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#11
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[ QUOTE ]
[ QUOTE ] I've heard 10%, but that may be optimistic. [/ QUOTE ] I've heard this figure too, but I'm not sure it's right. 45% of players are >0BB/100 according to my PT database, and this number increases as I filter for a greater number of PROS. [/ QUOTE ] fp |
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#12
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[ QUOTE ]
[ QUOTE ] I've heard 10%, but that may be optimistic. [/ QUOTE ] I've heard this figure too, but I'm not sure it's right. 45% of players are >0BB/100 according to my PT database, and this number increases as I filter for a greater number of hands. [/ QUOTE ] Survivor bias. OP, if I had to pick a number, it would be about 5% are winning players, though maybe 10% end up beating the game (winning players who don't go busto + losing players who win some and don't lose it all back, like they go on a heater or win a tourney, withdraw a good percentage and lose the rest and don't redeposit.) |
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#13
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Could it be possible that the population of players that play predominately cash games have a higher percentage of profitable players than the population of players that predominately play MTTs and/or STTs?
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#14
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I guess the 5% casino edge online crushes even decent players over the long run except at higher stakes where it is maxed out easily. Higher limits could have much larger % of winners.
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#15
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Survivor bias sounds cool, and I'm sure it has some effect on the problem. But it's a much more complicated concept than is needed to explain the basic pattern in the data, i.e., that a surprisingly high percentage (e.g, 40%) of players look like winners in people's databases when we believe from other sources that only 10% of players are actually long-term winners. Generate some win-rate numbers drawn from the appropriate distribution for the typical numbers of hands played by people in your PT database and you'll see what I mean.
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#16
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[ QUOTE ]
Could it be possible that the population of players that play predominately cash games have a higher percentage of profitable players than the population of players that predominately play MTTs and/or STTs? [/ QUOTE ] No |
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#17
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[ QUOTE ]
Survivor bias sounds cool, and I'm sure it has some effect on the problem. But it's a much more complicated concept than is needed to explain the basic pattern in the data, i.e., that a surprisingly high percentage (e.g, 40%) of players look like winners in people's databases when we believe from other sources that only 10% of players are actually long-term winners. Generate some win-rate numbers drawn from the appropriate distribution for the typical numbers of hands played by people in your PT database and you'll see what I mean. [/ QUOTE ] I've never seen a reliable cite for the 90%-losers-10%-winners statistic. It strikes me as being a number some poker author pulled out of his butt. |
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#18
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You may well be right, Alan.
My post was not so much about the validity of the "10% winners" assumption, more about the fact that 10% winners long term is not incompatible with 40% winners in many people's medium-sized PT databases. As for the reliability of the 10% claim, the only semi-reliable cite I know of was I think a CardPlayer article where the author had been talking to unnamed sources at two of the larger online sites (i.e., Party & Stars one assumes) and was told in both cases that only 7-9% of their customers were in the black. Forgive me for not digging up the reference, I am probably just contributing to the further circulation of what might just be an urban poker legend. |
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#19
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try thinking of it this way;
In a hand of poker 1 person out of nine will win the pot, barring a split. Over the lifetime of the game if the same 9 players play (or 9 million) on average only the percentage that represents 1/9 would show a profit (in a zero sum scenario) |
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#20
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My guess would be 15% or less.
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