No matter how good we think we are, no matter how many chips we have stacked, no matter how much money we walk away with, we're all prone to mistakes. One of these mistakes is getting sucked into the renowned gambler's fallacy, which is all too often the bane of casino players. But what is the gambler's fallacy and how do you stop yourself from falling victim to it?
As with most things in life, knowing your enemy is the first step to victory. This in-depth guide will explain the concept, provide you with examples, and take a look at the psychology of a gambler so you know not to fall into the same trap. Whether you call it the gambler's fallacy, the slippery slope fallacy, or the Monte Carlo fallacy, we've got everything you need to step up your game!
Let's simulate the Gambler's Fallacy just to convince ourselves that waiting for a high occurrence of one outcome doesn't result in a higher probability of an alternative outcome. A coin is flipped 40 times. The strategy we'll test is waiting until 10 heads are observed in a row. The probability of this occurring is 0.00098. Mistaken belief that an event that hasn't occurred (in a game of random chance) in a long time is somehow 'due' to occur. Used by gamblers in games of chance, often to their detriment. The Gambler's Fallacy and Roulette Also, it's important to understand how the gambler's fallacy fits into this discussion. This is a common math mistake where someone thinks that something that's happened repeatedly on previous bets changes the probability on the next bet.
The Gambler's Fallacy The Gambler's Fallacy is the idea that past behavior influences future behavior. In everyday life, it's a good strategy — there are all kinds of ways that events in the past. Advantage Play, probabilities and gambler's fallacy Probabilities and Gambler's Fallacy Many AP players are throwing around the 'gambler's fallacy' (GF for short) accusation, when the issue really is probabilities. Probabilities have a deterministic quality. They tell you how things will 'end' or look like after a large enough sample of trials.
What is the Gambler's Fallacy?
Most people, whether in the casino or in their day-to-day lives, have probably encountered the gambler's fallacy. In its simplest terms, this concept is based on the belief that a random event is less or more likely to happen following an event or series of events. Essentially, the basic premise of the gambler's fallacy is that something is likely to happen if it hasn't happened in a while.
Origins
The true origins of the gambler's fallacy are not fully known, but it was first proposed (in its modern iteration) by mathematical psychologist Amos Tversky and psychologist Daniel Kahneman. By analysing cognitive behaviors, such as the psychology of a gambler, they were able to attribute the gambler's fallacy to the mistaken belief that gambling was a fair process that would somehow correct itself in the event of a winning or losing streak.
Example
The best example of the gambler's fallacy in action is to examine it in relation to a coin toss. As you know, the chance of a coin toss landing on either heads or tails is 1:1, meaning that it is just as likely to come up tails as it is heads. So, if you flipped a coin 20 times and they all landed with tails up, under the gambler's fallacy you'd predict that the next flip is more likely to come up heads. This prediction is based on the idea that, because tails has come up 20 times, the sequence will break eventually and heads will come up.
Regardless of how many times the coin has come up heads, the probability of it being heads or tails on the next toss remains 50%; each coin toss is a separate event that is independent of the last one, meaning that previous tosses have no bearing on future ones.
Roulette Strategy Gambler's Fallacy Hasty
If you apply the gambler's fallacy to roulette, you can see how easy it is to be sucked in. For instance, the chances of the ball landing on red are 50% (or just under with the house edge). So, if the ball landed on red after 10 consecutive spins, under the gambler's fallacy you'd wrongly assume that the next spin will land on black. However, as with the coin toss, the probability of the result changing remains 50%. It's just as likely to land on red as black.
Equally, the reverse gambler's fallacy is to be avoided. In this scenario – after the coin has come up heads 20 times or the ball as landed on red 10 times – the player believes that, by some universal decree, the next toss or spin will result in the same result. Again, this disregards the probability and is simply a false assumption.
The Monte Carlo Casino Incident
What is the Gambler's Fallacy?
Most people, whether in the casino or in their day-to-day lives, have probably encountered the gambler's fallacy. In its simplest terms, this concept is based on the belief that a random event is less or more likely to happen following an event or series of events. Essentially, the basic premise of the gambler's fallacy is that something is likely to happen if it hasn't happened in a while.
Origins
The true origins of the gambler's fallacy are not fully known, but it was first proposed (in its modern iteration) by mathematical psychologist Amos Tversky and psychologist Daniel Kahneman. By analysing cognitive behaviors, such as the psychology of a gambler, they were able to attribute the gambler's fallacy to the mistaken belief that gambling was a fair process that would somehow correct itself in the event of a winning or losing streak.
Example
The best example of the gambler's fallacy in action is to examine it in relation to a coin toss. As you know, the chance of a coin toss landing on either heads or tails is 1:1, meaning that it is just as likely to come up tails as it is heads. So, if you flipped a coin 20 times and they all landed with tails up, under the gambler's fallacy you'd predict that the next flip is more likely to come up heads. This prediction is based on the idea that, because tails has come up 20 times, the sequence will break eventually and heads will come up.
Regardless of how many times the coin has come up heads, the probability of it being heads or tails on the next toss remains 50%; each coin toss is a separate event that is independent of the last one, meaning that previous tosses have no bearing on future ones.
Roulette Strategy Gambler's Fallacy Hasty
If you apply the gambler's fallacy to roulette, you can see how easy it is to be sucked in. For instance, the chances of the ball landing on red are 50% (or just under with the house edge). So, if the ball landed on red after 10 consecutive spins, under the gambler's fallacy you'd wrongly assume that the next spin will land on black. However, as with the coin toss, the probability of the result changing remains 50%. It's just as likely to land on red as black.
Equally, the reverse gambler's fallacy is to be avoided. In this scenario – after the coin has come up heads 20 times or the ball as landed on red 10 times – the player believes that, by some universal decree, the next toss or spin will result in the same result. Again, this disregards the probability and is simply a false assumption.
The Monte Carlo Casino Incident
One of the most famous examples of the gambler's fallacy took place in the world famous Monte Carlo Casino – part of the reason why one of the most popular synonyms for the gambler's fallacy is the Monte Carlo fallacy. During a game of roulette in 1913, the ball landed on black 26 times in a row.
While this is impressive for its high improbability, players at the casino incorrectly assumed the gambler's fallacy and bet millions of francs against black, with the reasoning that the streak was causing an imbalance that would result in a long red streak. It did not.
Gambler's Fallacy and Betting Strategies
Despite being widely disregarded, the gambler's fallacy is a major factor in a number of casino betting strategies, especially negative progressive systems. The most famous example of this is the Martingale strategy, wherein you double your even money bet (red/ black, high/ low etc) every time you lose in the hope of winning back your losses when you eventually win. Martingale is most commonly used in roulette.
The basis of the Martingale system, and negative progression strategies in general, is that you will eventually win after a series of losses, which is the same ethos behind the gambler's fallacy. In the same way that the ball could land in a red pocket 10 times in a row, you could easily lose 10 times in a row while chasing a win and exceed the table betting limits, effectively knocking yourself out of the game. This doesn't mean that negative progression systems shouldn't be used, as in some cases they can be effective, just keep the gambler's fallacy in mind and don't expect long-term profit!
Now that you know how to avoid the gambler's fallacy, why not try out one of our online casino games and put yourself to the test!
As human beings, we're naturally wired to look for patterns in the world around us. Unfortunately, this also leads to a tendency to see patterns where they don't actually exist. This tendency is at the heart of the Gambler's Fallacy, also known as the Monte Carlo Fallacy.
Roulette Strategy Gambler's Fallacy Argument
The name 'Monte Carlo Fallacy' comes from an incident in Monte Carlo in the summer of 1913, when a roulette wheel came up black fifteen times in a row. Gamblers decided that red had to come up soon, and bets on red rained down on the table. As black came up again and again, the players increased their stakes, becoming fanatically convinced that red was due. In the end, the wheel hit black twenty-six times, and the players who bet on red had been cleaned out of millions of francs.
The Gambler's Fallacy, simply stated, means forgetting that a roulette wheel, like other gambling devices, is random. The wheel has no memory, and the results of one spin have no effect on the results of future spins. As long as the wheel is fair, past results cannot be used to predict future outcomes. Even if the ball stops at 23 five times in a row, the odds of it stopping at 23 will be exactly the same for every future spin.
The Gambler's Fallacy shows up when players look for 'streaks' or 'hot' numbers. Conversely, as in the Monte Carlo example, it can also lead players to assume that a certain bet is 'due' because it hasn't won in a while.
Roulette Strategy Gambler's Fallacy Definition
In the heat of a gambling session, when you're looking for any advantage you can get to cut the house's edge, it can easy to forget you're playing an essentially random game. Don't fall into the trap of looking for patterns where there are none, or trying to predict the future based on random information.