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##### AsymBacGuy / Re: Why bac could be beatable itlr

« Last post by**AsymBacGuy**on

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**Yesterday**at 11:00:45 pmLet's compare baccarat with two casino games that have demonstrated to get players an edge.

First game is black jack.

How the hell bj was considered a beatable game?

By running millions of pc shoes to test whether high card and aces concentration (theory) really goes to player's advantage by a hi/lo card counting.

The theory was verified by practice. Bj is a math beatable game by card counting (providing a valuable penetration, etc).

Second game is craps.

Some shooters after having practiced for long at home think to be "dice controllers", meaning that they can throw the dice unrandomly thus producing profitable situations. For example, lowering the "sevens" rate or enhancing the 6 appearance on either cubes. That is to transform a random model into a wanted unrandom model.

To test the possible "unrandom" profitability such players would run thousands of throws, that means to study the limiting values of relative frequency that must deviate from common math expectancy applied to random outcomes.

If after a given amount of trials (of course the greater the better) the "sevens" percentage was lower than expected and/or the "6" appearance was greater than expected, those players might think to get an edge at different degrees (this not necessarily capable to invert the house edge in their favor) and now we talk about "statistical significance" (again restricted within certain levels).

Now theory can't be 100% ascertained by practice for two reasons: first, there's always a tiny probability to have registered unrandom results by coincidence; secondly, the dice throws sample is way more restricted than bj numbers.

Nonetheless, those dice controllers can't give a lesser damn about millions of throws proving or not their confidence to beat craps. They just collect the money won or accept the losses, assigning the possible temporary failure to a umproper technique due to several disparate causes.

Imo baccarat stays in the middle of those two extremes.

From one part certain very rare math distributions will favor B or P, but we know this feature isn't exploitable.

Yet, itlr key cards will affect the real outcomes not in the way studied so far (one side should be mathematically more likely than the other one) but in term of gaps probability intervening between two different situations not belonging to B and P.

From the other part, we must challenge the "baccarat model" to always provide perfect randomly situations regardless of when we decide to bet, a thing scientifically proven to be wrong at least in the live shoes dealt sample that any human can collect.

Now it's the dealer or the SM to really make the desired unrandom world we want to get.

In fact it's virtually impossible that at an 8-deck shoe a human or a physical shuffle machine will be able to arrange key cards proportionally for the entire lenght of the shoe, our datasets strongly state otherwise.

Again the probability after events tool will get us the decisive factor to beat baccarat.

Without any doubt.

Tomorrow we'll see why.

as.

First game is black jack.

How the hell bj was considered a beatable game?

By running millions of pc shoes to test whether high card and aces concentration (theory) really goes to player's advantage by a hi/lo card counting.

The theory was verified by practice. Bj is a math beatable game by card counting (providing a valuable penetration, etc).

Second game is craps.

Some shooters after having practiced for long at home think to be "dice controllers", meaning that they can throw the dice unrandomly thus producing profitable situations. For example, lowering the "sevens" rate or enhancing the 6 appearance on either cubes. That is to transform a random model into a wanted unrandom model.

To test the possible "unrandom" profitability such players would run thousands of throws, that means to study the limiting values of relative frequency that must deviate from common math expectancy applied to random outcomes.

If after a given amount of trials (of course the greater the better) the "sevens" percentage was lower than expected and/or the "6" appearance was greater than expected, those players might think to get an edge at different degrees (this not necessarily capable to invert the house edge in their favor) and now we talk about "statistical significance" (again restricted within certain levels).

Now theory can't be 100% ascertained by practice for two reasons: first, there's always a tiny probability to have registered unrandom results by coincidence; secondly, the dice throws sample is way more restricted than bj numbers.

Nonetheless, those dice controllers can't give a lesser damn about millions of throws proving or not their confidence to beat craps. They just collect the money won or accept the losses, assigning the possible temporary failure to a umproper technique due to several disparate causes.

Imo baccarat stays in the middle of those two extremes.

From one part certain very rare math distributions will favor B or P, but we know this feature isn't exploitable.

Yet, itlr key cards will affect the real outcomes not in the way studied so far (one side should be mathematically more likely than the other one) but in term of gaps probability intervening between two different situations not belonging to B and P.

From the other part, we must challenge the "baccarat model" to always provide perfect randomly situations regardless of when we decide to bet, a thing scientifically proven to be wrong at least in the live shoes dealt sample that any human can collect.

Now it's the dealer or the SM to really make the desired unrandom world we want to get.

In fact it's virtually impossible that at an 8-deck shoe a human or a physical shuffle machine will be able to arrange key cards proportionally for the entire lenght of the shoe, our datasets strongly state otherwise.

Again the probability after events tool will get us the decisive factor to beat baccarat.

Without any doubt.

Tomorrow we'll see why.

as.