Gambler’s fallacy is a cognitive bias that affects how people perceive randomness and probability. It is the belief that past events can influence future outcomes in games of chance, even when they are independent and identically distributed. For example, someone who believes in gambler’s fallacy might think that after a long streak of red numbers on a roulette wheel, a black number is more likely to appear next, because the wheel is for a change. This is incorrect, because each spin of the wheel is independent of the previous ones, and the probability of red or black is always 50%.
Gambler’s fallacy can lead to irrational and suboptimal decisions in gambling and other domains. It can cause people to bet more or less than they should, based on false assumptions about the odds. It can also affect how people interpret patterns and trends in data, such as stock prices, sports results, or weather forecasts. Gambler’s fallacy can result from several psychological factors, such as:
Gambler’s fallacy is also known as the Monte Carlo fallacy, because of a famous incident that occurred in 1913 at the Monte Carlo Casino, where the roulette wheel landed on black 26 times in a row. Many gamblers lost huge amounts of money, betting on red, thinking that it was bound to happen soon. Gambler’s fallacy is sometimes confused with the hot hand fallacy, which is the opposite belief that past successes or failures can predict future outcomes in games of skill, such as basketball or poker. However, both fallacies are based on the same error of reasoning, which is ignoring the independence and randomness of events.