Liquidity

Poker is a game of network effects.  If you have four players at a stake, there’s probably one table running.  If you add one more player, there’s a good chance you’ll now have two tables running because some of those original four wanted to play more than one table.  Adding one player increased the value of all the others.

This is a liquidity break point – adding one more player at this point won’t increase the value of the others, as you’ll still be at two tables. But where are these breakpoints?  When do they stop?  If you are past all the breakpoints around the clock, you maximise player LTV.  Sites that maximise LTV can acquire players more profitably.  This is part of PokerStars’ competitive advantage.

I can find the breakpoints for your playerbase, and have ways to measure liquidity at each stake. Using this, I can say what it’s worth to move between different liquidity levels, I will have suggestions for how to surgically target promotions to make those moves; for which countries to acquire players from (for their time zones), and when to add or remove stakes.  This ought to be particularly valuable in high stake games, and in closed-liquidity markets like .EU or the US. It is possible to make more money from existing players by giving them what they wanted in the first place.

I’ve done this work before for another company in cash games, but it should work in lottery or regular SNG too, provided the poker software records players in queues as well as in the games themselves.

The calculations require hand histories (no hole cards are needed) or hand history metadata that I can specify. I’ll use Python to import those to a database and run the analysis from there.