How Does The Crash Game Algorithm Work?

How Does The Crash Game Algorithm Work?

 

We’re sure that, by now, you’re familiar with crash games. Holding out while multipliers rise, praying that you have the good sense to pull out your winnings before the multiplier crashes, is an exciting concept. If only you could know “when” the multiplier was going to crash, you’d be very wealthy indeed.

As it happens, there are a few key factors that we can identify to help you. The best way to order this to gain a good understanding is to analyze it from the perspective of the crash gaming algorithm built into the games.

What’s the crash game algorithm?

At its most basic, an algorithm is a set of instructions or a step-by-step procedure designed to accomplish a specific task. Think of it like a recipe. A recipe provides instructions to prepare a dish; an algorithm provides instructions to solve a problem or, in the case of a game, make it function.

In the context of a crash game, an algorithm is the underlying logic that dictates how everything works. It’s the invisible code that determines:

• Game mechanics: How the game behaves.
• Player actions: What happens when a player interacts with the game.
• Game state: The current condition of the game (player’s location, health, etc.)
• Game rules: How the game is played, and the conditions for winning or losing.
• Artificial Intelligence (AI): How non-player characters (NPCs) behave.
• Randomness: How chance events or unpredictable elements are introduced.

But the algorithm driving any specific crash variant has several other elements or associations involved in determining crash points and round outcomes, all contributing in different ways:

Random Number Generator

Of course, the algorithm is used to run a random number generator, and that is the core system that ensures randomness on each game outcome. Even crash games that don’t utilise cryptocurrencies (and thus, aren’t Provably Fair) can still be checked to ensure the randomisation system is working, and that everything is fair.

The RNG mechanism, however, requires professional RNG auditors to validate the results. After they audit crash outcomes, they’ll award certificates, stating that games are RNG-certified for fair play.

Low- High Multiplier Events

By studying the results of successive games, you can start to work out a picture of where the crash points in each game are. Early crashes are common.

If you examine these trends as part of one or more strategies, you’ll find that most offer low multipliers. While the frequency of low crash point outcomes tends to be high (and the winnings low), high-risk outcomes are something of a statistical rarity.

If you compare those, they tend to occur once in a blue moon but deliver truly astronomical prizes when they do so. These are the easiest crash point factors you can check when trying to find a pattern.

Provably Fair System

Provably fair games are a cornerstone of crypto gambling platforms, representing a key attraction for players seeking transparency and trust. Unlike traditional online casinos, where players rely on the operator’s assurances, provably fair systems leverage blockchain technology to allow users to independently verify the fairness and randomness of game outcomes.

This feature is particularly valued by the crypto gaming community for its alignment with principles of decentralization and transparency.

When the BTCGOSU team review crypto casinos, we see that many exclusively host third-party games that integrate provably fair algorithms, enabling players to manually check results without relying on proprietary titles.

For those unfamiliar, how provably fair gaming works is by using cryptographic techniques, such as hashed server and client seeds, to generate outcomes that are tamper-proof and verifiable. Players can cross-check these outcomes using accessible tools, ensuring no manipulation has occurred.

High-end crypto casinos often incorporate these provably fair options into their game libraries, whether through in-house development or exclusive partnerships with trusted providers.

This approach appeals to hardcore crypto enthusiasts who prioritize transparency while evoking the early days of crypto gaming, where provably fair games were foundational to the platform experience.

If you need to check that your gaming is fair, you can use the provably fair checker here on BTCGOSU.

Seed Hash and Client Seed

How the seed hash works depends on the game you’re playing. As touched on, a specific formula is used to ensure randomness generation. You can use gambling seed tools to study the client and server seeds and, in effect, audit randomness in crash games.

To do this, you’ll need to measure the input data against the outcome. After a game, take the hashing seed and cryptographic inputs, then run them to ensure that you get the same outcome each time. If you do, then the algorithm works.

This on its own won’t help you identify “when” crash points will happen, but it will show you if they are at least random.

Statistical Outliers

There are other factors you might want to consider when engaging in probability analysis, such as statistical outliers.

These are essentially rare events, anomalous outcomes that can mess with any strategies you’re putting together or any patterns that you notice. When you choose to analyse probability by playing hundreds, if not thousands, of games, you’ll get better at learning to identify statistical outliers such as repetitive low or high crashes.

There are also statistical or predictive analysis tools out there that can help with this.

Risk Mitigation Mechanisms

Each crash game has its own safeguards, security measures, if you will, that ensure house advantage, and that gambling operators won’t end up bankrupt by statistical outliers such as regularly occurring big multipliers.

Casino game developers have come up with this sort of risk adjustment tool, risk control measures if you will, as a way to protect the operator. For instance, if too many high-risk payouts have occurred, the payout control mechanics will ensure risk-mitigating crashes (low multipliers) occur increasingly frequently until things have balanced out.

This form of operator/casino risk management isn’t unique to crash games. It can be found in virtually all types of gambling games.

Multiplier Distribution

What we described above (with risk mitigation) is a form of game balancing, a way for the game to ensure that casinos don’t end up losing their edge and going bankrupt.

This isn’t the only way this occurs, though. Crash patterns can also be identified by looking at multiplier distribution. This is the range of frequency that certain multipliers appear – the multiplier spread if you will.

If too many low or high-risk multipliers have been revealed, the game has built-in statistical analysis measures to cover that off by throwing out earlier or later crashes to compensate.

Pseudo-Randomness

Given what we’ve learned thus far, you could be forgiven for assuming that cryptographic randomness (Provably Fair) and RNG systems are only pseudo-random. However, the fact that they have controlled randomness is to be expected.

All algorithms, from blockchain algorithms right down to the “shuffle mode” on music players, have some form of deterministic logic behind them. The fact that you can’t predict how it will behave is what ensures randomness in the eyes of players.

Again, though, if you follow patterns, you can at least “expect” certain factors to crop up within a given timeframe.

Game Balancing Protocols

If you were to run a casino game successfully, you’d need to run one that balances fairness vs profitability.

If it is too profitable, you’ll get tons of players, but go bust. If it’s not fair enough, you’ll make plenty of cash, but only for a while, and players will eventually stop playing.

This is the tightrope that all operator algorithms try to walk. Game developers have to balance algorithmic rules to create a setup that works for players and operators alike. Because of this, we can get a “rough idea” of how games act.

Of course, this assumes that operators don’t have access to game adjustment tools to tilt things even more in their favour.

Entropy in Randomization

It’s all very well having RNG developers ensure that games offer random outcomes and yet still course correct when necessary, but all gambling games need some forms of disorder, uncertainty and randomness to gain a crowd.

Randomness quality will vary from game to game, but as long as the operators don’t have the keys to the kingdom (games should feature high levels of cryptographic security), random noise predictability, that is to say, the ability for wild and random outcomes to occur, should be expected.

Player Misconceptions

There’s a common misconception (and you’ll find it readily on gambling forums) that games are rigged. For instance, you don’t have to look for long to find criticisms that crash games are rigged because the multiplier coefficient crashes too early.

However, many of these misunderstandings come from bad places, such as players lashing out over losses.

Operators and developers are now providing player education and engaging with player advocacy groups to dispel misinformation and explain how their games work.

As we saw earlier, Provably Fair games allow you to test the algorithm and see for yourself how fair and open these games truly are.

Short-Term Variance

Crash variance, or volatility, will tell you how often a game pays and what sort of prizes you can expect. Highly volatile game dynamics ensure big wins over the long term. Short-term variance, or low outcome volatility, will see clusters of early crashes resulting in small-scale prizes and plenty of them.

It is important for you to gauge what sort of variance and volatility you’re dealing with when putting together your probability theory or strategies to successfully predict the factors causing crashes.

Operator Transparency

Player trust isn’t just between themselves and the casinos or licensing platforms they join. Software providers also have a level of trust to maintain with players.

While not every developer is going to engage in full algorithm disclosure, those that offer algorithmic openness to auditing agencies will likely appear more favourable.

By sticking to the crypto casino brands that you can trust and studying any disclosures made to auditors by software developers, you may be able to understand which factors contribute to crashes.

Cryptographic Integrity

Finally, any game you play should be fair and trustworthy.

Cryptographic security and algorithm integrity are must-have features. Moreover, the algorithms and games must be tamper-proof. This will often show in Provably Fair audits, alongside security verification steps and randomness.

You’ll have a lot easier time trying to work out the crash point factors in crash games if you know that everything is fair, trustworthy and legitimately doing what it is supposed to be doing.

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