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The gambler’s fallacy is a type of cognitive bias related to the perception of probability. We’ll explain this misconception by illustrating some common examples before discussing the risks involved. Heed our expert advice and avoid succumbing to the gambler’s fallacy.
What is Gambler’s Fallacy?
Gambler’s fallacy is the belief that random events are influenced by previous outcomes.
The most famous example concerns roulette. The story goes that in August 1913, players at the Monte Carlo Casino witnessed an unprecedented streak of 26 consecutive black numbers. With every subsequent result, more players piled increasingly large bets on red, expecting the sequence to break. It can’t be black again, can it?
Millions of francs were lost due to this illogical and fallacious thinking.
It may sound like fiction, but this well-documented story is true. The Monte Carlo Fallacy remains a cautionary tale for all gamblers.
Gambler’s Fallacy Examples
We’ve discussed the most famous example of the gambler’s fallacy, but that was a once-in-a-lifetime occurrence. Here are some more run-of-the-mill illustrations.
Tossing a coin
Coin flips are the simplest example, as there are just two outcomes. If the coin is fair, the probability of tossing a head or a tail is 50%. But is that always true? What happens when you’ve already flipped heads ten times? We must see some tails eventually, as the chances are 50-50. Surely we’re more likely to see that on the next flip?
No. That’s the gambler’s fallacy in a nutshell. With an infinite number of flips, there’ll be a distribution of precisely 50%. But an individual coin toss is not an infinite number – it’s one isolated flip. The probability is unaffected by history.
Hot slots
If you’ve spent time around slot players, you’ll be familiar with the idea of machines getting ready to pay. There may have been some truth in that, historically, due to old-fashioned coin collection mechanisms. However, modern real money slots are computer games. They’re glorified calculators, programmed to pay a fixed percentage over time.
It doesn’t matter if the slot paid nothing in the last 20 spins. The date of the previous jackpot is irrelevant. You’re just as likely to win on this spin as any other. Theoretically, you can even win the jackpot on two consecutive spins. It’s improbable, of course – but it’s possible.
Winning streaks
Sports bettors are just as vulnerable to the gambler’s fallacy. Betting on basketball or baseball games is different from betting on roulette. The odds are not fixed due to the variables involved. A star player could be injured. The weather might come into play. Teams travel across the country, which can cause fatigue.
Becoming a successful sports bettor requires an analytical mind. Yet, many people believe in streaks. Just because you’ve won your last five bets in a row, it doesn’t mean you’ll win again next time. Nor does it mean you’re due to make the wrong pick.
Independent vs. Dependent Outcomes in Betting
To fully grasp the gambler’s fallacy, the terms to understand are independent and dependent outcomes.
Independent Outcomes
These are unconnected events, like the examples of gambler’s fallacy we just discussed – coin tosses and roulette spins, for instance. When you flip a coin, the result has no bearing on the outcome of future flips. They are independent of each other.
Dependent Outcomes
On the other hand, a dependent outcome is directly influenced by a different event. For example, when playing blackjack at an online casino, the probability of drawing another specific card changes when a card is removed from the shoe without replacement. The outcome of the second event depends entirely on the result of the previous event.
Knowing that dependent outcomes exist, it’s easy to see how our brains can be tricked into thinking all probability events are connected.
The Risks of Gambler’s Fallacy
Succumbing to the gambler’s fallacy poses two main risks, the first of which is chasing your losses.
Irrational Decision Making
If you’ve convinced yourself a random outcome is due, it’s not hard to imagine upping the stakes.
Let’s say you’re playing roulette and have placed four prior $10 bets on black. They all lost, so you’re sure a black number is coming. A winning $50 bet here would return $100, covering the prior $40 loss and leaving you $10 up overall. It feels like a sure thing.
In reality, the probability is unaffected by past results. If this poorly considered wager loses, you must place an even bigger bet to cover your debt. These exponential increases will quickly lead to ruin. You should always gamble responsibly, and with funds you can afford to lose.
The Trap of Betting Systems
Another big trap is the belief in betting systems. You subscribe to these if you succumb to the gambler’s fallacy. With a deep understanding of sports and statistics, it’s possible to beat the bookmakers. But those bets involve dependent outcomes.
It’s not possible to devise a winning system for independent outcomes, such as the toss of a coin. Most casino betting systems involve some variation of Martingale, where you progressively increase your stake after each result. This is just chasing your losses with extra steps and should be avoided at all costs.
Conclusion
The mistaken belief that random events are somehow connected – commonly referred to as the gambler’s fallacy – is surprisingly common. However, if you’re to enjoy any success when gambling, you must understand that it’s not true. Each roll of the dice, turn of a card, and spin of the wheel is entirely independent. Whatever you do, don’t fall into the trap.
FAQs
Also known as the Monte Carlo fallacy, this is the false belief that independent events are somehow linked. For example, if a roulette wheel produces nine red numbers in a row, the next one must be black, as this result is due.
The most famous example dates back to 1913, when a Monte Carlo roulette wheel produced an incredible run of 26 consecutive black numbers. Players lost millions by betting on red, mistakenly expecting the sequence to end.
Gambler’s fallacy is real. It’s a form of cognitive bias that leads to incorrect beliefs around probability. Take the toss of a coin, for instance. If you think the outcome is affected in any way by prior results, you’re mistaken.
Psychologists Amos Tversky and Daniel Kahneman link the gambler’s fallacy to believing in the “law of small numbers.” This false notion asserts that random processes will self-correct in the short term. In other words, streaks will end quickly.
First, read about the true nature of variance or randomness. Once you understand this concept, it’s much easier to consider specific events and probabilities individually. In addition, it’s essential to keep a clear head when gambling and avoid emotional thinking.
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