Over the years I’ve written extensively on ways to beat RNG games. To summarize, RNG stands for “random number generator”. It’s basically software that determines the game outcomes, like with RNG roulette.

RNG is applied to many different casino games. If the game you play is software, then the game outcome is determined by RNG. Of course the most obvious is a slot machine game like Big Banker.

Anyway I wont explain what RNG is again. And I won’t repeat the other ways I’ve mentioned for beating RNG. This article explains some concepts you might want to explore, if you’d like to continue where I stopped.

## The Universe Has Order, Everywhere

Everything seemingly random has order to it. That is to say everything has a pattern. But often the pattern looks completely random.

If you’re familiar with my articles, you’d know I often say “nothing is ever random”, and that there’s only “cause and effect, and whether or not the two can be correlated”.

With physical roulette wheels, it’s easy to correlate physical variables that determine the winning number. I’m not the only person who figured it out. In fact much of it is common knowledge in the gaming industry. But most gamblers choose to remain ignorant about it.

One example of “cause and effect” is the technique called “visual ballistics”. This is simply estimating the speed of the ball and rotor to estimate where the ball will land. That’s at least a very simplistic explanation, and it’s not quite correct – but the explanation serves the purpose here.

So with visual ballistics, the two schools of thought are:

**Everything is random and unpredictable**: This is how you see the wheel if you have no understanding of wheel physics.**Variables can be measured to predict the winning number**: This is the view of professional advantage players.

The lesson here is your understanding limits your approach. This gets me to my next point, which is there’s no such thing as random. Everything has order. Everything has a pattern.

Everything is predictable to a degree. Predictability is more a matter of scale, amount of information, and accurate modelling.

So how can we make use of this knowledge?

Firstly, don’t expect to get anything from just a few spins. You need to look at thousands of spins – bare minimum. Although that depends on the game you’re playing.

However, it’s more likely you’ll need hundreds of thousands (or millions) of game results to know anything useful. It sounds like you’ll be sitting in front of your computer for years, but reality is different because proper data collection for RNG requires automated bots.

So almost everything should be automated by your computer and custom-made software. It would be much easier to have the source code of the RNG software you’re trying to beat, but that’s not realistically possible. And you can’t realistically wager large amounts to collect data, because you’ll lose too much in the process. So if you’re collecting data with a bot, you’ll need to make minimum bets. You’ll still make a loss in this process, but it’s part of the investment you make.

## Patterns You Can Expect To Find

With just a few game results, you wont see anything. But with much larger volumes of RNG data, here’s some of what you can expect to find:

It doesn’t look anything like “random”, right? That’s because it’s not random. Again nothing is ever random.

I discovered this myself over 20 years ago. I used a custom-made program to generate bitmap images from random number generators. The software could process any set of numbers, but it was originally designed for RNGs. I found that any change to the RNG algorithm or parameters resulted in a different pattern.

So I could see not even RNG was random. It was indeed predictable.

## The Problem With Using Fractals To Predict RNG

There were a few problems with using fractals for RNG prediction. The main one was I needed very large amounts of data. So it wasn’t practical for casino games.

However, I did manage to find ways to reduce the amount of data needed. And these approaches were applied to predict patterns from real physical roulette wheels. The methods can also be applied to data from craps dice shooting techniques, and other data analysis methods. But when it came it RNG, the data requirement as too unrealistic.

## Taking The Research Further

I’ve managed professional teams for decades. I’ve run multiple companies with various interests. I’ve made all the money I’ll ever need, and only need my passive investments to be comfortable – more than comfortable. So besides having a personal interest, I don’t have a desire to continue to research. I have no need for it.

But if you’re looking to continue, here’s what you need to know:

If you were reverse engineering DNA, you might see fragments of the DNA are missing. You could guess how they look. You might be correct some of the time, and wrong other times. It’s guesswork.

However, if you had background information about the genetic makeup of the individual, you’re more likely to make accurate educated guesses. For example, you might have additional information such as the race or gender of your subject. Finding patterns is much the same – educated guesswork.

And when it comes specifically to RNG, different RNGs algorithms have different fingerprints. Many online casinos use the same RNG software, but with different parameters. This is the same as having the same mathematical equations, but with different variables (values). The outcomes and patterns might seem different, but the underlying source code and equations are much the same. And by knowing this, you can model the correlation between different sets of game results you collect. But this cannot be done manually. You’ll realistically need automated software to conduct analysis.

Ultimately what you’re trying to is reduce the amount of data you need for reliable RNG analysis. And you achieve this by correlating any data you have, to other sets of data you have.