Patterns of Play

Final research findings from the Patterns of Play research project into improving understanding of the online gambling market and how the characteristics of gamblers and patterns of play relate to harmful gambling.

The research was commissioned by GambleAware and is a mixed methods programme comprising: 1) a scoping qualitative study, 2) collection and analysis of industry data and 3) a survey of gamblers.

The key questions of this project are as follows:

• What are the basic patterns of play within online gambling?
• How do these patterns of play vary for different types of people?
• How do patterns of play vary among different products and characteristics?
• What types of behaviours are associated with problem or ‘at-risk’ gambling (for example late night gambling as measured by stake sizes and intensity of spending)?

Findings

Stage 1: Qualitative Scoping Stage

• Participants varied in their chosen gambling activities, motivations for gambling, and amount of time and money spent gambling.
• Most participants had one gambling activity they favoured and spent most of their money on.

Stage 2: Account Data Stage

• Online bettors with the largest losses over the year were disproportionately likely to be male and their average age was around 40. A significant number had addresses in deprived areas.
• Slots games accounted for the majority of spending (60.1%) on gaming activities, reflecting its dominance in the whole online gambling sector.
• 1.2% of holders of accounts used for gaming (close to 50,000 individuals) spent the equivalent of eight full days playing over the study year.
• Similar to online betting, less than a quarter of casino and poker customers were women. However, in slots, the proportion of females was somewhat higher, about one-third, and women made up the majority (62%) of those who took part in online bingo.
• As with betting, the online gaming sector had heavy dependence on a “vital few” customers. The ‘top-20%’ of customers by volume generated just over 90% of revenue.
• Whilst online betting is more popular than online gaming among the British population, spending levels per customer tend to be much higher in gaming.
• In gaming, both participation and revenue were strongly skewed towards the most deprived areas. Across gaming, the 20% most deprived areas provided 29.2% of players and 25.2% of operator GGY, whereas the 20% least deprived areas provided 12.9% of players and 15.0% of operator Gross Gambling Yield (GGY).
• Dual customers (those who participated in both betting and gaming) were particularly profitable for operators. We estimate that per-account GGY during the one-year data period was £601.93 for dual customers (compared with £296.20 for gaming-only and £134.98 for betting-only).
• The ‘top-10%’ of gamblers defined by volume delivered 79.0% of operator revenue. The qualification for entering the top 10% (£4,568 staked) roughly corresponds to an expected one-year loss where (from international evidence) risk of problem gambling begins to increase.
• Deposit limits were used by far more account-holders than other self-management tools. 21.5% set a limit during the year studied.
• During the one-year period studied, 3.9% of account-holders received a social responsibility contact, usually in the form of an e-mail. Just 0.13% were contacted by telephone. Telephone interventions were typically followed by substantial moderation of gambling activity. While encouraging, further research is required before this can be established as a causal effect. 

Stage 3: Follow-on Survey Stage

• Survey respondents who gambled on gaming products only with their sampled account in 2018/19 were more likely than those who gambled on betting products only, to report that they gambled with more than one gambling company in 2018/19.
• Survey respondents who said they were finding it difficult to manage financially or just about getting by financially in 2018/19 were more likely to have a total spend with their sample operator account of more than £700 (25% and 21% respectively) compared to those who said they were living comfortably (12%).
• Those who spent more money across the account data period in 2018/19 with their sampled accounts or who gambled on gaming products only or on both betting and gaming products in 2018/19 were more likely to be identified as problem gamblers (for their gambling between September 2020 and September 2021).

Methodology

Stage one was a small exploratory study that examined patterns of play with participants who gamble online. This informed and shaped the research questions for the analyses in subsequent stages of the project.

Stage two consisted of account data from nearly 140,000 accounts from seven different gambling operators (20,000 each) over a 12-month period from 1^st July 2018 to 30^th June 2019. The account data were collected and examined at a high level of granularity in order to track behaviour within gambling sessions and over periods of time. Using the data, this report explores overall patterns in online gambling, in addition to individual explorations of the betting and gaming sub-sectors of the online industry. Finally, this report examines the use and impact of safer gambling tools. This report builds on the findings initially published in the Patterns of Play: Interim Report in March 2020. 

The Patterns of Play follow-on web survey formed the final phase of the research project. The aim of this web survey was to collect information (from a sub sample of the players from stage two) that was not available from their account data, to increase our understanding of online patterns of play.

NatCen led on the data collection and analysis of Stage one (qualitative study) and Stage three (follow-on survey) of the research project while Professors Forrest and McHale led the data analysis of Stage 2 (account-based data from gambling companies).

Download the main report here (pdf).

Additional reports

1. Technical report 1: Qualitative Scoping Stage (pdf)
2. Technical report 2: Account Data Stage report (pdf) 
3. Technical report 3: Follow-on Survey Stage (pdf)
4. Technical report 4: Account Data file (xls)
5. Technical report 5: Survey Data file (xls)