In probability theory, the craps principle is a theorem about event probabilities under repeated iid trials.
denote two mutually exclusive events which might occur on a given trial.
Then the probability that
occurs before
equals the conditional probability that
occur on the next trial, which is The events
need not be collectively exhaustive (if they are, the result is trivial).
be the event that
occurs before
be the event that neither
occurs on a given trial.
are mutually exclusive and collectively exhaustive for the first trial, we have and
and solving the displayed equation for
gives the formula If the trials are repetitions of a game between two players, and the events are then the craps principle gives the respective conditional probabilities of each player winning a certain repetition, given that someone wins (i.e., given that a draw does not occur).
In fact, the result is only affected by the relative marginal probabilities of winning
; in particular, the probability of a draw is irrelevant.
If the game is played repeatedly until someone wins, then the conditional probability above is the probability that the player wins the game.
This is illustrated below for the original game of craps, using an alternative proof.
If the game being played is craps, then this principle can greatly simplify the computation of the probability of winning in a certain scenario.
Specifically, if the first roll is a 4, 5, 6, 8, 9, or 10, then the dice are repeatedly re-rolled until one of two events occurs: Since
are mutually exclusive, the craps principle applies.
For example, if the original roll was a 4, then the probability of winning is This avoids having to sum the infinite series corresponding to all the possible outcomes: Mathematically, we can express the probability of rolling
ties followed by rolling the point: The summation becomes an infinite geometric series: which agrees with the earlier result.