The Mathematics of Poker by Bill Chen is one of those rare view changing books. Being a professional gambler requires a propensity for math, but not as much as the general public would think. I'd posit that there's no real need for calculus or any complicated math. More important is simple algebra, multiplying with percentages, and understanding basic probabilities.
Bayesian statistics goes a bit beyond basic probabilities, but it's pretty useful for games like poker. I'm not very comfortable with getting into complicated symbolic notation, because (1) most people don't get it and (2) being able to break things down to its most understandable form is the best way of teaching. Bayesian statistics is pretty much using observed information to try and get a more accurate picture of the probabilities. The most cited example is the testing for a rare genetic disease. If you test positive for the genetic disease, it's more likely that the positive test results are the result of testing error than having the disease. At the same time, testing positive the first time around means you're more likely to actually have the disease than without the first test.
Bill Chen provides a very good example of bayesian statistics in poker. When the table is broken up and you're sitting at a new table and see a guy with a big stack, either the player is very lucky or he's a loose aggressive player. The very tell that he has a big stack means it's likely that the guy is a loose aggressive player. The instant he makes a position play (an aggressive play), the probability of him of being a loose aggressive player jacks up instantaneously.
The big stack of chips is like testing positive for the genetic disease. This new information allows you to get a better understanding of what this person is really like.
Leave a comment