The Gambler’s Fallacy – Definition and Example

The Gambler's Fallacy - Definition and Examples - Fallacy in Logic

The gambler’s fallacy, also known as the Monte Carlo fallacy, refers to a false belief that commonly affects people who participate in gambling and other games of probabilities. It is a type of cognitive bias, meaning a systematic, built-in pattern of irrationality found in humans.

For individuals who take part in such activities, it is extremely important to learn to recognize and combat this fallacy; you’ll be able to make more rational decisions and may save yourself from unnecessary losses.


The gambler’s fallacy is the erroneous belief that a certain event is less (or more) likely to take place in the future since it already did (or didn’t) occur a number of times in the past.

To explain it more precisely, it may occur in either one of the following ways:

  • If an individual event appears to have happened frequently in the past, it is believed that the chances of it happening again are now lower.
  • If an individual event hasn’t yet happened in the past, it is believed that it’s now more likely to happen in the future.

These types of assumptions are against reason because the probability of the events occurring does not in any way depend on how the past turned out; when the events are random, and they are all independent of each other, then any future events cannot be influenced by the previous ones.


The gambler’s fallacy is easy to illustrate with the tossing of a coin:

Consider someone who flips their coin five times, and each time the coin lands “heads” up. Thus, they assert that “there is no way the next toss will land the same side up, the chances are too low!” However, they are wrong: the probabilities of the next toss are not affected by the last five. In fact, the probability of the next toss being “heads” is the same as for any single coin flip, which is 50%.


The fallacy originates from the events that took place at the Monte Carlo casino in Las Vegas in 1913.

At the casino’s roulette table, something extremely unlikely occurred: the ball fell in black 26 times in a row. The chances of this happening are roughly 1 in 66 million. As a result, participants lost large amounts of money because they kept betting against black; they believed that the odds were heavily on red’s side.

Hence, it is also called the Monte Carlo fallacy.