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Illegal online gambling: Consumer engagement and trends
The Gambling Commission’s report into estimated trends in consumer engagement with illegal gambling websites.
Published: 25 September 2025
Last updated: 30 September 2025
This version was printed or saved on: 2 October 2025
Online version: https://www.gamblingcommission.gov.uk/report/illegal-online-gambling-consumer-engagement-and-trends
Executive summary
This report explains our methodology to understand trends in consumer engagement with illegal gambling websites. By collecting data on this market, we can improve our understanding of how it operates and use this insight to inform work to disrupt it. This is helping the Gambling Commission achieve our strategic aim of making it difficult to provide illegal gambling at scale to consumers in Great Britain.
Our approach is still in development, and we have outlined key next steps to further improve this methodology. Whilst in development findings should be treated with caution.
We collected and analysed web traffic data from May 2024 to July 2025. This allowed us to estimate trends in engagement by consumers with illegal gambling websites over this period. Our key findings are as follows.
Around 1,000 unique illegal gambling websites were accessed by consumers in Great Britain.
There was no overall increase in engagement in illegal online websites by consumers from Great Britain (measured by the number of website visits and the duration of these visits).
Fluctuations in engagement took place over this period. There was a growth in estimated engagement in the summer and autumn of 2024, followed by a decline back to a level similar to that at the start of the period where data was collected. Further data collection and analysis is needed to understand if these changes are seasonal or associated with other factors.
Part 1 - Introduction
Key point summary
Key points in this section are as follows:
- this publication explains how we have used data analytics to identify illegal gambling websites and make estimates of trends in consumer engagement
- this is the second in our series of reports on illegal online gambling
- our approach is based on our best available data and provides useful insights. Measuring use of illegal products is difficult and so naturally findings come with a caveat. More work is in progress to continue to improve both the data and our understanding of it
- the methodology should be seen as ‘in development’ and results are early-stage estimates.
The illegal market creates a high risk of consumer detriment. It is unsafe and unregulated. It also pays no tax and undercuts legitimate businesses. The Gambling Commission is increasingly using data to inform our work to disrupt this market and achieve our strategic objective of making it difficult for illegal gambling to be offered at scale in Great Britain. Our work with data also allows us to improve our understanding of trends in this market. This report sets out our methodology to achieve this and presents our initial findings.
We have used the best available data to inform our work, but nonetheless our approach has required the use of several assumptions, which we outline in this report. We welcome input from stakeholders who have access to data to help us improve these estimates as we continue to refine our approach over time.
This report is structured as follows:
- part 2 – explains how we identify illegal gambling websites
- part 3 – sets out how we measure engagement and the challenges associated with obtaining robust estimates of this activity
- part 4 – discusses assumptions made to account for use of Virtual Private Networks (VPNs)
- part 5 – sets out the headline trends we have identified and our conclusions from this analysis
- part 6 – details our next steps to build on this approach and address the caveats.
This is the second in our series of publications on illegal gambling. The first, published in September, sets out findings from our consumer research on motivations and experiences of using illegal websites.
Future publications will cover:
- publication 3: the work we undertake to disrupt illegal gambling and take enforcement action
- publication 4: the challenge of making estimates of the financial size of this market.
Defining the illegal market
We define illegal gambling as the facilitation of commercial gambling to consumers in Great Britain without an operating licence from the Commission or a valid exemption for non-commercial gambling. This applies regardless of where in the world the gambling is provided from. A gambling licence issued in another country does not permit a company to provide gambling to consumers in Great Britain. The illegal online market is characterised by a complex interplay of operators, affiliates, payment methods, and access channels. Since the illegal market is not subject to regulation and the safeguarding this provides, there is a high rate of change as new technologies and products emerge.
Figure 1 helps illustrate the various channels through which consumers engage with the illegal gambling market, with the focus of this report being illegal gambling websites. Illegal land-based gambling is also recognised as a challenge but is not the focus of this report.
Many illegal gambling websites look indistinguishable from legal websites, meaning consumers may be using them without knowing they are not licensed by the Commission – a point backed up by the findings of our first publication. Some consumers may be using VPNs to access these sites.
Additionally, a notable trend is the growth in digital currencies and social communication platforms that have created new opportunities for individuals to engage in illegal gambling. Crypto casinos allow consumers to deposit and wager with cryptocurrencies instead of traditional fiat currencies. Many Crypto casinos appear within websites that also feature more traditional gambling products.
Illegal gambling can also be promoted and facilitated through communication platforms, such as WhatsApp and Telegram. Marketing within these platforms often directs to website-based gambling opportunities, but some opportunities to gamble also exist directly within these platforms. Illegal gambling opportunities may also be found within Apps on App stores – something our current methodology does not capture.
Figure 1: Focus of this report
Part 2 - Identifying illegal gambling websites
Key point summary
Key points in this section are as follows:
- we identify search terms based on primary research into the factors that lead to consumers intentionally or unintentionally using illegal gambling websites
- we use these search terms to obtain top search engine results for gambling websites and to marketing affiliate websites – from which we extract and analyse links to gambling websites
- we remove all legal (such as GB-licensed) websites from these results – leaving us with a list of illegal gambling websites
- if websites are geo-blocked to consumers in Great Britain these websites are also removed from this list – assumptions are made later in our methodology to account for web traffic hidden by Virtual Private Networks (VPNs).
We have compiled a list of search terms to identify and monitor sites of interest. These are designed around the illegal gambling motivations identified through industry engagement, our Consumer Voice research, advice from our intelligence and enforcement teams, and insight from web intelligence platforms.
Motivations used include circumventing self-exclusion and avoiding ‘know-your-customer’ (KYC) or identity checks. On-going research is being carried out to identify additional motivations to ensure the capture of websites is as targeted as possible. An example of this is using crypto currencies for gambling, where additional search terms were introduced to our methodology in December 2024.
We have previously shared information about our methodology in our publication from October 2024: Unlicensed gambling – using data to identify unlicensed operators and estimate the scale of this market.
Although this approach provides extensive coverage of illegal gambling websites, we recognise there are other aspects of the illegal market that are not captured with this methodology, such as gambling activity directly through messaging platforms and app-based gambling.
Identified affiliate and gambling websites
Our approach to data collection identifies both illegal gambling websites and affiliate webpages including links to these sites. Sites that are already blocked to consumers accessing from Great Britain are then removed from the analysis. Websites that are blocked to these consumers can still be accessed by using a VPN. Adjustments made to account for missed VPN traffic are further discussed later in this report.
The number of affiliate pages and/or articles identified from the results to our search terms has remained relatively stable since collecting data. The number of illegal gambling websites identified through these affiliate pages has increased since May 2024. Some of this increase can be attributed to the introduction of a set of crypto casino search terms in December 2024. There was a notable increase in the number of illegal websites identified in May and June 2025. Whether this is a persistent trend will become apparent as we collect further data.
With some active websites being disrupted and closed own, and with new websites entering the market, over the period monitored, just over 1,000 unique illegal gambling websites were accessed by consumers in Great Britain.
Figure 2: Number of illegal gambling websites and affliate websites identified
| Date | Number of affiliate pages | Number of illegal gambling websites |
|---|---|---|
| May 2024 | 483 | 364 |
| June 2024 | 482 | 324 |
| July 2024 | 477 | 313 |
| August 2024 | 479 | 340 |
| September 2024 | 486 | 354 |
| October 2024 | 485 | 371 |
| November 2024 | 478 | 355 |
| Crypto terms introduced | ||
| December 2024 | 477 | 394 |
| January 2025 | 479 | 388 |
| February 2025 | 471 | 389 |
| March 2025 | 469 | 406 |
| April 2025 | 464 | 378 |
| May 2025 | 484 | 378 |
| June 2025 | 482 | 505 |
| July 2025 | 477 | 535 |
Part 3 - Measuring engagement with the online illegal market
Key point summary
Key points in this section are as follows:
- we use Similarweb, a web intelligence platform, to estimate web traffic associated with the illegal gambling websites identified through the methodology set out in Part 2
- we obtain estimates of the number of visits to these websites and the duration of these visits
- web traffic estimates are imprecise, so results need to be treated with caution. Variability in these web traffic data was estimated using nonparametric 95 percent confidence intervals from 1,000 bootstrap samples
- the data we have collected shows estimated numbers of visits fluctuating over the 15 months monitored. More data needs to be collected, over a longer period, to understand if observed effects reflect seasonal changes or longer-term trends
- the duration of visits remained relatively constant over the period monitored.
Interpreting web traffic estimates
Once a list of illegal gambling websites has been identified, we want to understand the number of visits from consumers in Great Britain associated with each website. Similarweb is a third-party web intelligence platform used to access web traffic data with identified websites. The data obtained through Similarweb is based on estimations and helps us understand volume and changes in website engagement. More details on the methodology for calculating these estimates can be found on the Similarweb website (opens in a new tab) .
Estimated web traffic involves inherent uncertainty, particularly when relying on third-party data sources that use indirect measurement techniques. To better understand and communicate this uncertainty, we applied a bootstrapping approach to 2 key metrics: average estimated visits per site and average duration per visit per site.
By quantifying the range within which the true values are likely to fall this method provides a more transparent view of the variability in the data, helping to avoid overconfidence in point estimates. Further details of our approach to this analysis are provided in Annex B.
Despite the uncertainty around these estimations, they provide insights that allow us to start understanding the scale of the illegal gambling market. They also enable the targeted disruption of the illegal gambling websites that are most likely to be experiencing high levels of user engagement – and to measure the impact of the disruption work we undertake.
Data collected on estimated number of visits to illegal gambling websites
Estimated visits made by consumers in Great Britain increased between August and December 2024.This growth levelled out and was followed by a relatively sharp decrease in February 2025. By July 2025, estimated visits had returned to broadly similar levels to July 2024.
The following chart, and further charts in this report, include a 95 percent confidence interval calculated using the bootstrap analysis outlined in the previous section.
Figure 3: Estimated visits to illegal websites
| Date | Visits (upper bound) (millions) |
Visits (point estimate) (millions) |
Visits (lower bound) (millions) |
|---|---|---|---|
| May 2024 | 54 | 36 | 21 |
| June 2024 | 31 | 20 | 12 |
| July 2024 | 22 | 16 | 11 |
| August 2024 | 27 | 20 | 13 |
| September 2024 | 29 | 21 | 15 |
| October 2024 | 43 | 29 | 18 |
| November 2024 | 55 | 35 | 21 |
| December 2024 | 46 | 36 | 27 |
| January 2025 | 45 | 36 | 29 |
| February 2025 | 32 | 25 | 19 |
| March 2025 | 30 | 23 | 18 |
| April 2025 | 28 | 21 | 14 |
| May 2025 | 21 | 17 | 14 |
| June 2025 | 21 | 17 | 13 |
| July 2025 | 24 | 20 | 16 |
Data collected on estimated average visit duration
Estimated average visit duration has also been collected from Similarweb for each illegal website that we identified. When averaging across all sites, this has remained relatively consistent around 6 and 7 minutes per visit since we started collecting the data.
Figure 4: Estimated visit duration on illegal websites
| Date | Mean visit duration (upper bound) (Minutes) |
Mean visit duration (point estimate) (Minutes) |
Mean visit duration (lower bound) (Minutes) |
|---|---|---|---|
| May 2024 | 7 | 6 | 5 |
| June 2024 | 7 | 6 | 5 |
| July 2024 | 8 | 7 | 6 |
| August 2024 | 7 | 6 | 5 |
| September 2024 | 8 | 7 | 5 |
| October 2024 | 6 | 5 | 5 |
| November 2024 | 6 | 5 | 5 |
| December 2024 | 7 | 6 | 5 |
| January 2025 | 7 | 6 | 5 |
| February 2025 | 7 | 6 | 5 |
| March 2025 | 7 | 6 | 5 |
| April 2025 | 7 | 6 | 5 |
| May 2025 | 7 | 6 | 5 |
| June 2025 | 6 | 5 | 5 |
| July 2025 | 6 | 6 | 5 |
Part 4 - Assumptions on use of Virtual Private Networks (VPNs)
Key point summary
Key points in this section are as follows:
- some web traffic to illegal gambling websites will be hidden by use of Virtual Private Networks (VPNs)
- in addition, consumers using websites which are licensed in other jurisdictions and correctly geo-block consumers from Great Britain will also be hidden by use of VPNs
- we use findings from our Consumer Voice research to make an assumption about the proportion of traffic which could be hidden by VPNs
- web traffic estimates are increased by between 24 and 51 percent to account for missing VPN traffic.
The data obtained from Similarweb represents an estimate of visits from consumers accessing these websites from Great Britain. This means that any individuals accessing these websites from Great Britain while using a VPN are not likely to be captured within our estimates.
Similarweb attempts to account for VPN use by attributing a visit to the country from which they detect an individuals’ first visit of the day. For example, if someone from country A logs onto their computer and visits a website, and then later connects to their VPN (routing their traffic through country B) and visits more websites throughout the day, all website visits for the entire day will be attributed to country A. This would partially account for VPN traffic, but if an individual always has a VPN on, or activates their VPN before accessing any websites, their traffic would not be attributed to the correct country.
As part of our Consumer Voice research into the online illegal market, a survey was conducted where participants were asked about their use of VPNs both in general and specifically when using gambling websites. This question asked, “A Virtual Private Network (VPN) can protect your online identity by hiding your IP address when using the internet. Thinking of the last 12 months, which of the following statements best applies to you?”. Of those respondents who report to know and admit to usage of unlicensed websites, 26 percent use a VPN either all the time, or specifically when visiting gambling websites. Further detail on responses can be found in Annex C.
These findings give useful insights into consumers use of VPNs specifically for gambling, but it should be noted that it is based on a relatively small sample and may not be representative of all individuals who use illegal gambling websites. Because of this, a 95 percent confidence interval can be constructed to reflect the uncertainty around the findings from the small sample. This results in between 19 and 34 percent of individuals using a VPN all the time, or specifically to visit gambling websites. Applying this to our web traffic data, it would imply that our current data accounts for between 66 and 81 percent of consumers visiting gambling websites. To scale this up to account for 100 percent of traffic, including those using a VPN, we would need to use a multiplier of between 1.24 and 1.51 times our current figures.
For context, a recent study on the illegal gambling market in France surveyed over 11,000 adults in 2023. It found that of the respondents identified as having engaged in illegal gambling online, 35 percent said they used a VPN to do so, suggesting that an estimate based on non-VPN web traffic would need to be increased by about 54 percent. This is only slightly higher than the upper bound of the confidence interval generated from our consumer research. The online legal market is significantly more restricted in France than it is in Great Britain, meaning it may be more likely that individuals will use a VPN to access gambling websites that are illegal in France.
We have noted that consumer behaviour around VPN use is undergoing a period of change related to implementation of the Online Safety Act. It will be important to monitor what impact this has over future months of data collection.
Part 5 - Conclusions
Key point summary
Key points in this section are as follows:
- combining estimates of numbers of illegal website visits and visit duration, and applying an uplift to account for Virtual Private Network (VPN) use, allows us to generate an ‘engagement metric’
- we can see an increase in engagement between summer and winter of 2024. Following this, engagement dropped
- at the end of this period, engagement was at a similar level to the start – this suggests that there is no evidence of an overall increase in consumer engagement with illegal gambling websites over the period monitored
- caution, however, is still required, given caveats highlighted about margins for error associated with these estimates.
We have combined estimations for number of visits and average visit duration into one metric by multiplying them together. We also adjust to estimate VPN usage as discussed in the previous section. This represents an estimate for the total time spent on illegal websites by consumers in minutes and is referred to as estimated engagement. By combining these metrics into one the relationship between the individual metrics is captured.
Estimated engagement fluctuated across the reporting period. The changes in confidence interval indicate a greater variability within the data around November 2024. This could be due to a number of particular websites experiencing higher levels of estimated engagement due to successful promotions or high-profile sporting events. Towards the end of the period, between June and July 2025, there appears to be less variability within the data and engagement levels are similar to June 2024. These changes in estimated engagement are mostly driven by changes in number of visits since average visit duration has remained stable throughout the period.
Figure 5: Estimated online illegal market engagement with VPN adjustment
| Date | Estimated engagement (upper bound) (Minutes) |
Estimated engagement (point estimate) (Minutes) |
Estimated engagement (lower bound) (Minutes) |
|---|---|---|---|
| May 2024 | 574 million | 293 million | 135 million |
| June 2024 | 324 million | 158 million | 74 million |
| July 2024 | 264 million | 144 million | 77 million |
| August 2024 | 281 million | 155 million | 83 million |
| September 2024 | 347 million | 190 million | 101 million |
| October 2024 | 406 million | 212 million | 107 million |
| November 2024 | 536 million | 254 million | 118 million |
| December 2024 | 483 million | 284 million | 159 million |
| January 2025 | 494 million | 306 million | 193 million |
| February 2025 | 353 million | 215 million | 125 million |
| March 2025 | 323 million | 191 million | 112 million |
| April 2025 | 291 million | 167 million | 91 million |
| May 2025 | 225 million | 139 million | 88 million |
| June 2025 | 181 million | 116 million | 76 million |
| July 2025 | 233 million | 152 million | 97 million |
Part 6 - Next steps
Key point summary
Key points in this section are as follows:
- our methodology is still in development – actions are needed to further improve our approach and the accuracy of estimates
- we have set out our existing plans. These will be implemented over the coming months
- we welcome input and ideas from stakeholders on other opportunities to improve this approach.
Our data analysis work has provided valuable information to inform disruption activity. It has also generated data to help us estimate trends in consumer engagement with illegal gambling websites.
Our approach, however, is still a methodology in development. We welcome further conversations with stakeholders to help us improve the estimates in this analysis.
Our key next steps in terms of improving this methodology include:
- We will continue to monitor research on consumer motivations and update our search terms to reflect changing trends. We also recognise the need to explore opportunities to collect data related to social media gambling (on platforms such as Telegram) and within Apps.
- Further work is needed to understand the margins of error associated with web traffic estimates. There is an opportunity to work with licensed operators to compare the actual web traffic they experience and compare that to Similarweb estimates. We also plan to trial other web traffic intelligence platforms and compare results from different sources. Both of these would allow us to calibrate the web traffic estimations for illegal gambling websites to more accurately reflect the true traffic.
- We will obtain more data on Virtual Private Network (VPN) use in larger consumer surveys such as the Gambling Survey for Great Britain. We are also exploring how we can use open banking data to track changes in VPN subscription payments and are monitoring data on VPN downloads from App stores.
Annexes
Annex A - Summary of approach, assumptions and caveats
Our approach is currently a methodology in development. The following summarises each stage of our approach to estimating engagement, outlines key caveats and limitations, and sets out actions we will take to make further improvements.
Identifying illegal gambling websites
Summary of approach
Search terms are used to identify illegal gambling websites. These terms are based on insight from consumer research and engagement with industry. Results obtained from search terms are checked against our register of licensed (and therefore legal) gambling opportunities. We also remove links to websites that are geo-blocked. This leaves us with a list of illegal gambling websites which are currently marketed at consumers in Great Britain.
Caveats and limitations
We believe these terms are effective at capturing the majority of illegal gambling websites given we see significant overlap in websites identified in different terms. This approach only captures illegal gambling facilitated via websites – for example it does not search Apps Stores. It captures websites that are marketed on social media – but does not identify opportunities to gambling facilitated directly within social media channels. Some websites that are geo-blocked may still be accessed by consumers in Great Britain using Virtual Private Networks (VPNs). Assumptions to account for this are outlined in the following paragraphs.
Actions to improve
We will continue to monitor research on consumer motivations and update our search terms to reflect changing trends. We also recognise the need to explore opportunities to collect data related to social media gambling (on platforms such as Telegram) and within Apps.
Estimating number of website visits and visit duration
Summary of approach
We use Similarweb to estimate the number of visits to websites identified from search terms associated with illegal gambling websites. We also obtain data on the estimated duration of these visits. Data is collected monthly.
Caveats and limitations
Web traffic intelligence platforms make estimates – and these can be subject to significant margins for error. We have made estimates of the associated margins for error and have published these.
Actions to improve
Further work is needed to understand the margins of error associated with web traffic estimates. There is an opportunity to work with licensed operators to compare the actual web traffic they experience and compare that to Similarweb estimates.
We also plan to trial other web traffic intelligence platforms and compare results from different sources.
Accounting for VPN use
Summary of approach
VPN use will conceal some web traffic – including traffic to websites that are geo-blocked to GB consumers. We use survey data to apply an uplift to account for this hidden traffic.
Caveats and limitations
The true level of activity concealed by VPNs is very difficult to know. Our survey sample is currently limited in size and associate with a wide margin for error.
Actions to improve
We will obtain more data on VPN use in larger consumer surveys.
We are also exploring how we can use open banking data to track changes in VPN subscription payments. We are also monitoring data on VPN downloads from App stores.
Estimating overall engagement
Summary of approach
We combine data on number of visits and visit duration to create an engagement metric. This can be used to represent overall engagement with illegal gambling websites.
Caveats and limitations
The engagement metric is subject to margins of error associated with both Similarweb estimates and VPN use estimates. This further widens the margin of error associated with this metric.
Actions to improve
The actions outline above will help improve confidence in the overall engagement metric estimation.
Annex B - Bootstrapping methodology for web traffic estimates
Overview
To quantify the uncertainty in web traffic estimates, we employed a bootstrapping approach. This is one way to leverage the properties of a sample to further estimate properties of the population that sample came from.
Bootstrapping is a method that can estimate the variability of a given statistic by randomly resampling the data with replacement. By computing an estimated mean number of visits and visit duration for each of these 1,000 bootstrapped datasets, we defined the realistic range of our estimates as the 95 percent confidence interval that spans the 2.5th to the 97.5th percentiles of bootstrap-estimated values.
This method allows us to generate confidence intervals for key metrics without relying on parametric assumptions about the underlying data distribution. It is particularly useful when working with observational data that may exhibit skewness, outliers, or non-normality.
Metrics considered
The analysis focused on 2 primary metrics:
- estimated visits per site per month
- average visit duration provided in seconds and converted to minutes.
These were combined to derive a third metric: total time spent on identified illegal gambling websites, expressed in millions of minutes.
Bootstrapping methodology
For each month in the dataset:
- a subset of the data corresponding to that month was extracted
- from this subset, 1,000 bootstrap samples were drawn with replacement
- for each sample, the following statistics were calculated:
- mean number of visits
- total number of visits
- mean visit duration.
The 2.5th and 97.5th percentiles of the bootstrap distributions were used to construct 95 percent confidence intervals for each metric.
This process was repeated for every month in the dataset, resulting in a time series of bootstrapped estimates and associated confidence intervals.
Combining metrics
To estimate total time spent:
- the mean number of visits was multiplied by the number of sites reporting data and the mean visit duration
- confidence intervals for total time spent were derived by multiplying the lower bounds of the visit and duration intervals, and likewise for the upper bounds.
This approach assumes independence between the visit and duration metrics.
Interpretation
The resulting confidence intervals provide a range within which the true values of each metric are likely to fall given the observed data. This helps to communicate the inherent uncertainty in web traffic estimates.
The confidence interval calculated through this analysis is not uniform across a time series – it varies in magnitude between months. These variations are driven by the level of variation within the population of websites that month. The confidence interval will generally be smaller in months with the lower difference between the websites with the most and least traffic. We see larger confidence intervals In months where overall traffic is dominated by a smaller number of websites with high volumes of traffic.
Annex C - Consumer research on VPN use
Consumer research on Virtual Private Network (VPN) use (from Gambling Commission Consumer Voice survey (Phase 1; April 2024))
| VPN statement | All respondents (n=1,007) (percentage) |
Has or does use unlicensed sites (n=127) (percentage) |
|---|---|---|
| I have a VPN and it is always on | 7% | 7% |
| I have a VPN, and I always use it when visiting gambling websites, specifically | 5% | 19% |
| I have a VPN, though I do not check if I am using it when visiting gambling websites | 8% | 18% |
| I have a VPN, though I never use it when visiting gambling websites | 18% | 21% |
| I do not have a VPN | 58% | 34% |
| Prefer not to say | 3% | 1% |