What Is Gambler’s Fallacy?

gambler's fallacy

Gambler’s Fallacy, popularly known as the Monte Carlo Fallacy happens when you believe that the outcome of the next random event depends on the previous ones. The theory of the Monte Carlo Fallacy is an inaccurate representation of probability.

How The Gambler’s Fallacy Works

Let’s take an example: Assuming you flip 20 coins and they all land ‘heads up’. By the Monte Carlo Fallacy, we might predict that the next coin flip is more likely to be a ‘tails up.’
However, that is a probability mistake. Here’s why:

Each coin flip is independently done, meaning all the previous flips have no effect on future flips. Therefore, in all flips both ‘heads’ and ‘tails’ have the same probability of 50%. Thus, we can expect our 21st coin to either land a ‘heads’ or a ‘tails’.

Think about it like this, if at the start of the coin toss, the player was asked to bet all 21 coins would land ‘heads up’ it would seem absurd. But once 20 have landed ‘heads up’, he feels more comfortable to apply the Gambler’s Fallacy.

Gambler’s Fallacy in Online Casinos

It is easy to fall for the gambler’s fallacy when playing slots as you try to chase losses. But remember that everything on the reel is created by Random Number Generators. And it usually depends on luck.

On the brighter side, online slots offer Return To Player (RTP). This is percentage of all the money you have bet over time. For example: If you wager twenty £1 bets on a machine with 90% RTP, you will receive £18 wins.

In the end, the most memorable case of the gambler’s fallacy took place in Monte Carlo Casino, during a roulette game in 1913. The ball landed on black 26 times consecutively and many players bet millions against black. To most people’s surprise, the 27th attempt landed on red.