Boxcars is the outcome of rolling the dice in a game of craps and getting a 6 on each die. The pair of 6 pips resembles a pair of box cars on a freight train. In modern parlance, it refers to such a roll in any game involving 6 sided dice which are marked with pips. The probability of this roll is 1 in 36, or about 2.8%. One of the 4 bets on any common craps table. It is on the ‘high side’ of the horn bet in which the player can either bet on the 2,3,11, or 12. When the player throws in money and calls out “midnight” or “Boxcars”, the dealer will usually ‘book’ the bet as a bet on the 12, so as to not create confusion.
Also called Midnight.
Related terminology
In some role-playing games, especially ones where a roll of 3 six-sided dice is a standard action-resolution mechanism, a roll of three “six”s is often referred to as a freight train. In roll-low systems (such as GURPS), where a roll of 18 represents a critical failure, or in In Nomine, where a roll of 6 6 6 represents infernal influence on events, it is referred to as a “Freight Train from Hell.”
When someone with limited experience achieves better than expected results it is referred to as beginner’s luck. The term is most often used in reference to a first attempt in sport or gambling. For example, if Mike beats veteran golf player Joe in his first game, Joe might attribute this to beginner’s luck. Beginner’s luck is also be applicable to non-sporting activities. For example, if Susan takes first prize in her first ever baking contest, she might have had beginner’s luck. The term is also used when no skill whatsoever is involved such as a first-time slot machine player winning the jackpot.
One would expect experienced players to outperform novices – when the opposite happens it is counter-intuitive hence the need for a term to describe this phenomenon.
Availability error, related to the gambler’s fallacy, is the distortion of one’s perceptions of reality due to the tendency to remember one alternative outcome of a situation much more easily than another.
For example, if surrounded by slot machines people are more likely to continue feeding money into their machine, because they will occasionally see someone else win and think their chances are high of winning: they remember others winning much more readily than they remember all the times they and others have lost. The fact that somebody has won does not change the actual probability of winning, and concentrating on the number of wins fails to take into account the number of losses. People consistently make this mistake, even though the odds of winning are just as bad for the group as for the lone machine. It’s just easier to remember winnings in large groups than for the lone machine.
Other examples:
“Sorry I’m late — I hit every red light on the way here.”
Anti-”country X” sentiment escalating due to occasional unethical actions of country X.
“My friend is a choleric, a typical Aries”. (the person does not remember hundreds of untypical Aries he has met that were not choleric and falsely believes in the relation between character and the Zodiac Sign)
Availability Effects in Lethal Events
When asked to rate the probability of a variety of causes of death people tend to rate more “newsworthy” events as more likely. People often rate the chance of death by plane crash higher after plane crashes, and death by natural disaster as too likely only because these events are more reported than more common causes of death.
Similarly, in certain rare situations, safety equipment meant to save lives (e.g. seat belts) may instead hamper life-saving efforts and cause serious injury or death. Although these devices may save many more lives than they cost, only the fatalities are reported by the media, creating controversy about the risks of the safety device.
A shill is an associate of a person selling goods or services who pretends no association to the seller and assumes the air of an enthusiastic customer. The intention of the shill is, using crowd psychology, to encourage other potential customers unaware of the set-up to purchase said goods or services. Shills are often employed by confidence artists.
The word “shill” is probably related to “shillaber”, a word of obscure early-20th century origin with the same meaning.
Shills are illegal in many circumstances and in many jurisdictions because of the frequently fraudulent and damaging character of their actions. However, if a shill does not place uninformed parties at a risk of loss, but merely generates “buzz,” the shill’s actions may be legal. For example, a person planted in an audience to laugh and applaud when appropriate, see “claque”, or to participate in on-stage activities as a “random member of the audience”, is a type of legal shill.
Shills in gambling
The illegal and legal gambling industries often use shills to make winning at games appear more likely than it actually is. For example, illegal three card monte peddlers are notorious employers of shills. These shills also often aid in cheating; they will disrupt the game if the mark is likely to win.
In a legal casino, however, a shill is sometimes a gambler who plays using the casino’s money in order to keep games (e.g. especially poker) going when there are not enough players. (This is different from a proposition player who is paid a salary by the casino for the same purpose, but bets with their own money.)
A shill is an associate of a person selling goods or services who pretends no association to the seller and assumes the air of an enthusiastic customer. The intention of the shill is, using crowd psychology, to encourage other potential customers unaware of the set-up to purchase said goods or services. Shills are often employed by confidence artists.The word “shill” is probably related to “shillaber”, a word of obscure early-20th century origin with the same meaning.
Shills are illegal in many circumstances and in many jurisdictions because of the frequently fraudulent and damaging character of their actions. However, if a shill does not place uninformed parties at a risk of loss, but merely generates “buzz,” the shill’s actions may be legal. For example, a person planted in an audience to laugh and applaud when appropriate, see “claque”, or to participate in on-stage activities as a “random member of the audience”, is a type of legal shill.
Shills in gambling
The illegal and legal gambling industries often use shills to make winning at games appear more likely than it actually is. For example, illegal three card monte peddlers are notorious employers of shills. These shills also often aid in cheating; they will disrupt the game if the mark is likely to win.
In a legal casino, however, a shill is sometimes a gambler who plays using the casino’s money in order to keep games (e.g. especially poker) going when there are not enough players. (This is different from a proposition player who is paid a salary by the casino for the same purpose, but bets with their own money.)
A risk premium is the minimum difference between the expected value of an uncertain bet that a person is willing to take and the certain value that he is indifferent to.
Example
Suppose a game show participant may choose one of two doors, one that hides $1,000 and one that hides $0. Further suppose that the host also allows the contestant to take $500 instead of choosing a door. All three options (door 1, door 2, or take $500) have the same expected value of $500, so there is no risk premium for choosing the doors over the guaranteed $500.
A contestant unconcerned about risk is indifferent to these choices. However, a risk averse contestant may be more likely to choose no door and accept the guaranteed $500.
If too many contestants are risk averse, the game show may encourage selection of the riskier choices (door 1 or door 2) by creating a risk premium. If the game show offers $2,000 behind the good door, increasing to $1,000 the expected value of choosing doors 1 or 2, the risk premium becomes $500 (i.e., $1,000 expected value – $500 guaranteed amount). Contestants with a minimum acceptable rate of return of $500 or more will likely choose a door instead of accepting the guaranteed $500.
Finance
In finance, the risk premium can be the expected rate of return above the risk-free interest rate.
Debt: In terms of bonds it usually refers to the credit spread (the difference between the bond interest rate and the risk-free rate).
Equity: In the equity market it is the returns of a company stock, a group of company stock, or all stock market company stock, minus the risk-free rate. The return from equity is the dividend yield and capital gains. The risk premium for equities is also called the equity premium.
The white paper Equity Risk Premium: Expectations Great and Small notes that “it is dangerous to engage in simplistic analyses of historical ERPs to generate ex ante forecasts that differ from the realized mean.” Standard & Poor’s states “the most correct method is to use an arithmetic average of historical returns.”
In gambling jargon, a holdout is any of numerous accessories used by cheats to help them “hold-out” a card (or cards) during a game. Some holdout devices are extremely simple and require moderate or advanced manipulative skill to be used properly. On the other hand, there is a group of holdout devices which are mechanical in nature, therefore they fall under a separate category of holdout machines. Even if those machines are complex mechanical apparatuses, they still require a good level of skill from the cheat’s part, to be used well.Most of the holdout devices used today were invented in the 19th century.
The main purpose of any holdout device is to temporarily hold a card out of the game, so that the cheat may retrieve it at some later convenient time. Only one card out of play can tremendeously increase the odds of winning. The cheat not only knows the identity of this card (an advantage that no other player has) and knows that it couldn’t possibly be dealt to any other player, but this card also serves as if an extra card was dealt to the cheat on every round. In effect, this is as if the cheat was dealt a bonus card, so that he may decide which combination of cards he likes best and finally discard the unwanted one, only to possibly use it on the next round (or at least switch it for a better one).
Some of the most popular holdouts are:
the arm pressure sleeve holdout
the ring holdout
the vest holdout
the Kepplinger holdout
the cuff holdout
The basic meaning of gambler’s ruin is a gambler’s loss of the last of his bank of gambling money and consequent inability to continue gambling. “Gambler’s ruin” is also sometimes used to refer to a final large losing bet placed in the hopes of winning back all the gambler has lost during a gambling session.More generally however the phrase refers to the ever decreasing expected value of a gambler’s bank as he continues to gamble with his winnings.
Examples
Coin flipping
Consider a flipping coin game with two players where each player has a 50% chance of winning each flip. After a flip the loser transfers one penny to the winner. The game ends when one player has all the pennies. If there is no other limit on the number of flips, the probability that the game will eventually end this way is 100%. If player one has n1 pennies and player two n2 pennies, the chances P1 and P2 that players one and two, respectively, will end penniless are:
P1 = n2/(n1+n2)
P2 = n1/(n1+n2)
It follows that the player that starts with fewest pennies is most likely to fail. Even with equal odds, the longer one gambles, the greater the chance that the player starting out with the most pennies wins. However, this does not imply positive expected value for richer player since for each complete game (many flips) that the richer player loses, he will forfeit more pennies than his poorer playmate.
Consider players with 90 and 10 pennies respectively, repeating the game 100 times. The player with 90 pennies is expected to win 90 out of 100 complete games, winning 10 pennies each game. However, he is also expected to lose 10 games, each time forfeiting all 90 of his pennies. So after the series of 100 games, the richer player is expected to win 90*10=900 pennies, and lose 10*90=900 pennies. Despite the fact that after any single game, one player ends up with all the pennies, the expected result over many games is for both players to break even.
A casino generally has:
many more pennies than any player thus ensuring that the player is much more likely than the casino to experience gambler’s ruin;
odds that favor the casino resulting in negative expected return for the player; and
various risk management techniques that limits their maximum loss.
The combination of above ensures that the casino will in the vast majority of cases come out ahead in the long run. For an illustration, see this Gambler’s Ruin simulation: [1]
Casino games
A typical casino game has a slight house advantage. The advantage is the long-run expectation, most often expressed as a percentage of the amount wagered. It remains constant from one play to the next. If the long-run expectation is expressed as a percentage of the amount that the player starts with, however, then the house advantage increases the longer the player continues.
For example, the official house advantage for a casino game might be 1%, and thus the expected value of return for the gambler is 99%. However, this math would only be true if the gambler never used the results of a winning bet again. Thus after gambling 100 dollars the idealized average gambler would be left with 99 dollars, but, if he continued to bet using his 99 dollars in winnings, he would again lose 1% on average and his expected value would go down to 98.01 dollars. This downward spiral continues until the gambler’s expected value approaches zero: gambler’s ruin.
The long-run expectation will not necessarily be the result experienced by any particular gambler. The gambler who plays for a finite period of time may finish with a net win, despite the house advantage, or may go broke much more quickly than the mathematical prediction.
Speculation
It might be pointed out that where economic activity is concentrated in transfers of wealth rather than its creation, gambler’s ruin results in most of the wealth being held by a very small number of participants. We see this in the stock market when speculative activity is the norm rather than long-term dividend producing investment.
There are many scenarios where the gambler’s fallacy might superficially seem to apply, where it in fact does not.
When the probability of different events is not independent, the probability of future events can change based on the outcome of past events. An example of this is cards drawn without replacement. It’s true that once a jack is removed from the deck, the next draw is less likely to be a jack and more likely to be of another rank. Thus, the odds for drawing a jack, assuming that it was the first card drawn and that there are no jokers, have decreased from 4/52 (7.69%) to 3/51 (5.88%), while the odds for any other card have increased from 4/52 (7.69%) to 4/51 (7.84%).
When the probability of each event is not even, such as with a loaded die, a number which has come up more often in the past may very well continue to do so, if that number is favored by the weighting of the dice. This has been dubbed Nerd’s Gullibility Fallacy — assuming the coin indeed is fair and the gamblers are honest when it isn’t the case. This is an example of Hume’s principle: twenty tails in a row indicates that it is far more likely that the coin is loaded than that the coin is fair and the next toss will be fifty-fifty heads or tails.
The outcome of future events can be affected if external factors are allowed to change the probability of the events (e.g. changes in the rules of a game affecting a sports team’s performance levels). Additionally, a rookie sports player’s success may decrease after opposing teams discover his or her weaknesses and exploit them. The player must then attempt to compensate and randomize his strategy, ultimately resulting in Game Theory.
Many riddles trick the reader into believing that they are an example of Gambler’s Fallacy, such as the Monty Hall problem. Similarly, if I flip a coin twice and tell you that at least one (i.e. one or both) of the flips was heads, and ask what the probability is that they both came up heads, you might answer, that it is 50/50 (or 50%). This is incorrect: if I tell you that one of the two flips was heads then I am removing the tails-tails outcome only, leaving the following possible outcomes: heads-heads, heads-tails, and tails-heads. These are equally likely, so heads-heads happens 1 time in 3 or 33% of the time. If I had specified that the first flip was heads, then the chances the second flip was heads too is 50%.
The gambler’s fallacy can be illustrated by considering the repeated toss of a coin. With a fair coin the chances of getting heads are exactly 0.5 (one in two). The chances of it coming up heads twice in a row are 0.5×0.5=0.25 (one in four). The probability of three heads in a row is 0.5×0.5×0.5= 0.125 (one in eight) and so on.
Now suppose that we have just tossed four heads in a row. A believer in the gambler’s fallacy might say, “If the next coin flipped were to come up heads, it would generate a run of five successive heads. The probability of a run of five successive heads is
.55 = 0.03125; therefore, the next coin flipped only has a 1 in 32 chance of coming up heads.”
This is the fallacious step in the argument. If the coin is fair, then by definition the probability of tails must always be .5, never more (or less), and the probability of heads must always be .5, never less (or more). While a run of five heads is only 1 in 32 (0.03125), it is 1 in 32 before the coin is first tossed. After the first four tosses the results are no longer unknown, so they don’t count. The probability of five consecutive heads is the same as four successive heads followed by one tails. Tails is no more likely. Each of the two possible outcomes has equal probability no matter how many times the coin has been flipped previously and no matter what the result. Reasoning that it is more likely that the next toss will be a tail than a head due to the past tosses is the fallacy. The fallacy is the idea that a run of luck in the past somehow influences the odds of a bet in the future.
Sometimes, gamblers argue, “I just lost four times. Since the coin is fair and therefore in the long run everything has to even out, if I just keep playing, I will eventually win my money back.” However, it is irrational to look at things “in the long run” starting from before he started playing; he ought to consider that in the long run from where he is now, he could expect everything to even out to his current point, which is four losses down.
As an example, the popular doubling strategy (start with $1, if you lose, bet $2, then $4 etc., until you win) does not work; see Martingale (roulette system). Situations like these are investigated in the mathematical theory of random walks. This and similar strategies either trade many small wins for a few huge losses (as in this case) or vice versa. With an infinite amount of working capital, one would come out ahead using this strategy; as it stands, one is better off betting a constant amount if only because it makes it easier to estimate how much one stands to lose in an hour or day of play.
Notice that the gambler’s fallacy is quite different from the following path of reasoning (which comes to the opposite conclusion): the coin comes up heads more often than tails, so it is not a fair coin, so I will bet that the next toss will be heads also. This is not fallacious, though the first step – the argument from a finite number of observations to a statement of likelihood – is a very delicate matter, and is itself prone to fallacies of its own peculiar kind.
A joke told among mathematicians demonstrates the nature of the fallacy. When flying on an airplane, a man decides to always bring a bomb with him. “The chances of an airplane having a bomb on it are very small,” he reasons, “and certainly the chances of having two are almost none!”
Some claim that the gambler’s fallacy is a cognitive bias produced by a psychological heuristic called the representativeness heuristic.
The gambler’s fallacy is a logical fallacy that mistakenly believes past events will affect future events when dealing with random activities, such as many gambling games. It can encompass any of the following misconceptions:
A random event is more likely to occur because it has not happened for a period of time;
A random event is less likely to occur because it has not happened for a period of time;
A random event is more likely to occur because it recently happened; and
A random event is less likely to occur because it recently happened.
These are common misunderstandings that arise in everyday reasoning about probabilities, many of which have been studied in great detail. Many people lose money while gambling due to their erroneous belief in this fallacy.
Put simply, the chances of something happening the next time are not necessarily related to what has already happened, especially in many gambling games.
Examples
You flip a fair coin 20 times and it comes up heads every time. What is the probability it will come up tails next time? (Answer: 0.5, although the probability of a coin coming up the same 21 times in a row is only 0.000000477.)
A couple already has two daughters. What is the probability that the next child is a son? (Answer: 0.5, assuming the gender of a child is completely random)
Are you more likely to win the lottery by choosing the same numbers every time, or by choosing different numbers every time? (Answer: you are equally likely with either strategy. In reality, you may be better off choosing numbers in such a way as to reduce the risk of splitting the jackpot.)
Non-examples
There are many scenarios where the gambler’s fallacy might superficially seem to apply, where it in fact does not.
When the probability of different events is not independent, the probability of future events can change based on the outcome of past events. An example of this is cards drawn without replacement. It’s true that once a jack is removed from the deck, the next draw is less likely to be a jack and more likely to be of another rank. Thus, the odds for drawing a jack, assuming that it was the first card drawn and that there are no jokers, have decreased from 4/52 (7.69%) to 3/51 (5.88%), while the odds for any other card have increased from 4/52 (7.69%) to 4/51 (7.84%).
When the probability of each event is not even, such as with a loaded die, a number which has come up more often in the past may very well continue to do so, if that number is favored by the weighting of the dice. This has been dubbed Nerd’s Gullibility Fallacy — assuming the coin indeed is fair and the gamblers are honest when it isn’t the case. This is an example of Hume’s principle: twenty tails in a row indicates that it is far more likely that the coin is loaded than that the coin is fair and the next toss will be fifty-fifty heads or tails.
The outcome of future events can be affected if external factors are allowed to change the probability of the events (e.g. changes in the rules of a game affecting a sports team’s performance levels). Additionally, a rookie sports player’s success may decrease after opposing teams discover his or her weaknesses and exploit them. The player must then attempt to compensate and randomize his strategy, ultimately resulting in Game Theory.
Many riddles trick the reader into believing that they are an example of Gambler’s Fallacy, such as the Monty Hall problem. Similarly, if I flip a coin twice and tell you that at least one (i.e. one or both) of the flips was heads, and ask what the probability is that they both came up heads, you might answer, that it is 50/50 (or 50%). This is incorrect: if I tell you that one of the two flips was heads then I am removing the tails-tails outcome only, leaving the following possible outcomes: heads-heads, heads-tails, and tails-heads. These are equally likely, so heads-heads happens 1 time in 3 or 33% of the time. If I had specified that the first flip was heads, then the chances the second flip was heads too is 50%.
A croupier (in European usage) or dealer (in American usage) is a person who takes and pays out bets or otherwise assists at a gambling table, often in a casino. In American usage, dealer may imply a card game, but this is not always the case. For example it is common to refer to a craps dealer[1].In general, the croupier works only for their salary (and tips) and does not have a personal interest in the outcome of the game.
In gambling terminology a crimp is a bend that has been intentionally made on the corner(s) of a playing card to facilitate identification.A card cheat will typically bend some of the important cards during the game. Below are just several of the most popular examples.
In poker, for instance, a cheat may crimp one of the cards to mark off the exact location where he wishes his secret conspirator to cut the deck. Similarly, if the card cheat is not working with a confederate, he may bend one or more cards to force a cut upon an unsuspecting victim. In either case the deck will most likely be cut at the exact predetermined spot in the same way an old book always tends to open at the same page.
Another poker scenario (also popular in numerous other games) is to crimp some of the high-value cards during the early rounds. On subsequent rounds the cheat will be able to identify some of those cards during the deal. This enables the cheat to employ a second deal and deal some of those cards to the desired hand, or simply to identify some of the cards held by other players. In any event, the cheat has a mathematical edge over the other players.
In casino blackjack a crossroader may crimp all the 10-value cards. this will enable the cheat to sometimes identify the dealer’s hole card (the dealer has one card face up, called the up card, and one card face down, called the hole card). In those instances the cheat(s) will know the dealer’s total and play their hand(s) accordingly.
A Chinese auction is a type of auction (actually a combination of auction and raffle) that is typically featured at charity or other fundraising events.In a Chinese auction, bidders are not prospective buyers (as in the conventional English auction). Instead, they buy tickets, which are essentially chances to win items. Bidders may buy as many tickets as they like, and bid them on any item(s) they want by placing them in a basket or other container in front of the item(s) they are trying to win. At the conclusion of bidding, the winning ticket is drawn from the tickets bid on each item, and the item is given to the owner of that ticket.
A bidder may increase their chance of winning by buying and bidding more tickets on a specific item. Although there is generally no limit to the number of tickets a given individual may bid on a specific item, the chance of winning depends on the total number of tickets bid by all individuals.
It is unclear whether this type of auction actually originates in China; it is much more likely that the term derives from “chance auction,” which is also another name for this type of auction.
The Chinese auction is similar to the “silent auction,” with the difference being that in the silent auction bidders submit bids listing specific amounts that they are willing to pay for a specific item.
Boxcars is the outcome of rolling the dice in a game of craps and getting a 6 on each die. The pair of 6 pips resembles a pair of box cars on a freight train. In modern parlance, it refers to such a roll in any game involving 6 sided dice which are marked with pips. The probability of this roll is 1 in 36, or about 2.8%. One of the 4 bets on any common craps table. It is on the ‘high side’ of the horn bet in which the player can either bet on the 2,3,11, or 12. When the player throws in money and calls out “midnight” or “Boxcars”, the dealer will usually ‘book’ the bet as a bet on the 12, so as to not create confusion.Also called Midnight.
Related terminology
In some role-playing games, especially ones where a roll of 3 six-sided dice is a standard action-resolution mechanism, a roll of three “six”s is often referred to as a freight train. In roll-low systems (such as GURPS), where a roll of 18 represents a critical failure, or in In Nomine, where a roll of 6 6 6 represents infernal influence on events, it is referred to as a “Freight Train from Hell.”
Video: Craps (Craps (previously known as crabs) is a casino dice game. Craps is a simplification of the Old English game hazard. The game involves predicting what numbers will be rolled on a pair of dice. The objective is to bet whether the Shooter will roll a winning combination. The Shooter is a person who throws the dice. The first roll of the dice in a craps round is called the “come out roll”. The opening bet in craps, which is placed just before the come out roll, is called the “pass line bet.” Pass line bets win if the shooter’s come out roll is 7 or 11, and lose when the come out roll is 2 (snake eyes), 3 (cross eyes), or 12 (box cars). If 4, 5, 6, 8, 9, or 10 are rolled on the come out roll then that number becomes “the point”. Once the point has been established a plastic disc (the puck) is placed on the table over the box for the number rolled as the point is “4, 5, six, 8, nine, or 10″. )
When someone with limited experience achieves better than expected results it is referred to as beginner’s luck. The term is most often used in reference to a first attempt in sport or gambling. For example, if Mike beats veteran golf player Joe in his first game, Joe might attribute this to beginner’s luck. Beginner’s luck is also be applicable to non-sporting activities. For example, if Susan takes first prize in her first ever baking contest, she might have had beginner’s luck. The term is also used when no skill whatsoever is involved such as a first-time slot machine player winning the jackpot.One would expect experienced players to outperform novices – when the opposite happens it is counter-intuitive hence the need for a term to describe this phenomenon.
Availability error, related to the gambler’s fallacy, is the distortion of one’s perceptions of reality due to the tendency to remember one alternative outcome of a situation much more easily than another.For example, if surrounded by slot machines people are more likely to continue feeding money into their machine, because they will occasionally see someone else win and think their chances are high of winning: they remember others winning much more readily than they remember all the times they and others have lost. The fact that somebody has won does not change the actual probability of winning, and concentrating on the number of wins fails to take into account the number of losses. People consistently make this mistake, even though the odds of winning are just as bad for the group as for the lone machine. It’s just easier to remember winnings in large groups than for the lone machine.
Other examples:
“Sorry I’m late — I hit every red light on the way here.”
Anti-”country X” sentiment escalating due to occasional unethical actions of country X.
“My friend is a choleric, a typical Aries”. (the person does not remember hundreds of untypical Aries he has met that were not choleric and falsely believes in the relation between character and the Zodiac Sign)
Availability Effects in Lethal Events
When asked to rate the probability of a variety of causes of death people tend to rate more “newsworthy” events as more likely. People often rate the chance of death by plane crash higher after plane crashes, and death by natural disaster as too likely only because these events are more reported than more common causes of death.
Similarly, in certain rare situations, safety equipment meant to save lives (e.g. seat belts) may instead hamper life-saving efforts and cause serious injury or death. Although these devices may save many more lives than they cost, only the fatalities are reported by the media, creating controversy about the risks of the safety device.
Advantage player is a term used to describe a person who has the ability to play a casino gambling game so skillfully that even without cheating, that person can negate or reverse the casino’s typical built-in house advantage in that game. Examples of advantage play include card counting in blackjack and dice control in craps.Casinos will generally eject an individual whom they identify as being an advantage player. And habitual offenders may ultimately find themselves listed in the Griffin Book, and thus become unwelcome in most casinos. However, advantage players are abiding the established rules of the game, and thus committing no actual fraud against the casino. Therefore, unlike those who cheat outright at the games, advantage players can operate without fear of being criminally prosecuted if they are discovered.
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Boxcars is the outcome of rolling the dice in a game of craps and getting a 6 on each die. The pair of 6 pips resembles a pair of box cars on a freight train. In modern parlance, it refers to such a roll in any game involving 6 sided dice which are marked with pips. The probability of this roll is 1 in 36, or about 2.8%. One of the 4 bets on any common craps table. It is on the ‘high side’ of the horn bet in which the player can either bet on the 2,3,11, or 12. When the player throws in money and calls out “midnight” or “Boxcars”, the dealer will usually ‘book’ the bet as a bet on the 12, so as to not create confusion.
