Thanks for including ggdice there. It's suprising that it has more than my own vote considering the current tiny bankroll.

https://bitcointalk.org/index.php?topic=263522.0

"easy money"

Lowering the invested amount reduces risk and reward at the same time.  It doesn't change the risk/reward ratio.

Changing the max bet policy might reduce the risk a lot, while lowering the reward a little.  In other words, it might make the risk/reward ratio more favorable.

The results we've seen aren't statistically probable - in that they aren't a likely outcome.  But what valid math I've seen indicates that they aren't so unlikely as to suggest a problem.  If something has a 1 in 10 or 1 in 20 chance of happening then is there a problem if it happens?  Is it (your phrase) "statistically probable"?

If there is a problem then, ignoring server compromise/dooglus cheating, then the obvious issue would be if the RNG had a (even small) flaw in it.  For example if the odds of a high number after 2 low rolls was different than the odds of a high number after 2 high rolls.  Any flaw such as that could potentially make an otherwise normal (i.e. losing) strategy into a winning one (one with a positive expectation) - either through blind luck or as the result of careful analysis.

You are correct. But the problem is much much deeper than this. Let me begin by asking the simple question; since the KC maximizes profit over number of bets, and since variance decreases with bet size, how many max bets would we need to make in order to decrease variance to get, say, 0.9% < profit < 1.1% assuming all bets were max bets? Going with a set max bet size, say 500 BTC, guarantees we will find a sample size more than sufficient to limit profit in this way. Let's further simplify by going after the RNG and not the house edge.

So now we have simplified the problem into determining how many coin flips we need to make to show whether or not a coin is fair. Which is actually a well known problem. If we calculate this number, and determine that actually, just-dice has "flipped the coin" more times, we have then proven that just-dice is not a fair coin. It does not matter that we are not using the actual formulas for just-dice's statistics; our results are a superset of theirs. In short, if just-dice's numbers are within the sample size we require it may or may not be fair (we won't know) but if their numbers lie outside of ours we have proven that they are unfair. This proves using actual just-dice statistical formulas will merely create numbers x and y such that our figures bracket them as such; 0.9% < x < profit < y < 1.1%.

I'll even draw a picture. We will end up with a number (sample size) which will appear in one of the following places: A, B or C:
   

If our number shows up as A or B, we will not know which one it is (since we are calculating a simplified version of the statistics). In the case of A and B all we know is that just dice has not yet achieved the sample size we require to limit profit to 0.9% < profit < 1.1%. If, however, just dice has a sample size which falls at (C) -- which is greater than what we require -- we have guaranteed that profit should be limited to 0.9% < profit < 1.1%.

The formula for required sample size is (Z*Z)/(4*E*E), where E is the desired error (ex. 0.01 for 1%) and Z is how many standard deviations you want. 3 standard deviations gives a 99.7% level of confidence, which is less frequently broken than 1/300. A quick glance at a chart which shows how likely you are to die from various causes shows that it is far more probable that you will die by falling down (1:246) if you don't first die from committing suicide (1:121).

n = (3 * 3 ) / (4 * 0.01 * 0.01)
n = 9 / 0.0004
n = 22,500

In short, as long as we bet 500 bitcoins 22,500 times, we are guaranteed that the error will be no more than 1%. But the house edge is 1%, so this just states profit will be between 0% and 2%. (house edge +/- 1% is 0% to 2%.). That doesn't help us.

To get +/- 0.1%  or 0.9% < profit < 1.1%, we need to set E to be 0.001 not 0.01:

n = (3 * 3 ) / (4 * 0.001 * 0.001)
n = 9 / 0.000004
n = 2,250,000

There we go. How convenient. As you can see, we have just rolled over 2.4 million bets at 500 max bet. Therefore we arrive at the following connundrum:

1. 2,250,000 bets at 500 BTC is enough to guarantee variance within 0.9% < profit < 1.1%.
2. Actual sample size is a minimum of 2,400,000 because not all bets were made at max kelly bet.
3. Actual site profit is less than 0.2%.

0.2% < 0.9% < profit < 1.1%

This is a serious problem.

I am not merely suggesting something is wrong, I am proving it.

If Dooglus is interested in hiring me as a consultant I will help him fix this problem. Then again, the solution is obvious, but I think Dooglus needs someone to tell him. And no I will not advise anyone for free. You get what you pay for in life. That does not mean I am greedy it means I want Dooglus to listen to me, pay attention to what I say, and do it, or I will not waste my time. If he cannot value my advice then it has no value to him. It's that simple. That being said my rates are exceedingly cheap.

Chat soon~

Then simply multi-accounting would bypass the limit.

@usagi

That being said my rates are exceedingly cheap.

what is cheap? as I want to open an online casino I would be interested in Your opinion. I know what is wrong with JD. lets say I think I know and as I want to be sure I really would be interested in Your opinion. so how much  

cheers

Are withdrawals being processed?

Another completely new member making a clone dice site with the offer to invest.

DEAL WITH THOROUGH CAUTION.

Franchising was not conceived to avoid having 51%. That's not the point of it.

Don't discount insider trading possibilities.  You'd think gen2 would be announced by now but they may be delaying the announcement while scooping up cheaper shares.

My IP was just blocked for an hour - anyone know why?

I totally agree with that. At this point is better to sell all hardware. Take all the money now and start reinvesting in gen2, also they will probably get more profit than just mining.

The question is how fast are they going to start selling/mining with gen2, because the first takes all the market.

The Kelly Criterion derives from a model that differs from JD's real situation in a couple of important ways.

First, in the Kelly model, the player with the edge controls the betting.  Since he has an edge, he keeps on betting.  In contrast, with JD the house has the edge but must wait passively for the whales to bet.  Since the whales don't have an edge, they can and should stop when they're ahead.

Second, the Kelly model runs on "bet time", where the unit of time is one bet.  The Kelly Criterion maximizes the return over the number of bets.  In contrast, JD runs on "calendar time".  Investors count their return in percent per day or month or year, and count their opportunity cost the same way.

Because of these differences, it does not follow that setting the maximum bet based on the Kelly Criterion will maximize JD's return in calendar time. 

The maximum bet policy has been questioned before, and it's always been answered by an appeal to the Kelly Criterion, or to simulations based on the Kelly model.  I'm suggesting that the model doesn't match the reality, so it's time for a fresh look.