Casino Random Number Generators (RNGs) Explained

Random Number Generators (RNGs) are core components of gambling systems, ensuring ‘fair’ and probably unpredictable outcomes. The use is critical in both online and land-based clubs, where trust and transparency are paramount.

Many appreciate RNG for adding unpredictability and freshness, especially in roguelikes and loot systems. However, excessive randomness often sparks frustration, particularly when it undermines player skill.

Some gamers exploit predictable PRNG behaviours to their advantage (speedruns, loot manipulation). Others use seed resets for consistent outcomes, and yes, exploiting predictable PRNG behaviour really works - especially in older games or systems where the seed and algorithm are accessible or poorly protected.

What is an RNG?

An RNG is a system - either software-based or hardware-driven - designed to generate sequences of numbers with no discernible pattern. There are two primary types:

• True RNG (TRNG): Uses physical phenomena (e.g. radioactive decay or atmospheric noise) to produce truly random outputs. Rare in gambling due to complexity and cost.
• Pseudo-RNG (PRNG): Uses mathematical algorithms and a seed value. Fast, efficient, and widely used in digital iGaming environments.

Role in Gambling

RNGs determine outcomes in slot machines, virtual table games, instant win titles, etc. In regulated environments, certified PRNGs ensure every game round is unpredictable and free from manipulation.

Each spin or hand is generated in real-time, based on current algorithmic output. They claim that there is no memory of previous outcomes, ensuring a fair experience for all players.

To meet licensing requirements, RNGs must be regularly audited by independent bodies such as:

• GLI (Gaming Laboratories International)
• iTech Labs
• BMM Testlabs
• eCOGRA

Tests applied include chi-square distribution analysis, entropy evaluation, and sequence independence checks. Certification guarantees statistical randomness, integrity, and compliance with local gambling laws. Moreover, licensed casinos arrange random audits and test their software to make sure RNGs are working properly.

Emerging Trends

• Blockchain RNGs: Offer provable fairness via smart contracts and decentralised oracles (e.g. Chainlink VRF).
• Quantum RNGs: Utilise quantum mechanics for ultra-secure randomness - still early stage.

RNGs are the backbone of fair gaming. Properly implemented and certified, they ensure unbiased outcomes and maintain player trust. For operators, investment in RNG transparency and compliance is not optional - it’s a fundamental requirement for legal and commercial success.

 

I really like your take on this HARD subject. I'm give you my take. This is not plagiarism! I wrote. You can use. You might give me a "quote"? Or not...it's your decision...!

The SECRET WORLD of VIDEO POKER PROGRESSIVE
By Frank Kneeland (2006)​

Pseudo-anti-random-disestablish- mentarianism
“Oh, many a shaft at random sent

Finds mark the archer little meant!

And many a word at random spoken

May soothe, or wound, a heart that's broken!”

~ Sir Walter Scott​

Now that we’ve beaten to death the subject of what “random” is and isn’t, discussed the correct usage of the word “luck,” and the nonexistence of the “law of averages,” we can finally explain how a video poker machine deals your hand and picks the cards. This information is separate from the basic concept of “randomness” because now what we will discuss is computer-generated randomness.

Believe it or not, when you bring computers into the mix, the jury is still out even today on what is, and what is not, random. It seems the only thing more random than a truly random number is our understanding of it, and the opinions of the people making them. In nature, philosophers believe the things we think of as random are really only beyond our capability to predict. Unpredictability and randomness aren’t really the same thing. A math teacher once commented that, “teaching probability math properly was probably the most problematic[1].” (Try saying that ten times fast.) Mathematicians define random as something having no discernible pattern; yet if you produce a long string of numbers that don’t have an even distribution of digits, purists will immediately accuse it of being non-random. But isn’t an even distribution of digits a pattern?

A recent scientific description of what defines completely random numbers is, if the algorithm needed to describe the number is as long as the number itself then it is completely random[2]. Oddly, the science community has been arguing for years on what is and is not random as much if not more than the philosophers and theologians. More surprisingly, around 1965 many mathematicians[3] wanted to remove patterns like (1212121212) from long strings of randomly generated numbers, to make them useful for statistical analysis. This almost borders on insanity! By definition, in any sufficiently long string of completely random numbers, patterns like this will and should be present. They felt, however, that the random numbers needed to be manually doctored to make them more random (how weird is that?). How can a human, by dedicated purposeful action, make an already completely random number... better? If something is already random, it is impossible to make it “more random.”

Believe it or not, when doing the research for this book, I managed to confuse even myself a little. I thought I knew what random was, but now I’m not so sure. When you roll a die, we assume the chance of a one through six coming up is equally likely. When you roll two dice, however, as in craps, the numbers generated do not distribute evenly. A seven comes up six times as often as a two or twelve, yet we still think of this as random. When we talk about random with video poker or slots, what we really mean is, “Equiprobable and unpredictable.”

“Equiprobable,” means all the possible outcomes must be equally likely and occur with the same relative frequency, and “unpredictable” means you don’t know exactly when or in what order they will come. Since all modern slots and video poker machines use computer processors, they are limited to the level of randomness you can get with a computer algorithm, which unfortunately isn’t very good.

Believe it or not, it’s very hard to get a computer to do anything (other than crash) purely by chance!

Surprising as this may first seem, it is really difficult to get a computer to do something randomly. A computer runs a program, basically a set of instructions and follows these instructions blindly and is therefore completely predictable. The closest you can come to truly random numbers (if such a thing exists) is by an algorithm called a pseudo-random number generator. “Pseudo” because it is not truly random and quite predictable if you know the algorithm used. Take for example the never-ending digits of pi. They are random by a certain definition, as are some logarithms. They do not repeat, and they meet the three main criteria of randomness:

1. Even distribution of digits. (1234567890)
   
   
2. Equal chance of number pairs. (10,11,12,13,14,15,16,17,18,19,10,21,22,23,etc.)
   
   
3. Expected distribution of same-number strings. (0, 00, 000, 0000, 00000, 000000, etc.)
   

Yet anyone that knows pi could easily tell you in advance what the 81st digit will be and when to take it out of the oven. According to this pseudo- random definition of random numbers, a string of numbers is random even if it’s predictable. Of course this type of pseudo-random number would never do for a gaming device. So, how do they do it?

Believe it or not, in order to get a truly random number out of a computer you have to introduce what is called “an external source of entropy[4].” The random element must come from without, not from within, in order to be completely unpredictable as well as equiprobable, which is what we really mean when we say “random” as it applies to slots. On a computer, programmers have experimented with key stroke delay and mouse movement to generate the needed “seed number” as it is called, for their source of entropy. Fancier devices use the unpredictable decay of radioactive isotopes measured with a Geiger counter, listen to radio static from far off galaxies, or measure the emitted light radiating from a lava lamp (long live disco). The lavarand people at Silicon Graphics have been clever enough to use lava lamps to generate random numbers, so their entropy source not only gives them entropy, it also looks good at parties. I wonder if they get governments grants. I would have loved to be at that meeting. “Dude, check it out. Here’s where your money went. It makes random numbers and chicks dig it!” I kid...I just wish I had thought of it!

Slot manufactures rely on a different method and use a continuously cycling clock to generate their truly random numbers. It is constantly going even when no one is playing the machine and passes along a number when someone does.

The moment you hit the deal key it reads the clock on that particular millisecond (one thousandth of a second) passes the time along in the form of ’the seed’ to the RNG (Random Number Generator).

Here is the actual algorithm used in one type of RNG for Micro controllers:

Seed * multiplier * 2nd seed + adder = end result

Seed = Current clock time reduced to integer

Multiplier = arbitrary number, such as 1664525

2nd seed = another clock time after programmed read delay​

Adder = arbitrary addition to the result of the current sum

End result = sum made to fit desired spread (such as 1-52)

In one particular programming language it would look like this:

unsigned long seed ;... seed = 1664525L * seed + 1013904223L ;

Another example would be:

X0 = seed value (e.g., the time expressed to 10 digits), Xn+1 = (3141592653Xn + 2718281829) mod 2^35.

Mod means taking the remainder after dividing by 2^35, and is equivalent to just doing all the arithmetic in 35 bits or however many you are trying to generate. In the second round X0 is replaced with X1 (the output of round one), and so on.

Each different possible number represents one of the possible combinations you can draw from a 52- card deck. You don’t know what’s coming up. You can’t predict what’s coming up. The good news is, you don’t need to predict what’s coming up. You only need to know what all the things that can come up are, and that they each have an equal chance of occurrence. This is as fair and as random as things get. In all regulated areas, the gaming control board uses advanced analysis programs to test the output of industry RNG’s. I only wish life was this fair and unbiased. Believe it or not!

[Footnotes]

1. Not a word for word quote, but summarized from Burrill Gail, (1990) Statistics and probability. Mathematics Teacher: 83, 113-118.
   
   
2. Chaitin, Gregory J. 1966. In the Journal of Association for Computing Machinery 13: 547-569.
   
   
3. Ian Hacking, Logic of Scientific Inference (p. 131), and G. Spencer Brown, Randomness I (p. 149).
   
   
4. A reference to particle emissions from radioactive materials not the concept of universal chaos and decay.
   

“Some say, the secret to financial success is thinking ‘outside the
box.’ I say, thinking inside the box is just fine, as long as you sell
the box after you’re done.”
~ Frank Kneeland, 2005​

 

Wow, thanks for sharing! It’s a great reminder of how complex and multilayered the concept of “fairness” really is when it comes to gaming algorithms.
My general conclusion is: the machine doesn’t cheat you - it just honestly operates against you. Playing even in a licensed casino is essentially a fair contract built on unequal terms. And understanding those terms is the real player’s wisdom, I think.

 

interesting thxs

 

I really liked your post. I have seen really bad ones... I was a first contributor for this website. Now I just reply when some NEW happens...

Good luck!

 

Only the water of new knowledge can grow fruit in the soil of misunderstanding. ~FK 2002