Fairness is easy to understand when you can watch the cards being dealt or the roulette wheel turning. Put the game online and you are trusting code instead. That raises a good question for any digital business: when customers cannot see the machinery, what convinces them that it works as promised?
Put a coin into an old fruit machine and at least you could hear the machinery clunk away behind the glass. Online, all of that disappears. You tap a button, a few graphics move around and the software tells you whether you won. For a casino business, that creates an unusual problem: the part of the product that customers most need to trust is the part they cannot see.
Fairness Has to Be Visible in a Digital Product
A physical casino gives you plenty to watch. Cards come from a deck and roulette balls bounce around a wheel. Move the same entertainment online and the mechanism sits behind the screen, leaving the customer to judge the product from what the software shows them.
That becomes more complicated when a casino carries hundreds of games built by different developers. The Australian smokos-casino.com lobby has more than 700 games, with pokies alongside live casino titles. Its catalogue includes games from Pragmatic Play and Hacksaw Gaming, as well as Play’n GO and Nolimit City. Each developer brings its own games and mathematical models into the same customer-facing lobby.
Smokos therefore provides the shopfront, but the games inside it do not all work to one common mathematical profile. A customer moving between titles is moving between different products, even though everything is accessed through the same browser window.
For an online casino, trust starts with making that distinction understandable. The graphics may be the visible part of the experience, but there is a mathematical product running underneath them.
Computers Are Deterministic Machines. So How Do You Ask One to Do Something Unpredictable?
Professor Mads Haahr of Trinity College Dublin hit the nail on the head in his 1999 introduction to randomness: “It is difficult to get a computer to do something by chance.”
Computers follow instructions. Give a basic pseudorandom number generator the same starting information, known as a seed, and it can produce the same sequence again. That sounds like a problem for a casino game, where the next result needs to be unpredictable.
Software engineers solve it by bringing unpredictable information into the process and using generators designed to produce outputs that cannot practically be predicted from what came before. Apple Developer Documentation describes true randomisation as impossible in a deterministic system, which is why secure software uses specialised randomisation services when unpredictability is required.
Four terms make the idea easier to follow:
1. A seed gives a generator its starting information.
2. A PRNG uses an algorithm to produce a sequence that behaves statistically like random data.
3. Entropy supplies unpredictable information that the computer did not calculate for itself.
4. A CSPRNG is built so that predicting its output without knowing its internal state is computationally impractical.
The important point is less exotic than the terminology suggests. A machine that follows rules needs a properly engineered way to produce an outcome you cannot know in advance.
Random Does Not Mean Pattern-Free to the Person Watching
The software has another problem to contend with: human beings are very good at finding patterns, including ones that have no predictive value.
A 2025 Acta Psychologica study by Hiroyuki Muto and colleagues examined 17,970,830 baccarat games involving 6,625 casino customers. The researchers found positive recency behaviour, with customers tending to follow apparent trends and slightly increasing their stakes when doing so.
Casino culture has plenty of language for the same instinct. A run becomes hot; another result is due. Yet independent random outcomes can produce streaks without the previous result changing the next one.
That distinction is important when people judge whether software is behaving fairly. Randomness does not promise an alternating sequence of wins and losses. A run that looks unusual to you can still emerge from an independent process, because randomness has no obligation to produce the tidy pattern a human expects to see.
RTP Answers a Different Question
RTP often gets pulled into the fairness discussion as though it were another name for RNG. It describes something different.
RNG deals with the individual outcome. RTP, or return to player, describes the percentage of wagers that a game’s mathematical model is expected to return across a very large number of plays.
Gaming Laboratories International explains that its mathematicians establish RTP by evaluating payout combinations or using simulations when the number of possible outcomes becomes too large for straightforward analysis. GLI can also calculate the contribution made by different parts of a game and compare theoretical RTP with field data.
| Measure | What It Tells You | What It Does Not Tell You |
|---|---|---|
| RNG | How individual outcomes are generated | Your next result |
| RTP | Expected long-run percentage return | What one session will return |
| Hit frequency | How often winning events occur | The size of those wins |
| Volatility | How unevenly returns are distributed | Whether the next spin wins |
Yggdrasil’s Purrfect Potions, for example, has a 95.5% RTP and 21.26% hit frequency. Book of Books sits at 96.1% RTP but has a 33.26% hit frequency. The RTP figures are close, yet the frequency of winning events is markedly different.
Game Mathematics Is Part of the Customer Experience
Game mathematics is part of the product a casino sells. Developers set the RTP and volatility alongside the features of a game, and the same title can be available with different mathematical configurations. Hacksaw Gaming’s Wheel, for example, has published RTP configurations ranging from 88% to 99%.
That becomes relevant in a large casino lobby. Smokos carries games from developers including Hacksaw Gaming, so customers are moving between titles with different mathematical profiles rather than playing against one casino-wide RTP.
The same need for clarity applies elsewhere in technology, where monitoring and audit trails have become part of the discussion around automated systems. Casino customers also need practical control over the product while using it. Smokos provides deposit and loss limits, as well as a wager limit; reductions take effect immediately, while increases carry a 24-hour cooling-off period.
For an online casino business, transparency therefore covers both the games customers play and the controls available around them.
Trust Is the Product Behind the Product
Go back to that first spin and very little appears to happen. You press a button, the game runs and an outcome appears on screen. Behind that brief interaction sits software built to produce unpredictable results and a mathematical model that determines the game’s long-run return.
The Australian Smokos service puts those games in a browser-based product that works across devices, with identity verification required before a customer’s first withdrawal. Those practical systems sit around the game itself because an online casino business depends on more than attractive graphics.
RNG answers the question of what happens next. RTP tells you about the mathematics across a much longer run of play. Keeping those two ideas separate makes the technology easier to understand and gives customers a clearer basis for judging the digital product in front of them.
Gambling is entertainment and involves financial risk. Set limits that suit your circumstances, and stop playing when gambling is no longer enjoyable or affordable.