Quote: Originally posted by JADELottery on Jul 4, 2015
We're reposting your reply from the topic How to simulate a distribution and use the lottery's own randomness against itself since this is the relevant topic.
We will get back to this a little later.
We are testing and finalizing a =DisimulateNexus(Numbers, Distribution, N1, N2) function for the other topic.
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Hello, Jade
You have made a great statistical work.
But the question is: what is this for?
Can you build a predictive algorithm from this knowledge?
Here's an example:
Take the Megaball, once again.
If the common player bet 1 number he will get 0.0666 hits per draw (1/15 = 0.0666). This is the REFERENCE or the so called Theoretical Average (TA).
My question is: using this system (3 sums) how many hits can you achieve per draw?
If after 100 samples, for example, you get 0.0666 hits a draw, then there is no advantage to follow it;
If you get a higher value means you can beat the TA so, in this case you are predicting;
finally, If you get a lower value you are also predicting because, in this case, you may bet against the algorithm.
However, I fear it is not possible to predict using this knowledge because there is a synchronizing problem, I mean, although similarities in simulated and real patterns, you need to synchronize your model with the reality of the game.
Several years ago when I started to develop predictive algorithms I lost a few hours or even days (I can`t remember exactly) with part of this same exercise you did and I quickly came to dead ends. However, you went a little bit further introducing simulated information.
But, I insist: is that enough to beat the odds, i.e. to get more than 0,0666 matches per drawing? If so, the system works.
But let`s see some obvious problems present in the 3 sums technique.
If the first 2 numbers of the sum are 1 + 1 + ... = 24 and knowing that the ideal sum of Megaball is 24, it means that the third number would be 22. Now, the ball 22 does not exist!!!
In the case of the first 2 numbers are 15+13+…= 24 the third number would be -4. However, Megaball does not contain negative numbers. Therefore, a brief review finds that there are dozens of black cases where the system does not work, because there are no enough numbers.
But the real problem is to construct predictive algorithms based on Euclidian maths when the reality is fractal. We can not fight fractal maths with Euclidian ou Gaussian maths. That is the reason why is so difficult to predict...
That is like fighting a war tank with a plastic revolver.
Regards
RENTAP
