## Poll

1 vote (3.57%) | |||

2 votes (7.14%) | |||

3 votes (10.71%) | |||

4 votes (14.28%) | |||

2 votes (7.14%) | |||

6 votes (21.42%) | |||

5 votes (17.85%) | |||

1 vote (3.57%) | |||

15 votes (53.57%) | |||

3 votes (10.71%) |

**28 members have voted**

Quote:WizardNo! The numbers with bombs have a much greater chance of being drawn by the 20-ball draw of the game. I would agree that if you tracked balls numbers drawn, they would probably be equal, because they randomize where the bombs are put. If the player could choose the bomb locations, for example 1 to 3, then 1 to 3 would be hit more than 20/80 of the time each.

That assumes that the bomb locations are selected before the numbers are drawn. I have a feeling it is the other way around. Among other things, it makes it a lot easier to control how many bombs are hit.

Quote:ThatDonGuyThat assumes that the bomb locations are selected before the numbers are drawn. I have a feeling it is the other way around. Among other things, it makes it a lot easier to control how many bombs are hit.

I think you are right, but the game doesn’t display it that way. I think the game draws the 20 random balls and then decides where to put the bombs in order to have them hit. Either way, it’s deceptive.

May as well randomly display 0-3 bombs off the grid, then nobody would expect anything.

https://www.pacodeandbulletin.gov/Display/pacode?file=/secure/pacode/data/058/chapter810/s810.5.html

Quote:(d) The scaling method may not compromise the cryptographic strength of the random number generator. The scaling method must preserve the distribution of the scaled values. For example, if a 32-bit random number generator with a range of the set of integers in the closed interval [0, 232-1] were to be scaled to the range of the set of integers in the closed interval [1, 6] so that the scaled values can be used to simulate the roll of a standard six-sided die, then each integer in the scaled range should theoretically appear with equal frequency. In the example given, if the theoretical frequency for each value is not equal, then the scaling method is considered to have a bias. Thus, a compliant scaling method must have bias equal to zero.

also - this process isnt necessarily UNFAIR right?

because thats what were essentially worried about when weve created these laws

but this process somehow increases the players advantage?

which isnt necessarily unfair?

or since its NOT random it IS unfair?

Quote:CrystalMathI think you are right, but the game doesn’t display it that way. I think the game draws the 20 random balls and then decides where to put the bombs in order to have them hit. Either way, it’s deceptive.

I agree.

Quote:heatmapPennsylvania's Law which pertains to what were talking about - at least i think this is what were talking about algorithmically - maybe not though

That is not what we're talking about.

Direct: https://www.youtube.com/watch?v=pNIU6JyYCNQ

For those who couldn't stand my sample size of 55 before, despite being overwhelmingly conclusive, I am now up to 263 games played and recorded. Here are the updated totals.

Bombs | Obervations | Expected |
---|---|---|

3 | 37 | 3.65 |

2 | 38 | 36.49 |

1 | 34 | 113.32 |

0 | 154 | 109.54 |

Total | 263 | 263.00 |

A chi-squared test shows the probability of results this skewed or more are 1 in 958,700,425,938,185,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000. Is more data required?

.Quote:WizardHere is my video documenting my case that Keno Exposion is gaffed and a violation of NRS 14.050.5 .

.

Direct: https://www.youtube.com/watch?v=pNIU6JyYCNQ

For those who couldn't stand my sample size of 55 before, despite being overwhelmingly conclusive, I am now up to 263 games played and recorded. Here are the updated totals.

Bombs Obervations Expected 3 37 3.65 2 38 36.49 1 34 113.32 0 154 109.54 Total 263 263.00

A chi-squared test shows the probability of results this skewed or more are 1 in 958,700,425,938,185,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000. Is more data required?

I forget how exactly YOU define gaffed. If it as simple as ‘the outcomes don’t match what the actual physical game would be’ then you have proven it is gaffed. If you include in the definition somehow that the win percentage is changed you have NOT proven that. In the 263 games the TOTAL expected number of bombs seems about on expectation, just more ‘extremes’ (0 or 3)

Quote:SOOPOOI forget how exactly YOU define gaffed. If it as simple as ‘the outcomes don’t match what the actual physical game would be’ then you have proven it is gaffed. If you include in the definition somehow that the win percentage is changed you have NOT proven that. In the 263 games the TOTAL expected number of bombs seems about on expectation, just more ‘extremes’ (0 or 3)

I could prove that, but I'm afraid it would muddy the waters. If I programmed this game, assuming no gaffe, it would show a return of of about 80%, when in fact it is probably about 90%. Part of the reason is there are 12% more bombs hit than expected. Another his the bombs hit tend to be clumped in the same game. It would be better to play one game with 22 balls drawn and one with 20 than two with 21.