new poker research software - ALL IN 1.1

[gaijinuronin]

Hi all,

Some people say that online poker sites are trying to curb the flow of money from bad players to good players in order to boost their profits.
Is very hard to prove mathematically somenthing like that BUT I can do some math against specific situations.

THE PROBLEM:

Let's say I have hands H1,H2,....Hn where you are against one opponent and one of you two (or both) moves ALL IN.
Let's name your equities E1(H1),E2(H2).....when an ALL IN situation occurs before the river.

Let's define a function that returns the size of the pot when you WIN and 0 when you loose.
R(i)={ 0, if you loose
POTSIZE(i)/2, if we have a split
POTSIZE(i), if you are the winner
}


R(1)+R(2)+R(3)..................
and
E1(H1)*POTSIZE(1)+E2(H2)*POTSIZE(2)+.............. .

SHOULD CONVERGE!!!


The problem definition is somehow similiar with the one from 'all in luck/with total winnings' tab from Poker EV.
The differences are:
1. i dont take rake into consideration ..the game is considered 'ideal' (no rake)
2 only headsup 'all in's are considered in my program
3 In POker EV POTSIZE(i) represents the money bet only on the 'all in' street and not total pot size after all in like in my program


HOW TO RUN
The program is supposed to work with PT database (Access/Postgresql->ODBC access)
You also have the option to filter between 'big pot'/'small pot'/'all pots' ALL INs
The program will save 2 log files with the analyze and creates a chart with your result in ALLIN.png image file.

The conspiracy theory says that more than 80% of the winning players dont win their share of 'all in' pots.
With your help this theory can be confirmed or not.

You can download the program from here:
ALL IN 1.1

And this is the graph for my ~250.000 played hands:



I would highly appreciate if somebody could share with us a similar analyze by posting his graph in this thread.


Thanks,
Valentin

[gaijinuronin]

I compute only ALL IN situations for preflop/flop/turn with 2 players ( one moved all in and the other one called). When this kind of ALL IN happens I compute the equity of my hand at the moment the ALL IN happened.I know exactly at this moment how much I should win/loose in the long run.

The 'expected win' as I defined here its always positive because I dont take into account how much money I invested into the pot.

When an 'all in' happens and the other player calls the hands are face up.

I will take an example :

Hand1:
I move all in preflop and the opponent calls
Me:Kc Kh
Him:Ac Ah
Potsize : 1000$

My expected win is my equity multiplied by potsize:
EV(1) = E(1)*POTSIZE(1) = 0.18*1000 = 1800$

Result of the all in AA wins
R(1) = 0

Hand2:
I call an all in with 8c 8d on the following flop: 9h 8h 5h and the opponent turns Ah 2h for a flush
My equity in this 2000$ pot is 0.345 ( Poker Odds Calculator (twodimes.net) )

My expected win is EV(2) = 0.345*2000 = 690$

Turn is a 5d and river is a Jd and I win with a full house.
So result is R(2) = 2000$

Hand3:
I move all in on turn with 6c 7s on board: 9h 8h 2d As
The opponent calls my all in and he has Qh Qd
The potsize is 1000 and my equity in this pot is 0.182
( Poker Odds Calculator (twodimes.net) )
My expected win is EV(3) = 0.182*1000 = 182$

River is a blank and I loose the hand.
So R(3)=0

The sums
EV(1)+EV(2)+Ev(3)+ ..................
and
R(1)+R(2)+R(3)+ ................

SHOULD CONVERGE

[Phil153]

[ QUOTE ]
R(1)+R(2)+R(3)..................
and
E1(H1)*POTSIZE(1)+E2(H2)*POTSIZE(2)+.............. .

SHOULD CONVERGE!!!

[/ QUOTE ]

We talked before and I know you're trying to prove that poker sites are rigged...but one of the problem that any all-in EV analysis suffers from is a bunching effect. This makes it extremely difficult to definitively prove that sites are rigged, unless the rigging is quite statistically significant (which they would have to be anyway to make rigging worth the risk, one would think). It's a subtle effect and not really noticeable at ordinary play scales, but it could cause a statistically significant deviation over a huge number of hands (I mean hundreds of thousands), such as what you see in your graph.

The bunching effect I'm talking about is the fact that certain kinds of dead cards can be selected for, and all-in situations may tend to occur more often on decks where the dead cards are biased in a certain direction. For example, if a lot of people have an ace in their hand, bigger preflop pots tend to get built, leading to more favorable condition for drawing and staying in, and eventually getting all-in. Therefore, if you play Ax hands more than your opponents, you may find yourself getting all in against lesser opponents more often when your ace outs are dead. This is a very small effect, but it is cumulative, and over thousands of all ins it may be enough to show the deviation you see.

Anyway this is just an example, but it highlights the problems with getting excited about small deviations, especially ones that are showing a gradual increase over a large volume of hands.

Cliff notes: The method you're using is more than good enough for normal use, but not infallible to determine rigging without some solid statistical analysis.

[gaijinuronin]

Yeah .. I like your program (Poker EV)

1)There's no statistical discrepancy on the 'all in's from 250k hands I played ...only -3% in the aggregated expectation

2)I think i got the idea with the 'bunching effect' but doesnt that affect in equal measure me and the opponents?

I 've heard a lot of winning people complaining about 'running bad' when moving 'all in' . (..yeah .. i know ..maybe the people who are running bad are more likely to post about that...but..)

However I'm very curious how luck/unlucky are other people on a larger sample ( at least 100k hands)

[Phil153]

[ QUOTE ]
but doesnt that affect in equal measure me and the opponents?

[/ QUOTE ]
Not if you play differently, on average, than your opponents - and winning players generally do.

I'm not saying the effect is necessarily there for any player, but be aware that these calculations aren't and probably never can be definitive for proving that sites are rigged unless large effects are noticed.

Regardless, it's fun to look at.