oh let me let me

Assuming you don't hold either card (making the set) the odds of a pair on the board are just short of 50/50 by the river. 49%, I believe.

Variance of +/-25% (8/12) over such a tiny sample size is a snore.

Oh wait, sorry - online poker is rigged!

No, the chance the board pairs at all without regard for your cards, is 49%. But after looking at your own cards, the chance the board pairs in a rank you do not hold is 51%.

And the chance this happens in at least 8 of your next 12 hands (assuming showdowns) is 21%. But the chance it happens in at least 8 of some 12 hand streak during your next 1000 hands is essentially 100%.

Lol, please go. Don't bring this crap on Canada.

I guess we have to get clarification of the question. To me " How often do you think the board should have a pair on it, just out of interest?" means "without regards to players hands".

I was just assuming the guy wouldn't have complained about his 8 out of 12 if he hit some of them.

Well still - if we're talking about having our hands make a pair sometime before the river - its about 42%.

http://en.wikipedia.org/wiki/Poker_p..._hold_%27em%29

8/12 is 66% - which over a sample of 12 hands is still well within tolerance.

Come back when you have a sample over 1200 hands.

No, you've misread it. That's for exactly one pair. You also have to count trips, two pair, full house, and quads, all of which include a paired board. You also looked at 7 card hands, but the pertinent number is for 5 card hands to know the chance for the board. My numbers were accurate (as was your very first post).

I feel like I'm shooting at a moving target here.

Here's an analysis of 1 million hands on the Bodog network, just for you:
Online Poker Watchdog

% are worthless when debating about whether or not if online poker is rigged imo cuz obviously statistically speaking that will always even up over a large sample, im more intrested to see EV in terms of chips, cuz i dont care if the odds met i want to have a positive chip gain at the end, obviously for cash gamer makes no dif but for MTT/SNG players it does especially for MTTers, i can check a large sample size for lets say KK, and can show im winning 73% of the times with that but running 10 millions chips below EV, that been said, i want to see statistical prove of this from those ensuring online poker its NOT rigged

Broadly speaking, stuff happens some of the time. The rest of the time, it is other stuff that's happening.

You make a good argument, pokerwhiz.

Yeah - I want to see statistical prove from you shills, too. If you don't post it, I think we can all agree, and put this thread to bed, that will be proof certain that it is rigged in a way that can only be detected by a very few people who all happen not to keep any sort of data.

Obviously. People in Hell want ice water.

I wanna slowplay the nuts on the flop and still win the hand...

You're an idiot.

I would post links to the countless essays from experts in logic explaining why the concept of "proving a negative" is a null concept, but I suspect you would reject those out of hand because they don't align with the perspective you must maintain in order to avoid admitting the possibility that maybe you're just a bad poker player.

Surprised it sparked so much of a debate but 49% is what I got too... just thought it was amusing that someone would post 'OMG it happened 8/12 times' as if that was even remotely interesting or unusual

FYP for more impact.

Hi tompakee.

you should admitch yer shichwayshun...

Ty, now go to ur mom´s basement and do laundry
Intresting comment for a site admin or whatever but the thread isnt about me
so pls stop with the reverse psicology bs and yes, it def takes skill for ur pocket pair to hold vs Ax hand, winning flips on crucial late stages pots and/or just avoid getting coolered on a FT
Maybe ur right, ty for taking a time to write a respectfull, genuine and honest comment

. Fyp

It's a logical fallacy that is often misapplied to statements which are actually positive proofs that have been inverted.

Proving a negative doesn't just mean any negative. It means proving the non-existence of something.

Proving the circle cannot be squared isn't a negative. It's DISPROVING the assertion that a circle CAN be squared.

Can a circle be squared? No. Is that proven? Yes.

Proving a negative is along these lines: "There is an invisible purple dragon that fills the entire sky all the around the world in all directions, but it's incorporeal so we cannot actually detect it by any physical means. You cannot prove it's not true, therefore it must be true (or at least possible)."

Yes, I studied metaphysics, epistemology and symbolic logic.

I will disagree that it's impossible to "prove" that sites aren't rigged. However, I put rigged in quotation marks because a basis of all statistics is that you can't really prove anything. You can say that the null hypothesis is "rejected," but any form of rejection will have some sort of Type I error.

For example, something like beta blockers has dozens of studies rejecting the null hypothesis of beta blockers not preventing heart disease. All of these studies' data can be put together for a meta-analysis, where the number of sample points go up to many times what a single survey alone could do. The p-value can go down to an extremely minuscule amount, which means that it is very, very unlikely that beta blockers just happened to be lucky. But there is still some extremely minute chance that the experimental group in all of these studies just happened to have better outcomes by dumb luck.

Statistically speaking, there are ways to set up hypothesis tests that two things are equal. Usually the null hypothesis is that two things are equal and you want to prove one is greater than the other. In the case of "proving" non-riggieness, the hypothesis tests are switched. One can show that, say, the chance of each two card hand is very close, say within 0.01%, to their expected value with millions of hands. One test can be done for the RNG's probability being greater than 0.005% less than the expected value and another test for the RNG's probability being less than 0.005% greater than the expected value.

Flops, turns and rivers have an added complication that the hands need to be better quality than average for a hand to actually see a flop, turn and river. On the river, for example, Aces are a good bit less likely than one would expect because if hands get to the river, it's likely one or more Aces are in the hole cards. Still, some extensive tests can be done for "action" flops.

Many riggies have more or less admitted that these tests over millions of hands do conclusively prove an accurate distribution, and so they then give some sort of "equalization" nonsense. It's really hard to make sense of the equalization theory because of the zero-sum nature of hands. Let's say an eeeeevil poker site has a rig to boomswitch new donk players at the expense of long-playing regs. The regs will keep depositing while the donks will just give up if they go broke right away, or they may think they are the next Stu Ungar due to their boomswitch, or whatever. The regs now have a continuous disadvantage against new donks on their boomswitch, through say, getting Kings vs. Aces or set over set or getting sucked out on, and so on. But how wouldn't this be statistically detectable through looking at ONLY the hand history of the long-playing reg? How could the suckouts he suffers personally "equalize" out? The reg could similarly suck out against other regs, but then how wouldn't those other regs detect something amiss statistically? It makes no sense.

Now, for the diehard riggie which just won't listen to evidence, there is still the extremely minute possibility that all these statistical tests for randomness were passed by pure dumb luck. That's equivalent to the experimental group for Beta blockers always happening to have less heart disease and beta blockers don't actually do anything. But the p-values we are talking about here, for a meta-analysis or analysis of millions of hands, are on the order of 0.00000001%. You have to put aside biases at a certain point that "the boomswitch is obvious" and see overwhelming evidence that you're wrong.