I have been doing some programming and simulations on various things to do with blackjack and believe I may have found a new method of winning at blackjack - I don't know if anyone has pointed this out before.
Basically I was looking at the distribution of counts occuring in a 6 deck shoe. It is obvious that the count must be zero and the start and zero at the end of shoe. It is also therefore obvious that the maximums (highest high counts and lowest low counts) mostly appear at the middle of the shoe.
Further more we know that a card count increases or decreases the house edge. It is therefore statistically possible to calculate the most probable count at the middle of a shoe, based on the outcome (win/lose ratio) of previous hands in the shoe. eg. if we have won 20 out of 25 hands, its much more likly there is a good high count that if we got very lucky on a low count.
Most importantly for any shoe with a good count halfway though - it will have on average a good count for every remaining hand in the shoe. We know this is and it is the basis for the unbalanced counts like front count etc.
So if we have a high win/loss ratio at the beginning of a shoe, its is likly that the count is high, and that we will have a favourable count for the remainder of the shoe, so we should increase our bet. Like wise a large number of looses in a shoe is likly to have occured from negetive count that will stay on average negetive until the end of the shoe, so we should decrease bet or stop betting.
We have all seen 'hot shoes' and 'cold shoes' maybe there is truth to it after all?
I can imagine that the variance is going to be collosal with a method like this, but it will be interesting to see what reduction is house edge one can obtain by betting in the later part of the shoe depending on the number of wins in the early part.
Basically I was looking at the distribution of counts occuring in a 6 deck shoe. It is obvious that the count must be zero and the start and zero at the end of shoe. It is also therefore obvious that the maximums (highest high counts and lowest low counts) mostly appear at the middle of the shoe.
Further more we know that a card count increases or decreases the house edge. It is therefore statistically possible to calculate the most probable count at the middle of a shoe, based on the outcome (win/lose ratio) of previous hands in the shoe. eg. if we have won 20 out of 25 hands, its much more likly there is a good high count that if we got very lucky on a low count.
Most importantly for any shoe with a good count halfway though - it will have on average a good count for every remaining hand in the shoe. We know this is and it is the basis for the unbalanced counts like front count etc.
So if we have a high win/loss ratio at the beginning of a shoe, its is likly that the count is high, and that we will have a favourable count for the remainder of the shoe, so we should increase our bet. Like wise a large number of looses in a shoe is likly to have occured from negetive count that will stay on average negetive until the end of the shoe, so we should decrease bet or stop betting.
We have all seen 'hot shoes' and 'cold shoes' maybe there is truth to it after all?
I can imagine that the variance is going to be collosal with a method like this, but it will be interesting to see what reduction is house edge one can obtain by betting in the later part of the shoe depending on the number of wins in the early part.