| 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] |
IIRC, a martingale strategy will eventually destroy you because it requires an exponentially sustainable bankroll to maintain the same risk of ruin.
Also, 3,650 hands is far too small of a sample size for a game with such a small edge and you are probably just witnessing positive variance. See where the law of large numbers leads you and run your simulation for 500,000 hands.