Experts will tell you that a £10-20 hold’em player, with perfect play, should expect to win on average about £35 per hour. The question is, of course, what constitutes perfect play and how it can be achieved.
If you are a winning player, you probably realize that perfect play goes a lot further than simply never allowing yourself to go on tilt, bluffing and calling at appropriate frequencies, playing the right starting hands in the correct positions, and seeking out the best games. Perfect play also means that you need to apply strategic concepts in a dynamic fashion. The strategy you choose must be considered in relation to the current game situation, in order to be applied optimally. Poker, quite unlike Blackjack, does not lend itself to a formulaic approach.
Even Blackjack theorists discuss basic strategy as separate and distinct from advanced strategy. Most poker writers have not made this distinction. Those who have, do not emphasize it nearly enough. But the analogy is clear. First, if you expect to be able to play poker perfectly, you need to have a thorough knowledge of basic poker strategy. Once you understand and have assimilated basic strategic concepts, you need to learn how and when to deviate from them in order to apply this strategy dynamically, based on changing game conditions.
How important, first of all, is basic strategic knowledge to the poker player? In a word: imperative. If you have no basis for making decisions about whether to call, fold, raise or re-raise, you might as well play the lottery. While you will win occasionally, you will exercise no control over your destiny as a card player. Moreover, if you are not yet thoroughly grounded in basic strategy, you cannot consider yourself a winning player and your goal at this juncture ought not to be perfection. It should be centered on learning basic poker concepts. Once you are a proven winning player, you can concern yourself with learning to play perfectly. It is also important to realize that even when you know and understand the basics, this know-how must be continuously applied. The knowledge and abilities that comprise basic poker skills are not a pill to be swallowed once. They need to be continuously refined. Andres Segovia, the classical guitarist, reputedly spent 4 to 6 hours per day (of his 6 to 8 hour practice day) playing scales. Think about it. The greatest classical guitarist of our generation did not spend the majority of his practice time learning new pieces, or practicing his concert repertoire. He did just what beginning music students do the world over. He played scales! He spent 75 percent of his practice time on the basics, and he did this every day.
Recently some friends of mine and I have been experimenting with a poker software product called Wilson’s Turbo Texas Hold’em. We created a number of “players” with good skills, and have put them in computer-simulated games where all the other “players” were very beatable. Our objective was to see just what kinds of a win rate good players could expect to achieve.
The beatable players we created ranged from absolute rocks, to complete fish, and other varieties of live ones you’d love to find in a real game. We expected that our good players would absolutely dominate these games, since they never played hands they should not have, could not go on tilt, never got tired or emotionally distressed, nor suffered any of the game-weakening ills that hammer all of us from time-to-time. To our surprise, that was not the case. While our best simulated players always came away the big winner after sessions comprised of 100,000 hands (at 30 hands per hour, that’s equal to more than 3,000 hours of live play), they did not win at the rate we expected. We saw three possible reasons. First, we could have constructed less-than-expert players. We just do not think this is the case. Second, it simply is not possible to average £35 per hour in a £10-20 hold’em game, regardless of how well you play. We discounted this, since in live games many of us already have an actual win rate that exceed our computerized models. Third, the computerized models can apply only basic strategy, but cannot deviate from it based on the changing dynamics of the game. This, of course, is the hypothesis with the most validity.
Next time we will look at some specific examples and you’ll see that even big name poker players, competing for large sums of money in major tournaments, neither play perfectly all of the time, nor recognize when they are confronted with a situation requiring a dynamic shift in strategic thinking.