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Thursday, June 10, 2004

FYI

My PokerTracker databases are reaching maximum size with just under 2 million hands in them. A serious limitation for what I'm trying to do. I'm switching to MySQL and writing VB programs to administer them.

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Tuesday, June 08, 2004

Luck or Skill 1
For this week’s chart, I exported hands from one of my PokerTracker databases, all at $1-2 limit holdem tables and excluding any game I myself was involved in. I also filtered it to include only players who had at least 200 hundred hands represented. This yielded 793,571 hands from 1,534 players. I wanted to chart the often-used statistic in limit holdem, Big Bets earned per hour (BB/hr). Let’s see if there is a normal distribution and what the average earn might be. The poker literature throws two big blinds per hour out there as good performance at the higher levels.



Posted by Hello

The average was a negative 1.37 big bets per hour. The minimum was –35.62 with a maximum of 32.73. The standard deviation was 8.29 BB/hr.


Conclusions:
There is the makings of a bell curve present in the chart. This in itself tends to suggest that poker profits are random. If that were the case, it would also be saying that this is a negative expectation game. But, there are more losses here than can be accounted for by the rake alone. Next week, I’ll look more closely at the actual money distribution from this sample, including the rake. A major piece of information that is missing from the picture is that winners play more and win more. And there are tons of players playing a little and losing a lot. This might explain why the variance in this sample is so big!



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Tuesday, June 01, 2004

Running Good

My best earning month of poker was also the month that I spent the most time playing poker. I also spent more time working out at the gym and running in that month than any other since I’ve been playing. My worst month of poker dollar-wise was the month that I played the least, and I didn’t work out at all. Draw your own conclusions, but exercise helps me play longer and get in the right state of mind to win.

I’ve collected quite a few hand histories (over 1 million) since my last post. I’ll see where I can find some bell curves for next week's post.

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Tuesday, May 18, 2004

Raw Data

In each hand of a game, I use my perception of individual players to follow the interactions between everyone at the table. All the while, I’m trying to manage other players' perception of my game.

With the blog, I’d like to start looking at groups of players. The goal is to explore the universe of poker “truths” with statistics. Ultimately I hope to help my sense of perception at the tables.

So, here’s a small sample of data:

-Limit-----Hands---Winners---Losers---%Winners
$.5/$1---197,308--------299------393--------43.21
-$1/$2---220,013--------369------426--------46.42
$5/$10----64,983--------101------117--------46.33


Now what do I do with that? First, I try to recognize the limitations. It's not a big sample and the size of the sample is smaller at the $5/$10 level. I resolve to collect more data before drawing too many conclusions. Also, there might be more short-handed data at the higher limits than the lower ones. I’ll have to control for that. This table was collected at one site on ten-seat tables. Also, I limited the sample to players with more than 100 hands. Increasing the number of played hands radically changes the data. I excluded myself from any statistics.

What kind of inferences do I want to make? I want to know if the percentage of winners is a function of the game itself, or if the number of skillful players in the game makes the difference. Do most winning players at the higher levels make their money by cutting losses and letting their winners run? Or do they consistently stay on the winning side of the ledger more often? I don’t think I’m anywhere close to answering that at this point. Surely, both types of winners exist. Which is the most actuarially sound strategy? Thus the quest begins.

Hand Histories Wanted: depbonus@yahoo.com

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Tuesday, May 11, 2004

Averages VS Large Numbers

Anytime I solely use pot odds to make a play I’m relying on the “Law of Averages.” Results are going to vary, but the more hands I play the closer that variance will be to the actual mathematical expectation. There is no uncertainty about that, just odds of one thing or another happening. If all I ever do is play the cards, there is not much uncertainty for my knowledgeable opponents either.

All of the uncertainty in a “honest” poker game comes from the players, not the cards or the dealer. I can’t know with moral certainty what laws, if any my opponents are operating under. The trick is to infer their psychology from the way they have played past hands. With Limit Hold’em on the Internet, I can use hand histories and the “Law of Large Numbers” for opponents I see quite a bit. Once I know their type, I can apply the law of averages and use the strategy that best suits the situation given what I “know.” Without enough hands in the bank to get some statistical certainty, it is best to determine the psychology that dominates the table and stick to playing the cards. Of coarse, you want to pick the tables that will yield the juiciest return from such a strategy (Loose and Passive).

But ideally, I’d like one or two known quantities at that table too, even if they are excellent players. It reduces the uncertainty for me in the game. I also prefer short-handed play for the same reason.

Usually, a player with a really self-destructive psychology will not be around long enough online to establish moral certainty by statistical methods, nor do you need statistics to spot the maniac. He’ll also attract enough attention that table psychology is still the most important factor. So, it is with the better players and at higher limit games that this approach is most useful.

Still, all the stats are just an adjustment to pot odds. They help me determine how strong my hand must be to win in the here and now. If you know that, there is no uncertainty about the odds of this hand holding up or of me drawing to hand that is good enough. The law of averages will work its magic. Instincts about relative hand strength are nice/mandatory, but the statistical method is definitely the fastest way to develop them online.

That is, it could be, IF it wasn’t so hard to get enough data. You see, to infer a law from incomplete information, you need independent observations. This means that your data has to be situational because other players are playing the players too. In fact, a big part of what you are trying to measure is how much are they playing the players. To get independent observations, you have to create a slew of general situations that combine starting cards, position and the previous action. Given X environment, generalize that a loose/passive acts like this 75% of the time and a tight/aggressive would act this way 75% of the time. Take score, determine what category the player fits in and make your game-time decisions with those collected results in mind. I’m having troubles with the model in a six-player universe. As far as after the flop, all I got is raise/call/fold stats with no hand strength or previous action factored in. I have just enough to see the players that see a lot of flops but play tight and aggressive afterwards. And I don’t think I have enough computer power to add much more that anytime soon.

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Tuesday, April 27, 2004

If You Can’t Say Something Constructive

I wish I could say sorry for not writing. But, I’m not doing this to vent or whine when it’s not going so good. With a lot of time off for moving and some sub-par performance at the tables, it’s taken me until the 27th of the month to meet the monthly expenses.

I am sorry that I can’t be more like the Poker Blog. He’s there through thick and thin and I’ve come to rely on him as a poker news source. He’s just a better writer than I will ever be. Besides, at this point, it’s the playing of poker I have to focus on. And anything useful I have to share will spring from that.

I like those months were the nut is in the bag by the end of the first week and I’m a writing everyday. Or where everything is on schedule and I’m saying something every few days. But they can’t all be like. Can they?

My experience has been that 1/3 months are great, 1/3 are just reaching the goal and 1/3 feel like a death match that taps into the surplus from the great month. I have yet to have a losing month, but I don’t have a job to fall back on either.

Blogging during a death match is probably not recommended. At least, for me.

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Saturday, April 03, 2004

The Prescribed Amount

Got the new DSL up and going and I don’t have to climb a phone pole to use the Internet . . . impressive. Playing and blogging time have suffered over the last week or two.

Playing more equals more money. So, the most common mistake on the grind is playing too much and not being at your best for too much of the time. But recently, I’ve made the less common mistake-- not playing enough. Few people that play a game or sport for a living can afford to take many days completely off. You’ll slip out of the groove if it's going good and you’ll lose needed income if it is not going so good.

It’s not really a middle ground that I’m looking for. I want to execute the optimal amount of playing time per day. At first, you log hours arbitrarily trying to find a magic number. Eventually you learn to match your other obligations and needs with the playing conditions available and establish a rule for each day’s play.

I had some troubles making the phone company and my moving help follow the plan though.

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