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Probabilities of the Standard Poker Hands

Ranking poker hands from high card up to royal flush is really just a counting exercise — dividing the number of ways to deal each hand type by the total number of five-card hands, which is why rarer-looking hands are ranked higher.

Prerequisites: Permutations and Combinations

A five-card poker hand is dealt from a standard 52-card deck, and the total number of distinct five-card hands, ignoring order, is (525)=2,598,960\binom{52}{5} = 2{,}598{,}960. Every hand's probability is just its own count divided by that number, and hands are ranked precisely by rarity — the harder a hand type is to assemble, the higher it ranks.

Counting a specific hand type is a combinatorics exercise. A flush (five cards of one suit, ignoring straight flushes) is counted by choosing 1 of 4 suits and then 5 of that suit's 13 cards: 4×(135)=5,1484 \times \binom{13}{5} = 5{,}148 raw combinations, minus the straight flushes contained within, giving 5,108 pure flushes — a probability of 5,108/2,598,9600.197%5{,}108 / 2{,}598{,}960 \approx 0.197\%. A full house (three of one rank, two of another) is counted by choosing the triple's rank (13 ways) and 3 of its 4 suits ((43)=4\binom{4}{3}=4), then the pair's rank from the remaining 12 ranks and 2 of its 4 suits ((42)=6\binom{4}{2}=6): 13×4×12×6=3,74413 \times 4 \times 12 \times 6 = 3{,}744 hands, a probability of about 0.144% — rarer than a flush, hence ranked higher.

By contrast, one pair — the most common named hand — occurs in about 42% of all hands, which is exactly why it sits at the bottom of the ranked hand hierarchy: it's the easiest pattern to stumble into by chance.

Every poker hand's rank is fixed by how many of the (525)=2,598,960\binom{52}{5} = 2{,}598{,}960 possible five-card hands satisfy its pattern — rarer combinatorial counts (full house, flush, straight) sit higher in the hierarchy than common ones (one pair), and every probability follows directly from counting arrangements, not intuition.

Related concepts

Practice in interviews

Further reading

  • Feller, An Introduction to Probability Theory and Its Applications, ch. 2
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