambling (particularly in relation to slot machine gambling), the impact of such characteristics on online sports betting (at present) remains largely unknown.

(Please not that this article was co-written with Dr. Hibai Lopez-Gonzalez and Dr. Ana Estevez).

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (1993). Fruit machine gambling: The importance of structural characteristics. Journal of Gambling Studies, 9, 101-120.

Griffiths, M.D. (1999). Gambling technologies: Prospects for problem gambling. Journal of Gambling Studies, 15(3), 265–283.

Griffiths, M.D. (2005). A biopsychosocial approach to addiction. Psyke & Logos, 26(1), 9–26.

Griffiths, M.D. & Auer, M. (2013) The irrelevancy of game-type in the acquisition, development and maintenance of problem gambling. Frontiers in Psychology, 3, (621). doi: 10.3389/fpsyg.2012.00621.

LaBrie, R. & Shaffer, H.J. (2011). Identifying behavioral markers of disordered Internet sports gambling. Addiction Research & Theory, 19(1), 56–65.

LaPlante, D., Nelson, S.E. & Gray, H.M. (2014). Breadth and depth involvement: Understanding Internet gambling involvement and its relationship to gambling problems. Psychology of Addictive Behaviors, 28(2), 396-403.

LaPlante, D.A., Schumann, A., LaBrie, R.A., et al. (2008). Population trends in Internet sports gambling. Computers in Human Behavior, 24(5), 2399–2414.

Leino, T., Torsheim, T., Blaszczynski, A., Griffiths, M.D., Mentzoni, R., Pallesen, S. & Molde, H. (2015). The relationship between structural characteristics and gambling behavior: A population based study. Journal of Gambling Studies, 31, 1297-1315.

Lopez-Gonzalez, H., Estevez, A. & Griffiths, M.D. (2017). Marketing and advertising online sports betting: A problem gambling perspective. Journal of Sport and Social Issues, in press.

Lopez-Gonzalez, H. & Griffiths, M.D. (2016). Is European online gambling regulation adequately addressing in-play betting advertising? Gaming Law Review and Economics, 20, 495-503.

Lopez-Gonzalez, H. & Griffiths, M.D. (2017). Understanding the convergence of online sports betting markets. International Review for the Sociology of Sport, in press.

Lopez-Gonzalez, H. & Griffiths, M.D. (2017). ‘Cashing out’ in sports betting: Implications for problem gambling and regulation. Gaming Law Review and Economics, in press.

McCormack, A. & Griffiths, M.D. (2013). A scoping study of the structural and situational characteristics of internet gambling., 3(1), 29–49.

Parke, J. & Griffiths, M.D. (2006). The psychology of the fruit machine: The role of structural characteristics (revisited). International Journal of Mental Health and Addiction, 4, 151-179.

Parke, J. & Griffiths, M.D. (2007). The role of structural characteristics in gambling.  In G. Smith, D. Hodgins & R. Williams (Eds.), Research and Measurement Issues in Gambling Studies (pp.211-243). New York: Elsevier.

The dangers of strangers: What role does social facilitation play in gambling?

Back in 1987 I began my PhD on the psychology of excessive slot machine use and one of the methods I used extensively over a three-year period was participant and non-participant observation in British amusement arcades up and down the country. One of the things I often noticed (and made passing reference to in some of my early 1990s papers) was how gamblers’ behaviour would often change once they realised they were being watched. It wasn’t until 2003 that I (along with Dr Jonathan Parke, now at Salford University) wrote about social facilitation more formally in a book chapter on the environmental psychology of gambling.

Our research (up to the writing of that book chapter) had indicated that social facilitation and bystanders’ effects on gamblers’ behaviour was complex. We also speculated that gamblers’ behaviour might be different depending on whether the person watching was a friend (and whether the friend was a gambler or not) or a stranger. Based on our initial observations, we noted that the presence of gambling friends when gambling appeared to have three main effects:

  • Increased risk-taking: This occurred because there was a need to impress fellow gamblers through “risky but exciting” play (i.e., increased risk-taking). Friends who gamble are used to risk-taking and in addition to the ability to win, players respected a certain “fearless” element in another person’s play. Furthermore, they encouraged riskier play since they enjoyed a secondary high from the gambling themselves and therefore, there was a selfish element to their encouragement.
  • Improved skill level: This occurred because gamblers wanted to demonstrate the highest skill levels to fellow gamblers. As a result, the gambler was usually very alert and aware and maximized any opportunity to win, not only for a profit motive but to ensure a positive evaluation from the fellow gamblers.
  • Increased play duration: This occurred because a group of friends gambling on slot machines would watch each other and enjoy the “secondary high” thereby staying longer in that environment. However, this dynamic was more complicated than it first appeared. For example, take the case of three friends who gamble. Friend A begins playing the first slot machine while his two friends observe and encourage. After a short while, Friend B gets bored as the secondary high is no longer enough, so he begins to play another machine. Meanwhile, Friend A is ready to leave the arcade but Friend B does not want to leave yet as he not finished playing on his slot machine as he continues to chase his losses. The effect is a vicious circle where each of the three friends remain in the arcade until all of them are ready and willing to leave. The implications of this dynamic for prolonged gambling are clear – the longer they observe each other in the gambling environment, the more environmental cues they will experience which have the likely effect of eventually inducing fruit machine gambling.

In the case of friends who didn’t gamble, our research indicated that their presence was primarily inhibitory.  Reasons included:

  • Non-gambling friends giving negative appraisals for unnecessary risk taking: This is because friends who do not gamble, did not understand the motivations for gambling, particularly when the individual was losing. As a result, it was common for non-gambling friends to make negative judgements regarding the gambler’s character (e.g., they were unwise, impulsive, and weak). For this reason, many gamblers would take less risks, played lower stake machines, and stayed in the gambling environment for shorter periods of time.
  • Non-gambling friends wanting to do something else: Impatient non-gambling friends who found gambling “boring” would encourage the gambler to leave the environment to pursue other more “sensible” or “fun” activities with them.

One of the most interesting observations of our research relates to the effect younger more susceptible onlookers had on gamblers. Essentially, gamblers admitted to showing off by (i) increased concentration on skilful tasks, (ii) taking higher risks, and (iii) general reckless play. Gamblers who were watched by “inexperienced” onlookers gained both self-esteem and social approval. These can be reinforcing motivations for continued gambling.

Although we identified social facilitation as a potentially important factor in the maintenance of gambling behaviour, it has been the focus of very few empirical studies. However, Dr Matthew Rockloff (Central Queensland University, Australia) carried out an experimental study suggesting that players’ may increasingly engage in risky gambling as a way of impressing other players. In their experiment, participants (n=116) gambled on a slot machine simulation featuring a pre-programmed winning sequence that was then followed by an indefinite losing one. During the experiment, various data were collected from each player including the gambling speed, their average size of bet, the number of games played, and the final loss amount. During the experimental trials, some players were given computer-generated false feedback suggesting that other players nearby were playing the same game and winning. The study’s findings indicated that players bet more and lost more money when receiving information about other players’ winning compared to those players in similar experimental trials but receiving much less information. Therefore, study appeared to suggest that even just the (implied) presence of other slot machine players increased gambling intensity (i.e., they played and gambled more than those players gambling alone).

Karen Hardoon and Dr Jeff Derevensky(McGill University, Canada) conducted a study on children gambling in groups. They found that girls had increased mean wagers when they gambled in groups. No increases in mean wagers were found among the boys. Their results also indicated that children were more susceptible to peer influences than adults. Other factors, such as the medium of playing, may affect social facilitation. For instance, Jonathan Parke and I speculated (comparing case study data from internet and non-Internet gamblers) that the one positive aspect of Internet gambling is that it may reduce the social facilitation risk.

More recently, I (along with my colleagues Tom Cole and Dr Doug Barrett) carried out an experimental study at Nottingham Trent University. Using the game of roulette, we experimentally examined (amongst other things) the role social facilitation in gambling behaviour between online and offline gamblers. A total of 38 participants played online and offline roulette either alone or alongside another gambling participant, and the players’ chip placement and amount bet was recorded. We found that those who gambled in online roulette placed more chips per bet and made riskier bets than those who gambled on roulette offline. We also found that those who gambled alongside another gambler placed more chips and made riskier bets than those who gambled alone. Those who gambled online and in the presence of others, placed the highest number of chips per bet and made the riskiest bets.

Overall, these findings on social facilitation are consistent with the limited previous research in the area. The results suggest that gambling online may be facilitating participants to place higher stakes per roulette spin and that gambling alongside others led players to stake more than when playing alone. There are a number of reasons that could perhaps help explain why online players staked higher bets and made riskier bets. For instance, it was clear that in the experiment, participants were able to gamble at much quicker rates in the online condition than the offline condition (i.e., the event frequency was a lot higher). This was because withdrawing and handing out chips won and lost was instantaneous online (whereas offline the process was much slower). Such an observation supports the wealth of literature that tends to show that certain types of gambling with high event frequencies tend to be more problematic to individuals.

Another noticeable difference between the online and offline gambling in the experiment was in relation to the differing sound effects during play. By winning chips, the online casino used in this experiment played a ‘jovial’ or congratulatory noise. This could be argued as an effective way in which online casinos can facilitate gamblers’ playing behaviour by encouraging future play by rewarding past behaviour. Another potential explanation for gambling with higher stakes and making riskier bets could be the psychological value that the chips hold. The online condition obviously did not involve the participants holding the chips, whereas the offline condition required the participants to place chips themselves. Although there is little research into the difference in psychological value of online chips and offline chips, it could perhaps be argued that the value of placing chips in an offline table game is higher than placing virtual chips in an online game. There is little empirical research suggesting this to be the case, but the participants in this experiment often said they felt it was easier to gamble with online chips compared to chips offline. Further research on how players value chips online versus offline may prove useful.

With past research suggesting that both social facilitation and medium (i.e., online or offline) may increase players’ risk-taking behaviour, a priori it would suggest there should be a significant interaction between the two. Results of our study tended to support this hypothesis.

Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Cole, T., Barrett, D.K.R., Griffiths, M.D. (2011). Social facilitation in online and offline gambling: A pilot study. International Journal of Mental Health and Addiction, 9, 240-247.

Griffiths, M.D. (1991). The observational study of adolescent gambling in UK amusement arcades. Journal of Community and Applied Social Psychology, 1, 309-320.

Griffiths, M.D. (2011).  A typology of UK slot machine gamblers: A longitudinal observational and interview study. International Journal of Mental Health and Addiction, 9, 606-626.

Griffiths, M.D. & Parke, J. (2003). The environmental psychology of gambling. In G. Reith (Ed.), Gambling: Who wins? Who Loses? pp. 277-292. New York: Prometheus Books.

Griffiths, M.D. & Parke, J. (2007). Betting on the couch: A thematic analysis of Internet gambling using case studies. Social Psychological Review, 9(2), 29-36.

Hardoon, K.K. & Derevensky, J.L. (2001). Social influences involved in children’s gambling behavior. Journal of Gambling Studies, 17, 191-196.

Parke, J. & Griffiths. M.D. (2008). Participant and non-participant observation in gambling environments. ENQUIRE, 1, 1-18.

Rockloff, M.J. & Dyer, V. (2007). An experiment on the social facilitation of gambling behavior. Journal of Gambling Studies, 23, 1-12.