If my math is right, one would expect an ace to flop 23% of the time when holding KK.
(46/50) * (45/49) * (44/48) X 100 = 77%; 100% - 77% = 23%
2 Likes
Elvoid you should believe what you see that the majority of the time the WORST hand of an all in wins. I canāt post enough of these to prove anything to you non-believers but this happens constantly. Total garbage the player should be punished for calling with 2 4 against JJ and Ace 9 but instead he gets rewarded.
I canāt figure it out it either it doesnāt happen to you guys over and over like it does me and wildpokerdude or it does and you just put your heads in the sand but on a random site you would not EXPECT IT TO HAPPEN thatās what me and wildpokerdude are saying. When I play poker in real life I do not expect it because itās truly RANDOM. What else needs to be said? Itās broken period.
In the same day me and wildpokerdude both called on the chat that we were going to lose the hands before it happened and it did. That would be completely impossible to predict in a live random card poker game.
And itās sad the fact like I donāt know who programs this crap but why canāt someone just say weāre going to bring it to their attention and let them look at it? But no itās perfect the way it is right me and wildpokerdude are idiots imaging things sore losers with our millions that weāve earned without buying chips move along people nothing to see here. Thatās what makes me think itās not actually broken but done this way intentionally which is truly just pathetic.
Those numbers donāt mean anything on Replay. Itās probably like 90%.
Yeah, probably. Why should anyone use math when they can just pull numbers out of thin air?
3 Likes
Youāre trying to apply math that would work in a live poker game to Replay. Theyāre not the same. So yes throw all the math you could possibly think of out here because it does not apply.
One canāt say something happens more than it should unless they know how often it should happen. If my math is right (and it might be) then we can use it as a baseline in case someone wants to actually collect some data.
1 Like
Iād love to hear your response to how me and wildpokerdude in the same day predicted being beat on the chat before it happened in the same day. Itās probably our negativity that caused the cards to fall the way they did right? 
My new philosophy on Replay is
If you donāt have it on the flop, fold youāre going to lose
If you do have it on the flop, fold youāre going to lose
I suspect you are both manifesting your bad luck by expecting it. In quantum physics, this is known as retro-causality. This basically means that your thoughts now can affect the shuffling that happened in the past. So yes, your negativity might be the reason.
Hey, you asked! 
3 Likes
Why? Because you say so? Seriously?
Iāve picked a narrow, easy to quantify, easy to count experiment that I will conduct over the next few weeks or even months. The numbers wonāt lie, theyāre just the numbers, and much like the legendary Honey Badger, numbers donāt give a ā ā ā ā . Theyāll say what they say, period. And Iāll believe them.
Iām in the process of collecting those numbers. And those numbers will mean far more than one or two dozen cherry picked hands. If I donāt like the numbers, I can live with it. How about you?
1 Like
All of these hands happened in your last 200 hands. Obviously you can win with 2 pairā
3 Likes
In this post, I provide a statistical analysis of my hole cards in the 7553 hands I have played during my 10,000 to 1,000,000 Bankroll Challenge to see if the observed frequencies of the 169 non-equivalent starting hands are consistent with a randomly shuffled deck.
Null hypothesis and result
The null hypothesis for this analysis is as follows:
The Replay shuffling algorithm generates a deck that follows a uniform distribution in the sense that each permutation of the 52 cards is equally likely.
I conduct a Pearsonās chi-squared test to see if the observed frequencies of the 169 non-equivalent starting hands are significantly different from the expected frequencies under this null hypothesis. The test finds that the null hypothesis cannot be rejected at the standard 5% significance level, i.e., the frequencies of my starting hands are consistent with a uniformly distributed shuffled deck.
Details below.
Combos
There are 1326 different starting hands (ācombosā) in Texas Holdāem. Under the null hypothesis, all 1326 starting hands are equally likely. If we just look at the ranks of our hole cards and whether or not they are suited or not but ignore the specific suits, we end up with 169 non-equivalent starting hands: 13 non-equivalent pairs, 78 non-equivalent offsuit starting hands, and 78 non-equivalent suited starting hands. There are 6 combos for each pair, 12 combos for each offsuit unpaired starting hand, and 4 combos of each suited starting hand. As consequence, the probability of being dealt
- a specific pair (e.g., AA) is 6/1326 = 0.45%,
- two specific offsuit hole cards (e.g., AKo) is 12/1326 = 0.90%,
- two specific suited hole cards (e.g., AKs) is 4/1326 = 0.30%.
Expected frequencies
My sample consists of 7553 hands, so to get the expected frequencies for all 169 non-equivalent starting hands, I just need to multiply the above probabilities by 7553. Thus, the expected frequency (number of times among the 7553 hands) of being dealt
- a specific pair (e.g., AA) is 34.2,
- two specific offsuit hole cards (e.g., AKo) is 68.4,
- two specific suited hole cards (e.g., AKs) is 22.8.
Observed frequencies
The following table shows the actual number of times each non-equivalent starting hand occurred in my sample.
Pearsonās chi-squared test
Pearsonās chi-squared test āis a statistical test applied to sets of categorical data to evaluate how likely it is that any observed difference between the sets arose by chanceā (Wikipedia). The main outcome of a statistical test is the p-value. To quote Wikipedia:
the p-value is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. A very small p-value means that such an extreme observed outcome would be very unlikely under the null hypothesis.
A null hypothesis is rejected if the p-value is smaller than some significance level chosen in advance of the test. Typical significance levels are 5% or 1%. Smaller values decrease the probability of erroneously rejecting the null hypothesis but increase the probability of erroneously not rejecting the null hypothesis.
For this analysis, I choose a standard 5% significance level.
Result
We have 169 non-equivalent starting hands as categories and I have reported the expected and observed frequencies for each category above. Applying the chi-squared test yields a p-value of 78.8%. This is (much) larger than the 5% significance level and thus we cannot reject the null hypothesis that the shuffling algorithm generates a uniformly distributed deck.
10 Likes
Between October and January, I collected all my pocket card data. In addition, I recorded the result of every hand I participated in - win (full house), bad beat, folded because of scary flop/turn/river, etc. But I also noted the result if Iād folded and went on to hit something. I intended to collect data indefinitely and achieve a huge data set, but in January I gave up playing for three and a half months and data collection didnāt resume once Iād hit the tables again because I couldnāt be bothered. In the end, Iād collected around 11,000 hands, which I felt was large enough.
I didnāt collect data because I thought the dealing was rigged, rather it was because I felt I get so much trash. There were times (and there still are times) when I will go 1,000 games in a row and get 99% total garbage - every single hand is 7/2, 8/2, 9/2, 10/2, etc.
However, while I wasnāt interested in whether or not the site is or isnāt rigged, one conclusion I did end up drawing was that the dealing was clearly consistent with that of a random card dealer. Moreover, trash hands dealt were, actually, in proportion. 75% of hands were folded pre-flop, which is the exact number I would expect - because the chance of a trash hand is pretty much 75%. Very much to my surprise, the hand dealt the most often was off-suit ace/queen.
Other observations: (1) Suited hands % total hands were exactly what we would expect. (2) Each card ranking was dealt a very similar number of times. (3) Pairs % total hands were what we would expect. (4) A pair flopped a set a more or less expected number of times. I concluded that it is impossible for a non-random card dealer to produce results that appear random. Moreover, (5) the chance of a bad beat (losing to quads, losing to higher full house, nut flush losing to full house) was very remote - generally, if I made it to showdown, the chance of winning was around 80%. (6) Pocket aces is by far the most favorable hand - the chance of winning with aces was 90%, even though they rarely improve. Aces getting cracked can usually be avoided by folding if the community cards are unfavourable (typically, if they produce a straight or a flush for another player - itās usually obvious whatās going on, so folding is easy). Aces do, however, get cracked in a multi-way all-in scenario, in which case, folding may well be the best option here (although I never do that). Again, the results are very much in line with expectations. Finally, (7) trash hands almost never hit anything, as we would expect.
Lastly, thereās Ockhamās Razor. Given the choice between a simple explanation and convoluted explanation, a reasonable person accepts the simple explanation. A random card dealer will be very simple to create, while a highly intelligent, convoluted card dealer, which discriminates against particular players for no apparent reason, must have required quite a bit of research and development.
I canāt accept that card dealing is non-random for any of those reasons. None of this is to say that I donāt completely lose my sanity playing this game.
4 Likes
Well, now youāve done it. Your research has probably broken the thread!
Good job.
2 Likes
lol trash hands are king on here
1 Like
One personās trash is another personās treasure 
3 Likes
Haha, I doubt it, but if my post really helped ending this discussion, Iāll consider putting it on my CV 
4 Likes
In any kind of world of reason, your post would have been the nail in the coffin for this discussion.
Alasā¦ this isnāt a world of reason and weāre all out of nails.
3 Likes
So, youāre trying to refute his opinion with facts? That never works with people that canāt accept facts, because they donāt let facts get in the way of their opinions.
3 Likes
I only remember playing with you 1 time, a small SnG just the other day. In my last hand, I shoved my last 4BB with something like 5-6, and you called. There was a pair on the flop, I turned 2 pair, putting me in the lead, and the board paired again on the river, giving you the hand.
I was paying attention, and you won on the river 2 other times. I think your opponents sucked out on you once. Your made hands mostly stood up and won.
So my only question to you would beā¦ what the hell are you talking about?
4 Likes
I got so bored today that I actually started to read this topic for the first time.