Why the gambler’s fallacy is so dangerous for casino customers? Learn how to identify it and avoid it

If you pay a visit to a land-based casino anywhere in the world, you will notice that some customers are sitting back and watching other visitors ‘feeding’ slot machines without getting any wins, only to assume their positions once they leave. Waiting for a losing customer to leave the slot machine and then stepping up to play, hoping to get the jackpot, is a typical behavior of casino visitors who have an erroneous assumption about patterns in gambling. 

The truth is that such behavior is not only typical among visitors of land-based gambling establishments but also among users of an online gambling platform, let’s say, whether this is a casino website https://fruitycasinos.com. But why are we talking about that behavior and why is it important to be able to identify it and avoid it in our gambling endeavors?  

Well, the answer is that it has to do with a cognitive bias -known as Gambler’s fallacy or Monte Carlo fallacy- which distorts people’s perceptions of what is likely or what is not likely to happen based on what has happened up until now. 

Let’s go back to the casino customers who wait patiently for other customers to feed the slot machine and then go and play because they believe that the machine hasn’t been giving any money for a long time now. They hold the assumption that because other customers have poured money into the slot machine and haven’t experienced any wins, it’s about time that someone does and this someone is their selves. 

In a similar way, think of a gambler who sits in front of the roulette and watches that the ball lands too many times on black. Falsely, the gambler believes that it’s time for the ball to land on red and so he starts betting to take advantage of the turning point. Eventually, this turning point will come - at some point, it is only natural that the ball will land on red- but this has nothing to do with the exact time that the gambler has thought it would do so. Rather, the gambler will have, most profoundly, lost a lot of bets before he ends up (if he ends up) winning that time when the ball lands on red. 

In both these examples, the gambler maintains a false assumption. That there’s going to be a revere of the outcome or the result of a certain event, simply because the whole time a specific pattern is being noted. This pattern in the above examples is the fact that the slot machine hasn’t given any jackpots for quite some time and so it is now the time to give money and also that the roulette ball has been landing many times on one colour and now it’s time to land on the other. 

This cognitive bias arises from the misperception that a small sample of incidents can be representative of the population. Let’s take the example of a coin flip. If we flip the coin thousands of times, eventually we will get an equally distributed turning of tails and heads in the long run. But if we flip the coin only a couple of times, it is very possible that one will dominate the other and that they won’t have equal chances of turning up. Taking a bigger sample of coin flips will naturally bring the probabilities closer to what we would see if we were to do the experiment thousands of times. But still, this would not be a sure thing. 

That’s exactly what is happening with the Gambler’s fallacy. Eventually, a roulette ball, if we take thousands of sample events, will land in red and black in a somehow equal distribution. But in smaller samples -which is the case when a casino customer is able to track down - this is not necessarily true. But the gambler believes it to be, making inferences of the entirety of events. 

Being able to identify this cognitive bias and most importantly being able to get rid of this erroneous assumption, is a good way to prevent you from losing a lot of money the next time you visit a land-based casino or even the next time you want to play at one of the iPad casinos available to you. People have actually lost fortunes because of the Gambler’s fallacy and if they were able to recognize how this bias has led them to totally wrong decision-making, they might have managed to prevent themselves from the relevant risks.