Let's turn to the dangers of confirmation bias and Gambler's Fallacy.
Confirmation bias means seeking out information that fits your already held opinion. In other words, bettors are looking for information that tells them what they want to hear. Once they find it, they end the search for more data. This is dangerous because it causes bettors to talk themselves into or out of a bet based on cherry-picked information that may not tell the whole story.
Let's say the Boston Bruins are playing the Chicago Blackhawks in Game 7 of the Stanley Cup Finals. A hockey bettor is dying to bet the game so they scour the internet for Game 7 betting trends. Does the home team have an advantage? Is the away team undervalued? Does the team off of a win carry momentum into Game 7? What is the record of both coaches in Game 7s?
An experienced bettors finds a vast list of trends that favor both teams equally with no edge either way, so they smarty decide to lay off the game and not place a bet. However, if that bettor was a Bruins fan, he would choose to focus heavily on the trends that favor Boston while completely ignoring the trends favoring the Blackhawks. This type of thought process is natural, but it should be avoided at all costs because it leads to poor decision making. Always enter a bet with an open and clear mind. Let the data decide which team is the smart bet, not your pre-existing beliefs and emotions. And remember: there is nothing wrong with laying off a bet if you can't identify and edge. There will always be more games to bet on.
In an article for the website 538 titled "The Real Story of 2016," leading statistician Nate Silver blames confirmation bias as the main reason why the media failing to predict Donald Trump's presidential victory. "Journalists just didn't believe that someone like Trump could become president.. so they cherry-picked their way through data to support their belief, ignoring evidence, such as Hillary Clinton's poor standing in the midwest, that didn't fit the narrative."
Another mistake new bettors make it falling victim to the Gambler's Fallacy. This is the widely held belief that if something happens at a high rate in a short time, it's bound to happen less often in the future. However, this just isn't true.
Let's say you flip a coin 10 times. Because the odds of a coin landing on heads or tails are 50/50, you would assume five flips would be heads and five would be tails. However, you flip the coin 10 times and notice that it lands on heads seven times and tails three times.
You automatically say to yourself: "Wow. I should bet on the next coin flip being tails because tails has only hit three times out of ten. It's bound to hit on the 11th flip." At first glance, this sounds like a logical conclusion. However, it is flawed because every coin flip is independent of previous flips. It's incorrect to assume that the probability changes based on past results. The coin doesn't abide by the law of averages over a small series of flips. In the short term, anything can happen. It might continue to disproportionately land on heads. It's only when it's compounded over a massive sample size that the law of averages takes over.
If we flipped the coin a million times, we would see a ratio close to 50/50. But if we dissect every single flip along the way to 1 million, we would almost certainly see bunches in which heads landed more than tails, or vice versa.
The Gambler's Fallacy is also known as the Monte Carlo Fallacy. It got its name in 1923 when bettors at the Monte Carlo Casino noticed the roulette ball kept landing on black. As a result, nearly everyone at the casino jumped in and kept betting red, thinking that the black streak must end. Eventually it did, but not until the 27th spin. No one knows how much money the bettors betting red lost, but legend states it was more than a million dollars.
The same Gambler's Fallacy logic can be applied to sports betting. Let's say the Chicago Cubs have the best record in baseball and travel to San Diego to take on the last-place Padres. The lowly Padres win the first two games of the series. An inexperienced bettor might go all in on the Cubs to win the final game of the series, saying to himself "The Cubs are a great team. They can't possible lose three in a row and get swept by the Padres." Sure enough, you check the final score the next morning and the Padres won 4-2. If the Cubs and Padres played 100 times, Chicago would probably win 70 of them. Over the long haul, they are the much better team and the results would bear that out, but in the short term anything can happen, just the coin landing on heads seven time out of ten.
The Gambler's Fallacy can be boiled down to this: just because a good team is on a losing streak doesn't mean they are guaranteed to win their next game. Just because a bad team is on a winning streak doesn't mean they're a lock to lose their next game. In the end, the law of averages wins out, but in the interim a streak can continue.
In conclusion, always beware of trends, confirmation bias and the Gambler's Fallacy. They will only cloud your judgment and cause you to make poor, uninformed decisions. There is no easy way out or shortcut to becoming a successful sports bettor.
If it looks too good to be true, it almost always is.