Casino game outcomes are mostly random, but sometimes gamers anchor up to a certain series of results, believing they are signals for future upshots. These individuals exhibit what is called the gamblers fallacy.

They fail to understand that, in casino gaming, relying on past data to make decisions in games that are fundamentally random is often a trap. Current results are not a map of future outcomes.

But hold on for a minute: some people have made accurate decisions by monitoring previous occurrences, haven’t they? Yes, these instances occur, but after how many trials?

In today’s casino news, we discuss the gamblers fallacy to see if past gaming results can actually determine what happens next.

**The Gambler’s Fallacy: How Past Bets Fool Us**

The gambler’s fallacy, also known as the Monte Carlo fallacy, is an overreliance on past data, a bias in people’s perception of randomness. It is a belief that independent past events can influence the outcome of future events.

In simpler terms, the gambler’s fallacy suggests that if an event or a scenario happened frequently in the past, it is less likely to occur in the future and vice versa.

Consider a coin toss. A player may believe that because a coin toss landed on heads four times in a row, there is a high likelihood that the next coin toss would be tails. This is a gamblers fallacy example.

There is another opinion on random sequences, which is an inverse of the gambler’s fallacy. It is called the hot hand. Still, on the coin toss example, someone believing the hot hand fallacy thinks that if they guess the first outcomes correctly, their next prediction will also be correct because they are “hot.”

Psychologists have traced both phenomena to something called representative heuristics.

While this is interesting, let’s focus on the origin of the Monte Carlo fallacy.

**How It All Started: The Famous Monte Carlo Casino Gambler’s Fallacy**

The gambler’s fallacy happened at Monaco’s famous Monte Carlo casino. On August 18th, 1913, some gamblers decided to play roulette at the establishment instead of casino slots. They started the game normally: betting on either red or black. Ten spins in a row, and the ball landed on black. Then, the gambler’s fallacy kicked in.

Players began betting on red, believing the ball would land on red next. They were convinced and placed even bigger bets only to see black. The ball continued to land on black and did so 16 times. By the time it landed on red, the players had lost millions while the casino had made a fortune.

If you were there that day, what would have been your decision? Think about it. It’s not out of line to think that the ball should land on a red pocket. So, what went wrong on this day, and what is the issue with the gambler’s fallacy?

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**The Flaw in the Gambler’s Fallacy**

Let’s use the aforementioned coin toss, which represents chance in in which the outcome of each toss is independent of the next. There is always a 50% chance the coin will land on heads or tails. Since the coin toss has no memory or a set pattern of doing things, the outcome remains 50%. This is why the gambler’s fallacy is a mistaken belief.

However, some people have noticed that if you flip a coin long enough, you’ll begin to notice a pattern. This brings us to the next discussion point.

**The Law of Big Numbers**

In 1939, a South African mathematician named J.E. Kerrich found himself in an internment camp in Denmark. Out of boredom, he decided to flip a coin 10,000 times and record the number of times the coin landed on heads. The more times he flipped the coins, the percentage probability of heads approached 50%.

The law of large numbers states that more trials bring us closer to the relative frequency of the outcome and approach the probability of the event. It suggests that systems of chance balance themselves over a long period.

So, the gamblers at Monte Carlo were partially right, but the issue was that they didn’t know when things would balance out.

**How Do We Reconcile These Two Ideas?**

One difference between the gambler’s fallacy and the law of large numbers is the number of times the event happened. Probability may even out after a large number of trials. Few trials often lead to contrasting results, which is why the ball landed on black 26 times before red in the Monte Carlo Casino.

If you are playing slot games online, no matter how long you play, RNG makes your gaming outcome unpredictable.

So, while the gambler’s fallacy has some truth, it only takes a small sample of events from an infinitely large number of probable events, a sample that could very well be skewed.

**Tips To Avoid The Gambler’s Fallacy**

It’s easy to fall into the gambler’s fallacy, thinking you followed your intuition. However, there are things you can consider to prevent this.

We also have a long list of casino guides if you need help.

**Accept the Law of Chance**

Understand that every toss is independent of the other. You can’t judge a new outcome based on the previous. Focus on the probabilities of the events. This is why wagering odds are usually made open.

**Be Flexible but Make Plans**

Have a structure for your betting decisions. You can change them if you have thought about it well and are not trying to rely on your recent gaming results.

**Consider Other Opinions**

Following your intuition is good, but check for other opinions that can challenge your thinking to establish a balance.

**Making It Brief**

The gambler’s fallacy is a bias many people fall prey to without realizing this is what they are doing, but now you know the truth behind the fallacy and its flawed reasoning. Watch out for this whenever you’re gaming!

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