Gambler's Fallacy and Betting

The Gambler’s Fallacy: How it Applies to Betting

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The Gambler’s Fallacy is the concept created by Jacob Bernoulli roughly 400 years ago that came to the conclusion that the larger the sample size the more accurate it will be in giving you a true probability.

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The most common example used is the coin toss, which he believed if done relentlessly the results will roughly even out to 50-50 for heads and tails. But this isn’t necessarily true, as tossing a coin is pure chance and each action has an independent outcome. This subsequently makes it unlikely that it’ll be an even split for heads and tails no matter how big your sample size is.

Courtesy of Sports Betting Dime

Courtesy of Sports Betting Dime

Many wagerers have been known to transfer this theory into sports betting too, which can be a dangerous thing to do. Using the law of averages, many use the principle that a streak of wins will be followed by a streak of losses, but in reality the team you’re betting on could keep winning too.

Courtesy of Ol Advisors GamblingCourtesy of Ol Advisors Gambling

Applying this theory essentially suggests teams would end up with the same number of wins and losses during a season, which is clearly not always the case.

This line from BetLabs offers some excellent insight into the topic, stating: “When it comes to probability, a lack of understanding can lead to poor decision making. The best way to avoid the gambler’s fallacy is to understand the difference between independent and dependent events.”

Courtesy of Sports Betting Dime-2Courtesy of Sports Betting Dime

With all this in mind, undertaking a more thorough analysis of every selection you make using proven strategies is a far better way to go about your betting, instead of using the aforementioned method that relies more on luck and chance.

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