Your First Query

Let’s compute hero’s equity against a range of villain hands on a known flop.

The Query

select equity(hero)
from   game='holdem', hero='AhKh', villain='QQ+', board='Ah9s2c'

Reading left to right:

• select equity(hero) — ask for hero’s equity (sampled per trial).
• game='holdem' — play the hand as Texas Hold’em.
• hero='AhKh' — hero holds the Ace and King of hearts (specific cards).
• villain='QQ+' — villain has any pocket pair QQ or better.
• board='Ah9s2c' — three community cards are already on the table.

Run It

opql --run "select equity(hero) from game='holdem', hero='AhKh', villain='QQ+', board='Ah9s2c'"

The runner samples random runouts (turn + river) and prints the resulting equity. Re-run the query for a fresh Monte Carlo estimate.

A Second Example

Average number of suits on the river when hero holds A♠9♠ on a two-tone flop:

opql --run "select avg(boardSuitCount(river)) from game='holdem', hero='As9s', villain='*', board='2s3sJh'"

Here villain='*' means “any two cards”, and avg(...) averages a per-trial value across samples.

A Counting Example

Frequency hero flops top pair against any two cards:

opql --run "select count(hasTopBoardRank(hero, flop)) as pct_toppair from game='holdem', hero='AxKy', villain='*', board=''"

count(predicate) divides the number of trials where the predicate held by the total number of trials, giving you a probability.

Next Step

Learn more about CLI usage in CLI Basics, or skip ahead to Query Structure.