Welcome

Hello all, welcome to my online poker blog.

I've been playing on and off for a decade after being introduced by a friend.

I played regularly for a few years during the poker boom and had a decent record at the micros, particularly Rush and Zoom No Limit Hold'em games (here's one of my graphs).

Around 2012 I began a new career which involved immersing myself completely in study in my spare time, so I had little to no time for poker. However recently this burden has eased and so I have been gradually dipping back in.

I'm an amateur player who still hopes to some day beat the rake.





Friday 11 December 2009

Standard Deviation in HUSNGs

Well I decided to spend an hour looking back at some basic maths probability (it's been a few years since I looked at any) and decided to create a spreadsheet where I could calculate variance, standard deviation and some confidence intervals for HUSNGs. Here are some numbers and conclusions that will help me in the future.
Playing without knowing our ROI
Truly, noone really knows what their exact ROI is, but those professional players who play tens of thousands of games per year are fairly close to realising their expectation. This is obvious due to the somewhat linear curves that are displayed on sharkscope. So how do we go about ascertaining whether we can beat the games or not? Well, we can use elimination. If we have a winrate of 60% then after roughly 300 games it is 99.7% likely that we will not have lost any money. This means that if we HAVE lost money, we cannot reasonably consider that figure as our winrate. If we think our winrate is 55% then after about 2000 games we should not have lost money 99.7% of the time. Once again, if we have then we are likely a break even player at best. Ok, so we should just play and forget about it then? Well, this is where we must start making assumptions. In the games I've played so far (albeit small stakes) the players have been BAD. Few of them will know the maths like I do or will have the determination to improve to the level of play that I want to reach. So I will estimate that I should be able to beat the games at a winrate of about 55%.
Numbers assuming a 55% winrate
Let's say we play the $20 HUSNGs for a year on Absolute poker. We'll need to play over 2000 to guarantee some plus ROI 99.7% of the time. If we play ten a day for 300 days, then in those 3000 games we can expect our earn to be $3900+or-$3270 99.7% of the time. This is $630 < average < $7170. As you can see, there is alot of 'variance' in that range. Still, next year this should be the minimum that I should try to achieve since this a guaranteed profit of at least $630 providing our initial winrate assumption is reasonable. If we run good that's a few thousand quid - nothing to be sneered at.
Turning professional
Could we make a living playing $20 HUSNGs? Yes. Once again assuming a 55% winrate, if we played 100 games a day for 300 days of the year then we have 30000 games. Our earn would be $39000+or-$10340 so we would win (99.7% of the time) at least $29000.
Conclusions
It was about time that I did this work and got some idea about our expectations for these games. My first goal should be to learn as much as I can to beat the games, my second to play enough games such that I ride out the standard deviations from the average. If anyone thinks I'm about to jump ship and turn pro... Well tbh I'd love to give it a try. Maybe some day I will. But unfortunately it's a very big risk - too big a risk currently. My plan for the next year is just to learn, learn again, play some and then learn some more. I still enjoy playing and working stuff out - and being right some of the time - and I love the game theory and maths side to poker. It will probably just remain a firm hobby that might make me a bit on the side. But you never know, maybe some day.
If there's any maths that I fucked up - I'd give that a 99.7% chance of being true - please point it out. I deliberately typed in the equations in the spreadsheet instead of using the predefined functions so that I was using old skills almost forgotten. GL.

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