Also known as the Monte Carlo fallacy, it’s the mistaken belief that a run of specific results in a random process makes it less or more likely to occur the next time.
For example, a series of 10 coin flips might all land on heads. Under the gambler’s fallacy, a person might expect that the next coin flip is more likely to land on tails the next time.
Primary origin: Daniel Kahneman; Amos Tversky