Normally anytime we choose to bet a side we hope to be more right than wrong, without giving the proper value to the numerous factors that might alter in our favor the hand's destiny.
Our algorithms act by a different and more sophisticated way: They collect the most number of actual shoe informations and they put them in relationship of a general probability ascertained after thousand and thousands of real shoes data.
It could happen that actual shoe results will substantially differ from "expected" outcomes, that's why we have increased the real betting parameters weight. After all it'll be way better to wait than hoping to be right at too confused situations.
Hoping for the best is the recreational players mantra, expecting the worst and playing the probabilities is the pros way to accumulate profits.
Let's see in a very simplified fashion what are our algos lines of operations.
1) Smaller is the number of bets made, greater will be the probability NOT to fall into the undetectable variance's realm.
It's not a coincidence that casinos want us to make a lot of bets, knowing very well that the probability to be right will esponentially decrease with the number of bets placed.
Notice that casinos will win a lot more money by exploiting players bad attitudes than by taking advantage of the HE, so mathematical issues take a minor role in that.
The math assumption why no matter how are diluted our bets the probability to win is always EV- belongs just to 2+2=5 losers.
Fortunately when a gambling game cannot be resolved by math it remains unbeatable.
2) Since the bac productions are asymmetrically produced whatever the reasons involved, selectively chasing the clustering effect of something will get more positive sequences in quantity and quality than expected by a perfect independent 50/50 proposition.
It's just a matter of time (and we should consider 'time' in a different way than casinos do).
3) Frequency and rhythm are both two decisive factors to take care of, actually casinos and mathematicians do care only about frequency not knowing a fk about rhythms of presentation.
4) Average sd values of certain pattern presentation and distribution.
If given random walks action applied to several thousands and thousands of shoes data provide 2.5 sigma negative deviation maximum levels, it means that the betting model is somewhat restrained in its negative fluctuations. On the other end the positive deviations counterpart had demonstrated to reach 3.5 or even 4 sigma values. A big edge, I guess.
5) Raising the probability of success facilitates the clustering/isolated pattern distribution.
Anyone reading my pages knows that it's a good idea to rely upon a 0.75 probability distribution as being more detectable than a mere 50/50 or so probability.
Actually there are times when a given losing bet entices the same losing side to be wagered again and situations when the simple random walks action suggests to bet a side independently of the previous hand's destiny.
Itlr the random walk action takes a primary role, yet when the first (losing) bet was made at Banker side, we have more reasons to bet again the Banker side for obvious reasons.
This is just the sole situation we might alter the random walk pace that we've instructed to consider outcomes as 50/50 placed.
6) More likely distributions
Whereas it's relatively likely to encounter consecutive clustered singles not belonging to the two category, it'll be slight less probable to encounter 2-3 or 3-4 lenght streaks not coming out clustered at least one time.
Exaggerating a bit and for the lovers of progressive plans, after two isolated 2-3 or 3-4 streak situations, a clustered 2-3 or 3-4 event will happen by degrees of probability well superior than what math dictates.
Of course the same progressive plan could be applied by a positive wagering "chasing" the clustered situations superior than two, relying upon the verified long term streaks propensity to form same or next to same lenght categories.
7) More likely events distribution
If we use a 0.75 probability to succeed, we'll get an expected W/L 3:1 ratio, but since any shoe is asymmetrically shaped such ratio will be disregarded several times along any shoe dealt. Say more often than not.
Thus we should discard from our plan (in a way or another) those ideal average ratios as being less probable than what an asymmetrical distribution will be capable to do.
The list is not over yet.
See you in a couple of days.
as.
Our algorithms act by a different and more sophisticated way: They collect the most number of actual shoe informations and they put them in relationship of a general probability ascertained after thousand and thousands of real shoes data.
It could happen that actual shoe results will substantially differ from "expected" outcomes, that's why we have increased the real betting parameters weight. After all it'll be way better to wait than hoping to be right at too confused situations.
Hoping for the best is the recreational players mantra, expecting the worst and playing the probabilities is the pros way to accumulate profits.
Let's see in a very simplified fashion what are our algos lines of operations.
1) Smaller is the number of bets made, greater will be the probability NOT to fall into the undetectable variance's realm.
It's not a coincidence that casinos want us to make a lot of bets, knowing very well that the probability to be right will esponentially decrease with the number of bets placed.
Notice that casinos will win a lot more money by exploiting players bad attitudes than by taking advantage of the HE, so mathematical issues take a minor role in that.
The math assumption why no matter how are diluted our bets the probability to win is always EV- belongs just to 2+2=5 losers.
Fortunately when a gambling game cannot be resolved by math it remains unbeatable.
2) Since the bac productions are asymmetrically produced whatever the reasons involved, selectively chasing the clustering effect of something will get more positive sequences in quantity and quality than expected by a perfect independent 50/50 proposition.
It's just a matter of time (and we should consider 'time' in a different way than casinos do).
3) Frequency and rhythm are both two decisive factors to take care of, actually casinos and mathematicians do care only about frequency not knowing a fk about rhythms of presentation.
4) Average sd values of certain pattern presentation and distribution.
If given random walks action applied to several thousands and thousands of shoes data provide 2.5 sigma negative deviation maximum levels, it means that the betting model is somewhat restrained in its negative fluctuations. On the other end the positive deviations counterpart had demonstrated to reach 3.5 or even 4 sigma values. A big edge, I guess.
5) Raising the probability of success facilitates the clustering/isolated pattern distribution.
Anyone reading my pages knows that it's a good idea to rely upon a 0.75 probability distribution as being more detectable than a mere 50/50 or so probability.
Actually there are times when a given losing bet entices the same losing side to be wagered again and situations when the simple random walks action suggests to bet a side independently of the previous hand's destiny.
Itlr the random walk action takes a primary role, yet when the first (losing) bet was made at Banker side, we have more reasons to bet again the Banker side for obvious reasons.
This is just the sole situation we might alter the random walk pace that we've instructed to consider outcomes as 50/50 placed.
6) More likely distributions
Whereas it's relatively likely to encounter consecutive clustered singles not belonging to the two category, it'll be slight less probable to encounter 2-3 or 3-4 lenght streaks not coming out clustered at least one time.
Exaggerating a bit and for the lovers of progressive plans, after two isolated 2-3 or 3-4 streak situations, a clustered 2-3 or 3-4 event will happen by degrees of probability well superior than what math dictates.
Of course the same progressive plan could be applied by a positive wagering "chasing" the clustered situations superior than two, relying upon the verified long term streaks propensity to form same or next to same lenght categories.
7) More likely events distribution
If we use a 0.75 probability to succeed, we'll get an expected W/L 3:1 ratio, but since any shoe is asymmetrically shaped such ratio will be disregarded several times along any shoe dealt. Say more often than not.
Thus we should discard from our plan (in a way or another) those ideal average ratios as being less probable than what an asymmetrical distribution will be capable to do.
The list is not over yet.
See you in a couple of days.
as.