Is like the ocean with waves, beautiful ...

Here can you see one complete cycle fail during 300 trails.
So if your selection would be five then you would pass this 300 trails and winning them all.

Now a march or algorithm like this capture current random states of the random flow, does can you use to pin point out winning bets and not play them all.
Like this, bet once after one loss with each state ... WWWLW LL WLWWWWWWWW

There is many options when you use cycle methodology ....

1
1 L
2 W
2 L
1 W
1 L
2 W
1 W
2 W
2 L
2 L
1 W
2 W
2 L
1 W
2 W
2 L
2 L
2 L

2
2 L
1 W
1 L
2 W
1 W
1 L
1 L
1 L

2
1 W
1 L
2 W
2 L
1 W
1 L
1 L
2 W
1 W
1 L
2 W
1 W
2 W
1 W
1 L
2 W
2 L
2 L
1 W
2 W
2 L
1 W
1 L
2 W
2 L
1 W
1 L
2 W
2 L
1 W
2 W
2 L
2 L
2 L

2
1 W
1 L
1 L
2 W
1 W
2 W
2 L
2 L
2 L

2
2 L
2 L
2 L

1
1 L
2 W
1 W
2 W
1 W
2 W
2 L
1 W
1 L
2 W
1 W
2 W
2 L
2 L
1 W
1 L
1 L
1 L

2
1 W
2 W
2 L
2 L
1 W
2 W
2 L
1 W
2 W
1 W
1 W
1 L
2 W
2 L
1 W
2 W
2 L
1 W
1 L
1 L
1 L

1
2 W
1 W
1 L
2 W
1 W
1 L
2 W
2 L
2 L
2 L

2
2 L
1 W
1 L
1 L
2 W
1 W
1 L
1 L
1 L

1
2 W
1 W
1 L
2 W
2 L
2 L
1 W
2 W
2 L
1 W
2 W
2 L
2 L
2 L

2
1 W
2 W
1 W
2 W
2 L
1 W
1 L
1 L
2 W
2 L
2 L
1 W
1 L
1 L
2 W
1 W
2 W
1 W
1 L
1 L
2 W
1 W
2 W
2 L
1 W
1 L
1 L
2 W
1 W
1 L
2 W
1 W
2 W
2 L
2 L
2 L

2
1 W
1 L
2 W
2 L
1 W
2 W
2 L
1 W
2 W
1 W
1 L
1 L
2 W
1 W
2 W
1 W
2 W
2 L
1 W
2 W
2 L
2 L
2 L

2
1 W
2 W
2 L
1 W
1 L
1 L
2 W
2 L
1 W
1 L
1 L
2 W
1 W
2 W
1 W
1 L
2 W
1 W
1 L
2 W
1 W
1 L
2 W
1 W
2 W
1 W
2 W
2 L
1 W
2 W
1 W
2 W
1 W
1 L
1 L
2 W
1 W
2 W
1 W
2 W
2 L
1 W
2 W
1 W
2 W
2 L
2 L
1 W
1 L
1 L
2 W
2 L
1 W
2 W
2 L
1 W
2 W
2 L
1 W
2 W
2 L
1 W
1 L
1 L
2 W
2 L
1 W
2 W
2 L
1 W
1 L
1 L
1 L

1
2 W
1 W
1 L
2 W
2 L
1 W
2 W
2 L
1 W
2 W

Quote from: GreatGrampa on June 17, 2013, 01:42:34 PM
Thought so!  with respect to staking plan, it might be possible that cyclic betting suits this better, as we are using fixed cycles of 5 bets.

But cycle betting is predetermined based upon math and probability.
Lets take a dice with four sides and clustering them into even money, then we get four patterns.

1.RR
2.BB
3.RB
4.BR

Then if you get five reds in a row you have this situation.

1.RR
2.RX
3.RX
4.RX

Then you can see the clustering that you would bet that not red would come for three attempts.
Then if it does then you have four sides of the same and the same situation of a dice repeating one side four times in a row.

That is one cycle and you place three bets if the trigger is five and that is the correct methodology.
Now if you would bet six times, then the probability would be as follows ...

You see red you bet black for three times.
If you see black you bet red for three times.

Now if you lose you have one color four times in a row.

R
R
R
R

or

B
B
B
B

Then you wait for the next result to show with out betting, as that will show what clustering pattern you will get or what side out of four possibilities will show, clustering pattern.

If you get RB then you bet against that cycle.
If you get RR then you bet against that cycle.
If you get BR then you bet against that cycle.
If you get BB then you bet against that cycle.

I post this as cycle methodology follow strict rules and math/probability.

RB
RB
RB
RB

RR
RR
RR
RR

BB
BB
BB
BB

BR
BR
BR
BR

Pretty good LW-Registry ... i test this with Marigny style and regression toward the mean and also get pretty good results.

LWWLWLWWWWLWWLWLLLWLWWWWLWLWWLWLLWWWWLW

Largers series vs singles and largest drawdown three loses ...
Sure you can use same staking plan ...

Feels better using random states of property that indicate current states ... when you aim to catch events ...
Looks like it is more solid then his method, as my playing model is based upon math and probability towards tendency play.

 
PDA why do you continue if you lose your money, i would not continue doing what i am doing if i was losing money.

 
Each LW-Registry sequence is one current property state.
It up to you to develop a march or algorithm to catch larger series or choppy flow.
Now you have the math (STD) and the probability for trending.
And with a practical charting method in real casino environment.

1
1 L
1 L
1
1
2
2 L
1 W
1 L
2 W
2 L
2 L
1
1 L
2 W
1 W
2 W
2 L
2 L
1
2 W
1 W
2 W
1 W
1 L
2 W
2 L
1 W
2 W
2 L
2 L
2
1
2 W
2 L
1 W
2 W
1 W
1 L
1 L
2
2 L
1 W
2 W
2 L
1 W
1 L
1 L
2
2 L
1 W
1 L
2 W
1 W
2 W
2 L
2 L
1
1 L
2 W
1 W
2 W
2 L
1 W
2 W
1 W
2 W
1 W
2 W
1 W
2 W
2 L
1 W
2 W
1 W
2 W
2 L
2 L
2
1
1 L
1 L
2
1 W
1 L
2 W
1 W
1 L
2 W
1 W
2 W
2 L
1 W
1 L
1 L
1
1
2
2 L
1 W
2 W
1 W
2 W
1 W
2 W
2 L
1 W
2 W
2 L
2 L
2
2
1
1 L
1 L
2
1 W
1 L
1 L
2
2 L
2 L
1
1 L
1 L
2
2 L
1 W
2 W
2 L
1 W
2 W
2 L
1 W
2 W
2 L
2 L
2
1
2 W
2 L
2 L
2
2
1
1 L
1 L
2
1 W
1 L
1 L
2
1 W
1 L
2 W
2 L
1 W
1 L
1 L
1
2
1 W
2 W
1 W
2 W
2 L
1 W
2 W
2 L
2 L
2
1
2 W
2 L
1 W
1 L
1 L
2
1 W
2 W
1 W
1 L
2 W
1 W
2 W
1 W
1 L
1 L
2
1 W
2 W
1 W
1 L
2 W
2 L
1 W
1 L
2 W
2 L
1 W
1 L
1 L
1
2
2 L
2 L
1
2 W
2 L
2 L
2
2
2
2
2
1
2 W
1 W
1 L
1 L
1
1
2
1 W
2 W
2 L
2 L
2
1
1 L
1 L
1
1
1
1
2
2 L
1 W
2 W
1 W
1 L
2 W
1 W
1 L
1 L
1
2
2 L
2 L
1
2 W
1 W
1 L
2 W
2 L
1 W
2 W
2 L
1 W
1 L
1 L
1
1
2
2 L
2 L
1
2 W
1 W
2 W
2 L
2 L
1
1 L
2 W
1 W
2 W
2 L
2 L
1
1 L
1 L
2
2 L
1 W
1 L
2 W
1 W
2 W
1 W
2 W
2 L
1 W
2 W
2 L
1 W
2 W
2 L
1 W
2 W

 
Here you can see how table at average overall random flow is choppy and rare events is double loses triggers LL ...
Double loses LL is only intresting if you have allot of singles and series of two present with you property state hitting around 2,5 to 3.0 STD.
Works also with other window selections if you stick to them when trending.

The other way around is that you see wins follow by wins at least twice or many more times in a row with out double loses LL and after each double loses.
That is a overall natural random flow as the singles and series of two is dominating by nature.

 
The charting algorithm is very easy, you can use the LW-Registry ...
So you charting red and black as they come and next to them you write a win if you get a single and a lose if you get a series.

Then when you get a choppy table you will get singles and series of two and the LW-Registry will look like this ... LWWWWLWLWLWLWWWWLWLWWWWLWWLWLWLWLW
You get wins and maximum one loss.

When the table current state produce larger series then you will get two loses LL that indicate larger series are present ... WLWLL WLL WLL WLL LL LL LL WLL WLL LL
Then you pick to play once after a win when you aim for choppy table and attack after two loses when you aim for larger series.

Easy way to visual following the random states and add STD into your calculations when trending.

Current state property.
Is random window selections with overrepresented events.
Withe swans.

The black swan is the negative expectation.
I know its shape and will describe it.

Playing model:
Singles contra larger series.
Larger series contra singles.

Example, we can select window selection of singles and series of two hitting 2, 3 to 4 STD.
We can use raw calculation in head to estimate the strength with our current state property, window selection, the random property flow.d will describe it.

So if i have 12 singles and two series of three, then i have 2.5 STD
Then if i have 6 singles and one series of three i have around 1.2 STD

All we need is the common benchmark to estimate the value.
Then we can set rules for how small or large we will allow our selections to be.
As in 16 events up to 25 or even 50 events.

Now other bench mark is 3.0 STD that equals 14 singles and two series of three.
You just make up a chart with common values and divide.

The values is:

Singles has the value of 1
Series of two has the value of 0
Series of three has the value of 1
Series of four has the value of 2
Series of five has the value of 3
Series of six has the value of 4
Series of seven has the value of 5
And so it continues ...

Example, i see series of 3,4,5,6,7 to chop with one or two singles, then i have hit 2.5 or 3.0 STD.
Then i know tiny, small, middle, large property states with singles and series of two will show.

Example, i see singles and series of two to chop with one or two series, then i have hit 2.5 or 3.0 STD.
Then i know tiny, small, middle, large property states with larger series will show.

Example, i see both does two current property states, then the values cancel each other out hovering at zero point, one option is to define that as erratic random balance, or chaotic property state where there is no existing imbalance.

This way you can read the random flow, distribution like a open book.
We know that there is three current property states.

We can get imbalance towards two directions based upon this playing model.
And we can hovering around the mean or we can see the current property state as erratic random flow that behave chaotic.

This is the withe swans.
We can understand them as events and current property states, window of selections.

We need to define length and strength of the current property state we will measuring.
For that we have STD.
So that explains the math.

Now to the probability aspect and the black swan, the negative expectation.
First i will just say this is trending on the highest existing level.

When you have a current property state hitting for example 3.0 STD during 16 to 30 events.
Then you have isolated the window selection around 25 to 50 trails.
For example with singles and series of two.

Now the bell curve has no limit and it can continue to grow or fall back to back.
But that is not the black swan or any issue, as we would not play.

We would only aim to play when there is an existing change, tendency towards tiny, small, middle, large correction, present change.
We know that with this example, that does will come for the next 20 40 100 150 trails/events.

Is like having a crustal ball that say you know what is coming, but you don't know when.
So we wait until they do.
Then we hit.

Now the black swan is as follows.
If you get tendency in perfect order with out any existing imbalance after a current property state with overrepresented events.

This means that if we throw a dice six times (one cycle) and each side would show once in numerical order.
123456

As the march or algorithm is develop to catch the underrepresented events.
So are they mechanical tools with limitation.

One march is that you wait for one larger series to show.
Then you attack after series of two show, up to three times.
That is one attack sequence.

The existing algorithms and marches are effective.
As the probability is on your side and does underrepresented events chops with out coming in numerical order.

Very nice topic ...
I just love it when you explain in details and add screen-shots to describe a complete idea.

Nice work.

geoff365 i recognize you from Vip Lounge, you are a real old-timer :-)

Can you give more details about how one position is more frequent then others.
Post a screen-shot would be good.

Thanks

At GG there was a competition about different systems.
A coder code 10 different systems, one of them was made by Izak and it came second place.

Just mention it as i remember it now.

I know that, but still don't see the point not using random org, the slight difference between P and B is so tiny so your system or any existing strategy will not notice, if you don't just play B ... just silly, my opinion.

 
Can some one explain for me why you need 1000 zumma.
Silly if you ask me, when you have random org, my opinion.
You beat random org you beat any zumma Collection or real baccarat game, simple as that.