Baccarat Simulation Series 37 Results: Setup SF

Results from Baccarat Simulations Series 37 are presented below.

In this series, I examined Setup SF.

Data set tested: 4,165 live baccarat shoes (313,559 total decisions), entire data-set continuously (open universe):

Bet Selection Player’s Advantage Net Score Total Bet % Won % Lost
Banker -1.11% -2,122.95 192,129 50.72% 49.28%
Player -1.45% -2,746.00 189,102 49.27% 50.73%

Data set tested: 6,651 live baccarat shoes (494,837 total decisions), starting over each new shoe (closed universe):

Bet Selection Player’s Advantage Net Score Total Bet % Won % Lost
Banker -1.01% -3,100.15 307,657 50.77% 49.23%
Player -1.37% -4,156.00 302,290 49.31% 50.68%

Flat betting 1u per bet.

Above results are from calculations using data only from live shoes recorded in live casino sessions.

The results are entirely consistent and agrees with simulated shoes, supporting the concept that there is no mathematical difference between simulated and live shoes.

Player’s Advantage is the net units won after commissions divided by the total units bet.

Disclaimer: The betting strategies and results presented are for educational and entertainment purposes only. Gambling involves substantial risks, and the odds are not in the player’s favor by design. The author does not state nor imply any system, method, or approach offers users any advantage, and he shall not be held liable under any circumstances for any losses whatsoever.

Advertisements

4 Responses to “Baccarat Simulation Series 37 Results: Setup SF”

  1. Just a Question, Do you use random.org for baccarat statistics? is it the same as zumma and other real live results with out counting the tie

    • I generate my own baccarat shoes realistically following conventional drawing rules.

      • i see, but in your opinion is it wrong or right to use random.org number generator for bacarrat results? Just need to know if what i am doing is valid or not, because i am doing a research using random.org number integrator for random results results.

      • Hmm … remember, though, P/B decisions in baccarat are not purely 50/50. The B decision has a slight edge, hence the house’s commissions.

        When you use random.org, are you able to input specific expectations for each decision?

        If not, then the resulting decisions are generated 50/50 and thus will not accurately simulate actual baccarat results.

        If so, then just be aware that you’re starting the generation of values based on idealized long-term expectancies, and actual short-term results may vary due to variance.

        In other words, if you start with a baccarat simulator (as I do), your long term statistics will approach the idealized values in the limit of an infinite number of decisions, but for all practical purposes, the actual values may vary in shorter-term stretches, as a real baccarat player may experience in real life at the tables. It will be realistic in the short term, because you’re actually generating cards based on the conventional drawing rules.

        However, starting from the idealized values in the first place (that is, using a random number generator such as at random.org with specified input values) may not be as accurate in the short term, because you’re using starting conditions based on long-term values.

        That’s just my hunch, though. One would need to perform a full statistical comparison of the random number generator’s results to a baccarat simulator’s results to be able to make a proper assessment and definitive conclusion.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.

%d bloggers like this: