Percentage of Online Winners, Revisited Yet Again

[dfan]

I know this has been discussed many times before, but never seemed to reach any resolution. The threads tend to end with just a bunch of guesses. At least that is my impression after reading a number of recent threads on the subject. If I'm wrong I'm sure I will be corrected. Anyway, here goes my foray down this so far dead-end lane.

In the Software Forum there was a discussion of the fact that many people were finding that about 40% of the players in their PT db's were winners and what this meant. My final take on it was that the 40% was an accurate and reliable estimate, but unfortunately not of anything very interesting. It represented "the proportion of players at a typical online table that are winners for the short span of hands that appear in a typical PT database." Whoopdedoo, right?

But the question usually posed is very different: "What percentage of online players are winning players"?

And answering that is problematic for a few reasons, some conceptual, some logistical.

First problem is clearly defining the question. What is the definition of "winning player"? I would guess it would be someone who has played at least X number of hands and is + $ for lifetime online play. What should X be? 50K? 100K? Lets pick 50K.

For players with 50K hands we are set to go assuming we could get the data. But what about players who played fewer than 50k hands but quit because they were losing so much money. Shouldn't they be counted in the "losing player" category? And if so, to be fair, shouldn't players with less than 50k hands who quit a winner as "winning players"? But if that approach is followed "winner" no longer means long-term winner.

One solution is to redefine our question to: "What percentage of online players who stick with the game long enough to amass 50k hands are lifetime + $."

(For ease of discussion I'll refer now to Party players.)

If that is our definition we still need a random sample of a 1000 Party players to get an estimate that is +/- 3% with 95% confidence. Unfortunately we can't get that by observing tables because winning players are overrepresented there. If we could get Party's player list we could pick a random sample from it but we don't have that.

So how to proceed? I can only think of a few possibilities.

1. Somehow creating a "correction factor" that would adjust for the overrepresentation of of winning players at a typical tables. Anyone have any ideas on how to do that?

2. If Party ever accidentally publishes a semi-random list of players that could be used. How would that happen? Well it could result from some type of promotion. For example, you could argue that winning the bad beat jackpot is a pretty random event, so the list of winners would constitute a random list. Of course the problem is that the list would be very short and also biased in that it would include only the type of players who play in those games. Is there anything else that Party does that picks players on a close-to-random basis and reveals their names?

3. If a random list could be created then those players would have to be datamined for ideally 50k hands. Then count up the winners and divide by the total and you have your answer. But since 50k hands on a 1000 players is quite an undertaking, it might be possible to infer the answer from trends in the data. The change in % of players that are winners as hand count increases is likely a pretty well defined function. So you could plot a graph of hand count vs % win for the data you could get on these players and see where that graph leads to at 50k.

Of course Party could answer the question easily but I doubt they would be thrilled to do that. I can see them advertising "Come to Party and join the other X% that lose here."

So until the "non-random sample problem" can be solved, the question is not answerable and no amount of PT datamining will help. Anyone have any ideas or comments?

[astroglide]

didn't read the post, but to head it off at the pass DO NOT FACTOR THE POKERTRACKER WINNING PLAYERS STAT INTO THIS. it counts everyone. people who changed names, people who sit for 3 hands, etc. it's not going to be remotely accurate unless you have thousands of hands for all involved, and many of those with thousands of hands are at least decent players.

[reubenf]

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didn't read the post

[/ QUOTE ]

obviously

[SomethingClever]

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My final take on it was that the 40% was an accurate and reliable estimate

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So wrong.

You're never going to get anything but a guess, so here's mine: 5%.

[imported_CaseClosed326]

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So wrong.

You're never going to get anything but a guess, so here's mine: 5%.

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Wrong again, it's easily in the 90-95% range.

[dfan]

You weren't paying attention. I said 40% was a reliable estimate of the "winning" players in a PT database, where winning only means being up for a short span of hands. Or have you found that only 5% of the player in your PT are + $?

[UncleDuke]

I think something on the order of 40% sounds reasonable when we're talking about the % of people playing in a small number hands who are ahead for that period. This is just figuring that over a very short run, assuming the whole test group is involved over the entire test period of hands, randomness would dictate that you'd expect about 50% to be up and 50% down ignoring rake. Skill differences will probably only affect the results modestly if we're looking at a very short period. Since there is rake, I'd knock a fraction off the % who are up, so I see 40ish% as ballpark reasonable.

Note that this doesn't really say very much about the larger question of what % of online players are winning players in general (without making those very controlled assumptions above). I think the most reasonable way to phrase the big is question is, of those playing during some random snapshot moment, what percentage are winning players? Of course, this will change from moment to moment, but let's say the "answer" is the average % you get if you measured this over many snapshots. I'd define a winning player to be someone who is ahead over the course of his poker career, however long or short it is.

[teamdonkey]

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You weren't paying attention. I said 40% was a reliable estimate of the "winning" players in a PT database, where winning only means being up for a short span of hands. Or have you found that only 5% of the player in your PT are + $?

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my (smallish) PT database:

players who have won money: 37.7%
hands dealt to players who have won money: 51.9%

That second number is somewhat skewed since 11% of those hands were dealt to one person (me), but even without me it's at 46%. I think that number more accurately answers the question of "at a random table how many people are winning and how many losing?".

[Delphin]

Your definition seems very strange to me. Do you really think there are lots of people out there who have played 50k hands and lost money and keep on depositing and playing? I would think with that definition the % of losing players would be very small.

That definition isn't really all that important to me anyway. What I really want to know is if I sit down at an average table, how many people in the game with me are winning players? For that purpose, the PT database is probably as good an answer as you are going to get.

I think that most people either try it out and lose a lot of money pretty quickly and never come back, or they stick around and eventually learn a few things and become winning players. The good news is that for every one that leaves, there are a lot more joining up because of the popularity of poker right now.

[dfan]

True there could be several definitions of "winning player" and "losing player." Some take winning player to mean someone who plays well enough to have a positive EV when he/she sits down at the table. Maybe this should be called a +EV player. Anyway for that definition you need a hell of a lot of hands to make a reliable classification. I took that number to be 50K, maybe it is fewer or more. I'm a semi-newbie and I don't know what the consensus is.

A different definition of "winning player" versus "losing player" is whether or not a player is up or down overall since he/she started playing online. Some people are interested in that for various reasons, including getting a reference point for how they compare to others who try this game.

You say the definition isn't that important to you but let's take your question as an example of why a precise definition is absolutely required. You say "What I really want to know is if I sit down at an average table, how many people in the game with me are winning players?" I assume you mean +EV vs -EV players since you want to know how many fish there are. So here are the players at your table:

AAkkJ: is up $ for the last 50k hands he's played.
ImAJerk: been losing slowly but steadily for the past 2 years, but blames it on bad beats.
DORK: Only played 4k hands, but is up 2BB/100 for that time.
CrushU: Played 15k hands, is down overall, but up for the last 10k.

Now tell me how many winning player and losing players there are at this table.

You see the point? You can't answer your question without defining your categories.

One final thought - may have to use multiple cateogories: +EV player, -EV player (proven Fish), Possible +EV player, Likely -EV player (likely Fish), and Not Enough Info.