Do you seriously play $30-$60 and have no concept of how large a hand sample size is required to be meaningful? 20k? No disrespect, but that’s laughable..Top cash game players play hundreds of thousands of hands per year and breakeven/downswings over 100k hands are not that uncommon.

Justin wrote:” Incidentally, I am not a ‘losing player’ I have a 32% ROI and profit well in online poker.”

A 32% roi at what exactly and over what sample size? You must be a sit n go superstar with that roi.Screen name or gtfo ( as dem nasty 2+2′ers would say).

Stevie T wrote:
“Answer me this. Why is it every site that tries to disbarge the theory that online poker rooms are rigged all have ads by those very poker rooms”

I nearly left my blog addy on this comment but I have a ‘Stars ad up and someone might hack my email account and find the evidence! Here’s a snippet of the incriminating email: ” Dear Poker Blogger on Special Rigged Boomswitch Account,we would very much like to place an ad with you …”

Seriously, any winning poker player knows they will go through mind numbing downswings and long runs of cards which seem almost unnatural and surreal.If you’re a winning player with mental toughness you ride it out and remember that every new hand is exactly that and not related to any previous play.

Anyway, I’d also like to take my hat off to Bill for continuing to reply with grace and good humour to the “poker is rigged” crowd.Gl at the tables…

1) 50,000+ hands within a week after cashing out vs. 50,000+ hands for a player who has not cashed out in over a year
2) 50,000+ hands for a specific player within a minute after having typed in chat at the table vs 50,000+ hands for that same player after not having chatted at all in that particular session.
3) 50,000+ hands in heads up situations in which the aggressor is the underdog in each hand vs. 50,000+ hands in which the underdog is passively calling.

These are three conditions that come to mind; I’m sure there are many more that could be tested. #2 sounds a bit paranoid I suppose, but it’s worth testing anyway. Let me state clearly that with regard to #3 above, I fully understand the concept of semibluffing, and this is not at all what I am referring to. I realize that aggressive players often get paid off by making keen semibluffs; a tight opponent may get out of the hand and the aggressor takes it down right then and there. If the opponent does call, the bluffer has at least given himself an opportunity to get lucky and hit what he needs. This is just semibluffing in a nutshell and I’m sure you all know this already. What I am talking about is compiling long-term data given all situations in which an aggressive semibluffer hits what he needs vs. a different data set consisting of how often a passive caller who isn’t contributing much to the ‘juiciness’ of the pot hits his hands with the same draws/ likelihoods of hitting as the semibluffer. For example, let’s say hypothetically that a particular draw has a 28% chance of hitting. After 100,000 hands of situations in which the semibluffer comes over the top and is called to see a showdown, the semibluffer wins 36% of the time. This discrepancy over this many hands would be statistically significant. HOWEVER, all the site would have to do is to be sure that given the same 28% likelihood of hitting the draw, a passive caller on that same draw would hit a mere 20% of the time. And this is of course assuming that there are just as many passive callers as there are semibluffers. The point is that these billion-dollar industries could easily pay to hire the best programmers in the world who are willing to sacrifice their morality for huge paychecks. They know what conditions are more profitable on the site’s behalf and then could easily trigger the software to favor those conditions, not the players themselves. And of course for every action there is an equal and opposite reaction, (i.e. 36% for semibluffer vs 20% for passive caller on a 28% draw), and when all conditional probabilities are tallied up in the longrun, they can easily make sure that each hand hits as often as it should. I encourage anyone who cares enough and who has the time to gather such data, because it may be the key to proving empirically that there is something fishy going on. The mere fact that a 28% draw hits 28% of the time and that a bozo amateur statistically survey confirms that does not mean that this is fair play.