This post was written in September 2019, when I was Managing Director of Poker at Microgaming.
In recent months we’ve seen a trend for poker operators to publish statistics about their Game Integrity successes. In particular we’ve seen operators publish details about the number of bot accounts that have been detected and locked, how many accounts were refunded, and how much money was returned to the victims.
This is a great step in the right direction. Previously, there was a fear in the industry about publishing this information. There was a sentiment that to do so would have no upside – you can never be perfect at detecting and preventing cheating, and any shortfall from perfect is a failure. Players would simply jump on the failures without recognising the successes, or so was the received wisdom.
I give a lot of credit to the operators who stuck their neck out by publishing the information first. It made us think; we’ve been having debates ever since about whether we should do the same.
The downside of course, is that the information that has been published so far is very subjective. Imagine that I told you that we’d locked 1,000 bot accounts in the month of August. Is that good? Perhaps there were 10,000 bot accounts operating on the site in August, so I only caught 10% of them. On the other hand, perhaps there were only 900, and so 100 were false positives and I actually seized money from innocent players. The number on its own tells us very little.
Similarly, there is a huge difference in size between poker operators. If the market leader seizes €1,000,000 that is not the same as MPN seizing €1,000,000. So how do you make meaningful comparisons between poker operators and know where is a safe place to play, and where still needs to improve?
In this blog, we’re going to show data which is more meaningful, and which allows for useful comparisons between us and other poker operators. My hope is that others will take up the challenge, and post data of their own which can be compared to ours. In other words, if you’re serious about Poker Integrity, show us your stats.
Before we get on to the data, I’d like to highlight a few points about how to interpret it.
First of all, any time you seize a large amount of money it generally means one thing. Cheats who feel like they are unlikely to be caught leave large sums of money in their accounts. Cheats who feel like they are at risk of being detected deposit the minimum to achieve their aims, and cash out as soon as possible. So if you see an operator seize a large amount of money, it generally means that they were behind the curve for some time, and finally caught up, catching the cheats unaware. You’ll see an example of this in our own data from August 2018, where we caught a large bot ring thanks in part to reports from players.
Secondly, a consistently large amount of money seized or accounts banned is also revealing. Cheats should feel scared. We know from our undercover investigations that, in the last few years, cheats went from being indifferent about MPN to actively recommending that others in their community avoid us. If cheats keep coming back, that’s a bad thing. A lower amount refunded can actually mean that the games are safer.
Without further ado, on to the data:
Year | Month | % of MAU Who were Investigated | % of MAU Who Were Locked | Proactive Detection Ratio | Proactive Detection Ratio (Bots Only) | Total Refunds (€) | % of MAU Who Were Refunded |
2016 | Jan | 6.4% | 1.88% | 97.1% | 100% | € 1,066 | 0.2% |
2016 | Feb | 6.4% | 2.01% | 98.6% | 100% | € 5,315 | 0.3% |
2016 | Mar | 7.4% | 1.18% | 98.9% | 100% | € 6,590 | 0.3% |
2016 | Apr | 5.1% | 1.15% | 99.5% | 100% | € 65 | 0.0% |
2016 | May | 5.2% | 0.80% | 96.7% | 100% | € 48,409 | 3.4% |
2016 | Jun | 5.6% | 1.35% | 97.5% | 97% | € 49 | 0.0% |
2016 | Jul | 5.2% | 0.98% | 98.5% | 100% | € 21,749 | 1.5% |
2016 | Aug | 4.8% | 1.20% | 98.7% | 100% | € 1,692 | 0.3% |
2016 | Sep | 6.3% | 1.16% | 98.1% | 100% | € 3,576 | 0.5% |
2016 | Oct | 6.3% | 1.07% | 98.0% | 100% | € 3,855 | 0.6% |
2016 | Nov | 5.6% | 1.43% | 99.2% | 100% | € 454 | 0.0% |
2016 | Dec | 5.4% | 1.77% | 98.3% | 100% | € 16,751 | 1.3% |
2017 | Jan | 6.1% | 1.83% | 99.4% | 100% | € 552 | 0.1% |
2017 | Feb | 6.5% | 0.91% | 98.7% | 100% | € 18,647 | 1.1% |
2017 | Mar | 5.3% | 1.08% | 96.6% | 100% | € 0 | 0.0% |
2017 | Apr | 4.9% | 1.15% | 96.9% | 100% | € 20,045 | 1.2% |
2017 | May | 6.0% | 1.79% | 97.3% | 61% | € 16,938 | 1.0% |
2017 | Jun | 6.4% | 1.69% | 98.0% | 100% | € 35,936 | 0.8% |
2017 | Jul | 5.9% | 1.81% | 98.3% | 100% | € 38,290 | 1.3% |
2017 | Aug | 5.5% | 2.03% | 97.6% | 100% | € 11,321 | 0.7% |
2017 | Sep | 6.3% | 1.88% | 98.7% | 100% | € 6,670 | 0.9% |
2017 | Oct | 7.5% | 2.66% | 98.6% | 100% | € 5,910 | 1.2% |
2017 | Nov | 7.2% | 3.15% | 99.3% | 100% | € 48,998 | 0.6% |
2017 | Dec | 5.7% | 1.84% | 98.1% | 100% | € 2,764 | 0.2% |
2018 | Jan | 5.5% | 1.53% | 96.9% | 100% | € 22,347 | 0.9% |
2018 | Feb | 4.7% | 1.36% | 98.2% | 100% | € 42,587 | 1.6% |
2018 | Mar | 4.2% | 0.94% | 95.7% | 100% | € 18,061 | 1.6% |
2018 | Apr | 4.4% | 1.25% | 95.8% | 95% | € 14,283 | 0.9% |
2018 | May | 4.2% | 0.75% | 98.5% | 100% | € 7,269 | 0.9% |
2018 | Jun | 12.1% | 0.80% | 98.3% | 100% | € 8,716 | 1.1% |
2018 | Jul | 11.3% | 0.97% | 99.7% | 100% | € 5,381 | 0.4% |
2018 | Aug | 10.8% | 1.37% | 95.5% | 89% | € 318,784 | 1.3% |
2018 | Sep | 9.0% | 0.64% | 97.6% | 100% | € 17,559 | 0.9% |
2018 | Oct | 7.2% | 0.78% | 97.6% | 98% | € 97,338 | 1.3% |
2018 | Nov | 11.8% | 0.39% | 98.0% | 100% | € 818 | 0.0% |
2018 | Dec | 7.4% | 0.79% | 98.0% | 83% | € 43,065 | 0.5% |
2019 | Jan | 13.5% | 0.45% | 100.0% | 100% | € 1,507 | 0.2% |
2019 | Feb | 17.0% | 0.41% | 98.8% | 88% | € 31,817 | 1.3% |
2019 | Mar | 8.9% | 0.48% | 99.5% | 100% | € 24,918 | 0.9% |
2019 | Apr | 9.9% | 0.87% | 99.4% | 100% | € 61,760 | 0.7% |
2019 | May | 10.2% | 0.88% | 99.0% | 100% | € 7,750 | 0.9% |
2019 | Jun | 8.9% | 0.46% | 98.8% | 100% | € 1,046 | 0.2% |
2019 | Jul | 12.7% | 0.82% | 98.3% | 100% | € 3,407 | 0.6% |
2019 | Aug | 10.2% | 1.05% | 98.9% | 100% | € 46,366 | 0.6% |
Total | 7.43% | 1.25% | 98.16% | 97.97% | € 1,090,421 | 0.78% |
Above, ‘MAU’ means Monthly Active Users. Only real money users are counted.
The proactive detection ratio is the percentage of locked accounts that were identified through our own proactive procedures and tools, as opposed to as a result of a player report. For example, if 10 accounts were locked, and 2 were identified as a result of player reports, and 8 from our own tools, the ratio would be 80%.