Is there something amiss in the software used to run FullTilt, or is it just our imagination? This post will examine the inherent RNG Full Tilt poker flaws and how it adversely affects players.
The RNG, as most any online poker player knows is the Random Number Generator that "shuffles" the cards in an online poker room. The RNG is by most accounts the fairest way to shuffle a deck to make the game appear fair and random. However, there are several inherent flaws which inevitably have many poker players screaming "This site is rigged"
There are several arguments as to why bad beats and suck outs occur on Full Tilt, and most of these are explained away in a non-technical 'that's poker' explanation. However, it stands to reason that there actually should be a more plausible reasoning behind the enormous amount of bad beats and suckouts.
That reasoning, as discussed by Paul Westin (a professional poker player and software engineer), is that there really are flaws in the programs used by Full Tilt as well as Pokerstars and almost all other online poker sites.
The flaws are a result of an attempt by the programmers to create a secure and unpredictable deal of the cards using the RNG. In 2001 several skilled software programmers were able to break the pattern of a popular RNG used on a well-known poker site, resulting in massive wins by the hackers.
This prompted the Online poker sites to find a more secure manner in which to deal and shuffle cards. At first, the seed used in the RNG was changed to a non-static variable (such as a white noise generator, sound wave technology, etc). This helped make it nearly impossible to find the seed, since the variable would constantly change in a widely non-specific pattern.
The next measure was to add in algorithms and subroutines to prevent any one player to win pot after pot. This was a safeguard in case the RNG was possibly compromised, and further accomplished by an algorithm which would force specific hands to win, while others would lose. (you know AA vs. 5 8os and the 5 8 gets there!)
The result is less than desirable, since the actual deal of the cards no longer mimic real life statistics. In fact, in a study of 250,000 hand histories, it was determined that a straight or flush occurred 12% more often than it would in live play. While a full house occurred nearly 25% more often than it statistically would in live play.
After careful examination of Paul Westin's complete study on the RNG full tilt poker flaws, I am without a doubt convinced that his answers are way more plausible than the standard answers given in most rigged poker debates.
It should be noted that Westin does not claim the sites are rigged to their own advantage, rather they are rigged to prevent cheating, collusion and players dominating a table. The algorithms used are in place to prevent what the poker site feels would otherwise be an unfair advantage.
However, the fact that they add in algorithms and subroutines in an attempt to prevent cheats, has opened up the door for a person to actually win more if they are familiar with the patterns created by the algorithms and if that player knows what to 'look for' while playing.
My opinion is that Westin is on target, his explanation definitely gives a player the advantage and he even shows how to suckout and how to know when you are going to lose a big hand.
You can read more at the Online Poker Code Crack site and further articles located at ezinearticles.
Good Luck as always!
Showing posts with label rng. Show all posts
Showing posts with label rng. Show all posts
Saturday, September 12, 2009
Friday, August 14, 2009
Online Poker The Random Number Generator
As many people are aware, online poker rooms (as well as any online gambling site) uses what is called a random number generator to produce what would appear to be a random outcome in each hand.
This article will explain the Random Number Generator (also called Pseudo-Random Number Generator, PRNG or RNG). The purpose of this article is to familiarize players with the 'inner workings' of the software used in the Online Poker rooms and the way cards are produced in a deal.
The use of a RNG is nothing new, as it actually dates back hundreds of years before the computer was even conceived. Mathematicians as early as the 1700's used a random number process to try and determine outcomes of specific problems.
The advent of the computer presented a challenge for scientists and programmers wanting to produce a seemingly random action from the computer, and therefore an assembly code language function was implemented called RAND also known as randomize and RND. This function would be attached to a program and assigned a variable to select a random number.
However, the program required a 'seed' number to begin its process of selecting what would appear to be a random number, otherwise it would produce the same series of numbers each time the program ran. Therefore, early programmers used the timer function on the CPU in order to produce a different series of seemingly random numbers each time the program ran.
This was somewhat acceptable and appeared to produce a different random result each time. However, after several thousand runs of the program, it became easier to 'predict' what series of numbers would come out. This gave a challenge to programmers to find a way to actually produce what would seem to be a truly random result, one that could not be predicted or repeated in any short course of time.
Ultimately, a mathematical method was derived that gave the RNG's a better way to produce a more realistic way of generating random numbers. In addition, experiments using white noise generators to produce the seed were also successful. Both of these among other secondary methods to produce a seemingly random result are used today in all major Online Poker rooms.
Now for the DEAL!
How does that affect the deal of cards, you may ask. Well, actually, the modern RNG programs are more beneficial then the software used several years ago. The sophistication of the randomness is better for the player, because the predictability of a card is much harder, and the RNG is designed to curtail cheating. However, it is not the best method and has many failures.
The Major Fail
A standard 52 card deck has a total number of possible combinations of 80,658,175,170,943,878,571,660,636,856,404,000,000,000,000,000,000,000,000,000,000,000,000
Thats a BIG number, in fact, there is no name for a number that large except to say it is 8 times 10 to the 67th power.
What this means is that if you lay out all 52 cards in order, that is one possible combination of the deck, you shuffle the cards and lay them out again, they obviously are in a different order, and that would be a second combination, repeat this process and each time you would get a different sequence or combination of cards laid out on the table. It would require a minimum 8 times 10 to the 67th power 'deals' to repeat the exact same sequence of cards.
In essence, a deck of cards is ideally suited to an RNG because of the endless variety of combinations of a deck. However, there is no possible way any computer in existence has the ability to store every combination (it would require at the bare minimum a 256 bit processor and a whole lot of speed!) and since most servers use only a 32 or 64 bit architecture they are only able to process a small fraction of all possible combinations.
Two Pigeons; One Hole
This is known as the Pigeonhole Principle, wherein the theorem states that there does not exist an injective function on finite sets whose co-domain is smaller than its domain. In other words, you can not put two objects into a container that is physically only able to hold one object.
So what happens to the billions of possible deck combinations? Simple, they are never used, processed or even appear in the online poker RNG. They do not exist as far as the program is concerned.
In reality, out of the 8x10^67 possible combinations only about 4 billion deck combinations are used in a 32bit architecture. This greatly reduces the number of possible hands you can make, and also is a basic explanation as to why there are so many bad beats and made hands in online poker.
For this reason, you will notice more straights, more flushes and more often full houses appear at showdown. The program, by reducing all the possible combinations down to less than 1/20^58, now forces a lot of action and produces a lot of big hands, because it strips away all the outer-dimensional deck combinations. (How often do you see high card, one pair or two pair win?)
In conclusion, the RNG used in online poker is never able to truly produce a random deck or outcome, simply because the program does not use all possible combinations of decks. There are other reasons the deck may be stacked against you and we will explore those in upcoming articles.
I hope this article is helpful to you in understanding how the RNG produces a 'random' deck of cards and invite you to subscribe or bookmark this blog to learn more about online poker.
This post is intended to give a brief oversight of some of the inner workings of the online poker RNG, in the next post, I will explore how the RNG can actually be manipulated to your advantage.
This article will explain the Random Number Generator (also called Pseudo-Random Number Generator, PRNG or RNG). The purpose of this article is to familiarize players with the 'inner workings' of the software used in the Online Poker rooms and the way cards are produced in a deal.
The use of a RNG is nothing new, as it actually dates back hundreds of years before the computer was even conceived. Mathematicians as early as the 1700's used a random number process to try and determine outcomes of specific problems.
The advent of the computer presented a challenge for scientists and programmers wanting to produce a seemingly random action from the computer, and therefore an assembly code language function was implemented called RAND also known as randomize and RND. This function would be attached to a program and assigned a variable to select a random number.
However, the program required a 'seed' number to begin its process of selecting what would appear to be a random number, otherwise it would produce the same series of numbers each time the program ran. Therefore, early programmers used the timer function on the CPU in order to produce a different series of seemingly random numbers each time the program ran.
This was somewhat acceptable and appeared to produce a different random result each time. However, after several thousand runs of the program, it became easier to 'predict' what series of numbers would come out. This gave a challenge to programmers to find a way to actually produce what would seem to be a truly random result, one that could not be predicted or repeated in any short course of time.
Ultimately, a mathematical method was derived that gave the RNG's a better way to produce a more realistic way of generating random numbers. In addition, experiments using white noise generators to produce the seed were also successful. Both of these among other secondary methods to produce a seemingly random result are used today in all major Online Poker rooms.
Now for the DEAL!
How does that affect the deal of cards, you may ask. Well, actually, the modern RNG programs are more beneficial then the software used several years ago. The sophistication of the randomness is better for the player, because the predictability of a card is much harder, and the RNG is designed to curtail cheating. However, it is not the best method and has many failures.
The Major Fail
A standard 52 card deck has a total number of possible combinations of 80,658,175,170,943,878,571,660,636,856,404,000,000,000,000,000,000,000,000,000,000,000,000
Thats a BIG number, in fact, there is no name for a number that large except to say it is 8 times 10 to the 67th power.
What this means is that if you lay out all 52 cards in order, that is one possible combination of the deck, you shuffle the cards and lay them out again, they obviously are in a different order, and that would be a second combination, repeat this process and each time you would get a different sequence or combination of cards laid out on the table. It would require a minimum 8 times 10 to the 67th power 'deals' to repeat the exact same sequence of cards.
In essence, a deck of cards is ideally suited to an RNG because of the endless variety of combinations of a deck. However, there is no possible way any computer in existence has the ability to store every combination (it would require at the bare minimum a 256 bit processor and a whole lot of speed!) and since most servers use only a 32 or 64 bit architecture they are only able to process a small fraction of all possible combinations.
Two Pigeons; One Hole
This is known as the Pigeonhole Principle, wherein the theorem states that there does not exist an injective function on finite sets whose co-domain is smaller than its domain. In other words, you can not put two objects into a container that is physically only able to hold one object.
So what happens to the billions of possible deck combinations? Simple, they are never used, processed or even appear in the online poker RNG. They do not exist as far as the program is concerned.
In reality, out of the 8x10^67 possible combinations only about 4 billion deck combinations are used in a 32bit architecture. This greatly reduces the number of possible hands you can make, and also is a basic explanation as to why there are so many bad beats and made hands in online poker.
For this reason, you will notice more straights, more flushes and more often full houses appear at showdown. The program, by reducing all the possible combinations down to less than 1/20^58, now forces a lot of action and produces a lot of big hands, because it strips away all the outer-dimensional deck combinations. (How often do you see high card, one pair or two pair win?)
In conclusion, the RNG used in online poker is never able to truly produce a random deck or outcome, simply because the program does not use all possible combinations of decks. There are other reasons the deck may be stacked against you and we will explore those in upcoming articles.
I hope this article is helpful to you in understanding how the RNG produces a 'random' deck of cards and invite you to subscribe or bookmark this blog to learn more about online poker.
This post is intended to give a brief oversight of some of the inner workings of the online poker RNG, in the next post, I will explore how the RNG can actually be manipulated to your advantage.
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