noal

Coming from a background of working with security for financial institutions (Banks, Creditcard companies and so on), I'd highly recommend re-evaluating this implementation from a liability perspective.

Feel free to send me a message (contact information in profile), and I can share advise on how the banking and creditcard industry deals with cross authentication and verification.

I'll clean up my code a bit and post it on pastebin, there's probably a mistake in my logic somewhere.

Overall; I agree [and having played my share of a variety of strategies] I found the data to be confusing, hence my peaked curiosity. :-)

Though it did (in the simulation). The accumulated winnings with the limits on bankrupt and cashing out at 1500 created a over time win percentage in a otherwise negative-biased game?

Note that's 3,650 decks / 28,470 hands (not counting "War" hands).

As it was run twice, it's closer to 56,940. (using two different alg.)

Rerunning it (now) produces minimal differences, even at a 1,000 year setup. (3-5% variation)

Interesting read; I was playing with similar thoughts over my lunch break a couple of days ago.

The base of my sample program [implemented in ruby] was based (in theory) of Proportional Betting "The Martingale" - http://www.bjmath.com/bjmath/progress/prog1.htm

The game I picked was "Casino War" [ http://wizardofodds.com/games/casino-war/ ], as it was very quick to implement in a few lines of code. I selected the base rules as played in Garden City Casino [Bay Area] (50c drop per every $100), and came up with the following:

Game/House Rules: - 6 deck of cards. - Played until 1/2 is gone. - 50c drop for every $100 [Example: $200 bet costs $1, $300 $1.5.]

Betting Rules:

- Base Bet is always 1% of current wallet, at starting point - $10. - If the proportional bet can not be covered by wallet, the round is surrendered and the player waits until re-shuffle. [Example: Lost up to $500, next bet is $1000, wallet has $700, game ends/waits and the player accepts a loss of $300.] - Bets are doubled on loss as defined in the Proportional betting link.

Here's my data, though I believe something is wrong due to its results:

- I ran the initial program, as is, expecting the player to play one round every day for 10 years. - Losses and earnings were added together. - The average win % went to 58.4%. - The average cash win [the times the player didn't go bankrupt] was $1590. - Max loss [consecutive] cash $2980. [Bankroll covered over multiple sessions]

* A key point here is the average cash win. It was highly consistent and never below 1500.

I then added a factor that stated in the software:

- If winnings are at $1500, the player stops, takes the winnings and waits for a re-shuffle.

* Win percentage went up to 64.8% !

If anyone is interested, I'd be happy to share/pastebin the code or similar. Overall, due to the percentages I'm assuming something is wrong with my assumptions/gameplay, but so far an interesting experiment.

[Edited for clarity on betting strategy]