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Baccarat system design on the topic of Card Shoe and Result Shoe.
Let me repeat the statistics here:
(1) Total 500,000 shoes (1-deck):
Total hands: 5075866 (10.15/shoe)
Player: 2268293(44.688%) Banker: 2332781(45.958%) Tie: 474792(9.354%)
Total Shoes: 1.459E+42
(2) Total 500,000 shoes (half-deck):
Total hands: 2450623 (4.90/shoe)
Player: 1093333(44.614%) Banker: 1130165(46.117%) Tie: 227125(9.268%)
Total Shoes: 1.954E+19
Galo thinks the Card Shoe vs. Result Shoe distribution will obey Gauss distribution. I try to find it out. If the object is a 8-deck shoe, I have no idea how much samples should I run to get a close result because the whole set Card Shoe of 8-deck is 416!/[(32!)^9*128!]=1.6494E+376. So I better start it from a 1-deck shoe because not only the Card Shoe is much much less but the Result Shoe is about 2^10.15=1136. I would make the Result Shoe set 2^12=4096 and see how are the pigeons go into the pigeon-cages.
First I label the shoe from 0 to 4096 as followed. For example, a result shoe is PBPPPPBBPB (recorded from left to right, first hand is P last hand is B); convert it to 1011110010 (P=1, B=0) then take it as a Bin number and convert it to Dec number 317. Hence, this shoe is labeled 317. By this way shoe from 000-000-000-000 to 111-111-111-111 has the only individual label number from 0 to 4096. Note that the power order is from left to right; and the shoes are eliminated the Tie; and I do not delimit fixed hand shoe, i.e. there are shoes are 7 hands, there are shoes are 10 hands, etc. So all Banker shoes will have the same label 0, and some Result Shoe will overlap too, particular those shoe adding Banker after Player, e.g. shoe 0011101 has same label as 0011101-000 has. I will think about this label system later since I have already ran 5 million shoes.
See the curve and the output data. I can see the curve is not a Gauss curve, is it? Probably it is.
The shoe label method has drawback, any idea better one?