integrity · rng
Poker RNG.
A deal you cannot see is a deal you have to take on trust, and the reasonable question is what that trust rests on. The answer is not a promise from an operator. It is a published standard, an outside laboratory that reads the source code, and a statistical test on the decks the machine actually produced.
sources checked 30 August 2026
two halves, and both have to work
A software shuffle is two things bolted together. The first is a generator that produces numbers. The second is an algorithm that turns those numbers into an order for fifty two cards, which is a much duller piece of work than it sounds: the standard method walks the deck from the back, swapping each card with one chosen from the part not yet visited. It is textbook material, published decades ago, and there is nothing secret about it.
The interesting failures live in the join. A good generator feeding a careless conversion produces an uneven deck, and an even conversion fed by a poor generator produces a predictable one. That is why the audit described below looks at the raw numbers and at the shuffled decks separately, rather than checking one and assuming the other. Neither half being fine is evidence that the pair is.
what "random" is required to mean
Randomness is not a single property, which is why regulators do not ask for it as one. The British standard names five things a generator has to demonstrate, and the useful way to read them is as five separate ways for a shuffle to be unfair while looking fine.
Uniform distribution
Every value in the range comes up as often as every other. Without this, some cards are simply more common than others, and no amount of shuffling on top repairs it.
Unpredictability
Knowing the numbers so far must not make the next one computable. This is the property that separates a generator good enough for a game from one good enough for money.
Non-cycling
The stream must not repeat itself. Every generator that runs on arithmetic eventually would, so the requirement is that it does not do so within any run anybody will ever see.
Fair seeding
The starting value, and any restart, must not reintroduce predictability. A perfect generator started from a guessable point is a guessable generator.
Scaling that keeps all of that
A raw number has to become a card between 1 and 52, and that conversion is where evenness is most easily lost. The requirement follows the number all the way to the card.
Alongside those sits a sixth rule that is not about randomness at all. A game may not adapt its own odds while it is being played, by hand or automatically, which forbids the thing players most often suspect: a deal that quietly changes to keep somebody at the table. It is a licence condition with an audit behind it, and that is worth more than any assurance printed on a website, including this one.
who checks it, and what checking means
Not the operator, and not you. The regulator keeps a list of approved test houses, the operator picks one from that list, and the two agree the scope. The work has four parts: reading the documentation to establish what was built, researching the chosen algorithm for weaknesses that are already publicly known, reading the source code to confirm the implementation matches the documentation, and running statistical analysis on the output. That last part covers the raw stream and the shuffled deck data, which is the sentence worth remembering from the whole page.
The timing matters as much as the content. New games and new generators are not allowed out until the testing is done, minor changes are picked up by an annual audit, and a change to the generator underneath several games means a representative sample of them is tested again. In the Netherlands the shape is the same with different names: the gaming system is approved against a published assessment scheme by a testing body the minister has designated, and the regulator publishes the list of those bodies. Both regimes put the same two things in the way of trusting an operator's own word, an outside laboratory and a public standard.
what you can conclude from your own seat
Almost nothing, and it is worth being blunt about why. Put all in against and you win 87.12 percent of the time when all five cards are dealt. Roughly one time in eight the best hand before the flop loses the pot, and over an evening of such spots the losses arrive in clumps, because that is what clumps look like when you only notice them afterwards.
A few thousand hands cannot separate an unfair deal from a normal bad run, and your memory of those hands is a much worse instrument than the hands themselves, since the ones that hurt are the ones that stay. That is not a reassurance that everything is always fine. It is the reason this job is done with the raw output in a laboratory rather than with impressions at a table, and it is the same argument that runs through the page on cheating: the view that settles these questions is not the one you have.
What is left to you is worth doing anyway. Check that the site holds a licence from a regulator you can name, and read what that regulator requires rather than what the site says about itself. If you think something is wrong, report it to the operator and to the regulator, with dates and hand identifiers, exactly as you would for players working together.
what this page leaves out, and why
Two things are missing on purpose. There is no description of how a weak generator would be attacked, and there is no list of signs that a shuffle has been tampered with. The first is a method, and this section does not publish methods. The second is the omission readers notice, and it is the one we are most sure about: a list of what gives something away is also a list of what the next person will make sure to avoid, and in the meantime it hands a player false certainty built on far too few hands.
There is also no verdict on any particular operator's generator here. We have not read anybody's audit report, we are not a test house, and a confident judgement we cannot back would be exactly the sort of thing this section exists to avoid. What we can do is say where the standard is written down and who is allowed to check against it, which is what the sources below are for.
Our own position, for completeness. The practice table on this site shuffles in your browser with the same textbook algorithm, using the randomness function the browser provides. It has no buy in, no prize pool and no payout, so there is nothing to certify and nobody has certified it. It is a training table, and where our own boundaries sit is written out on the page about our bots.
sources
Gambling Commission, RTS 7: generation of random outcomes
The requirement itself, in the words of a regulator: the five properties a random number generator has to demonstrate, and the ban on a game changing its own odds while it is being played.
Gambling Commission, testing strategy: procedure for testing
What an audit actually consists of, including the sentence that matters most here: the statistical testing covers the raw output of the generator and the shuffled deck data, not just one of the two.
Kansspelautoriteit, approving a gaming system
The same idea under a different regulator. The gaming system must be approved against a published assessment scheme by a testing body the minister has designated, and the regulator publishes which bodies those are.
next step
The rest of the integrity questions.
The shuffle is one of four questions that decide whether the game is worth playing at all. The others are whether people cheat, where the line sits on software during a hand, and what machines can actually do. Each page says what is known, names its sources, and says what it leaves out.
questions about poker RNG
What is an RNG in poker?
The random number generator: the part of a poker site that produces the numbers a shuffle is built from. On its own it produces numbers, not cards. A separate step turns those numbers into an order for a 52 card deck, and both halves have to be right for the deal to be fair.
How is a poker shuffle tested?
By an independent test house from a list the regulator publishes, and in four parts. The documentation is reviewed to establish what was actually built, the algorithm is researched for publicly known weaknesses, the source code is read to check that it matches the documentation, and the output is analysed statistically. That statistical work covers both the raw numbers and the shuffled decks they produce.
Who checks that a poker site shuffles fairly?
Not the site itself, and not its players. In Great Britain the Gambling Commission maintains a list of approved test houses and testing against its standards is a condition of the licence. In the Netherlands the gaming system has to be approved against a published assessment scheme by a testing body designated by the minister. The shape is the same in both: an outside laboratory, working to a published standard, under a regulator.
Can a poker site change the cards to keep me playing?
A licensed one is not permitted to. The British standard forbids adaptive behaviour outright, meaning a game may not alter the probability of its outcomes while it is being played, by hand or automatically. That is a rule with an audit behind it rather than a promise, which is the only kind worth anything here.
Can I tell from my own hands whether the deal is rigged?
No, and this is the honest core of the page. A sample of a few thousand hands is far too small to distinguish an unfair deal from an ordinary bad run, and human memory over that sample is worse still, because losing hands are remembered and folded ones are not. This is why the checking is done by laboratories on the raw output rather than by players at the table.
Why does this page not list warning signs of a rigged shuffle?
Because such a list is read by two audiences and only helps one of them. It gives a player a checklist that produces false certainty from far too little data, and it gives anyone building something dishonest a list of things to avoid. If you believe something is wrong, report it to the operator and to its regulator, who can look at the parts of the system you cannot.