# 5 Common Cognitive Biases that Make You Lose Money Gambling

The gambling decisions most likely to be long-term winners are the most rational gambling decisions. Sadly, most people don’t behave rationally even when they think they do. One of the main reasons people behave irrationally is because of “cognitive bias.”

What’s cognitive bias?

It’s just a fancy phrase that describes when a person’s psychology causes them to make one or more irrational decisions.

Psychologists describe multiple kinds of cognitive bias. For example, cognitive biases based on “heuristics” are common. These are mistakes that come from mental shortcuts everyone uses to understand the world and make decisions.

In gambling, the most common type of cognitive bias that affects your potential winnings and losses is the motivational bias. Most (but not all) of the 5 cognitive biases I describe in this post are motivational in nature.

The unfortunate thing about powerful psychological factors like cognitive bias is that they’re hard (and sometimes impossible) to overcome even if you’re aware of them.

I’ve read extensively about cults and brainwashing, and that’s a similar phenomenon. Studies have demonstrated repeatedly that being aware of and knowledgeable of brainwashing techniques does NOT make you immune to those techniques.

By the same token, being aware of cognitive biases doesn’t mean that you’re immune from their effects.

Here are the cognitive biases you should watch out for and thwart—if you can:

## 1. The Gambler’s Fallacy

Other names for “The Gambler’s Fallacy” include “Positive Recency Bias,” “The Monte Carlo Fallacy,” and “The Fallacy of the Maturity of Chances.” No matter what name you use for it, the phenomenon is the belief that previous results affect the probability of future results, especially when they relate to recent events.

After all, if something happens more often than probability would suggest, it seems likely that things will even out on the next events.

Sometimes the opposite belief happens. People think that something that’s happening more often will keep happening more often for a while.

But in reality, if something is random and consists of independent events, the probability of future events are unaffected by previous events.

This sounds more complicated than it is. Let me illustrate it with an example or 2:

The first example is easy to understand. You’re in a coin-flipping contest with a friend. He wins the coin every time it lands on heads, but you win the coin if it lands on tails.

The coin has landed on heads 8 times in a row.

Your friend offers to bet you $100 that the coin will land on heads on the next coin toss.

Your friend thinks that “heads” is hot, and it’s more likely to come up again on the next coin toss.

You have the opposite belief. “Tails” is due because of the results of the previous 8 tosses.

Neither.

The probability of the coin landing on heads on the next toss is exactly 50%. The probability of it landing on tails on the next toss is also exactly 50%.

Each toss of the coin is a random, independent event. The results of the previous coin tosses have no bearing on the results of the next toss.

But, wait, you say…

Isn’t it unlikely that a coin will land on heads 9 times in a row?

The answer is yes, it is.

But you and your friend aren’t betting on the coin landing on heads 9 times in a row. You’re betting on the next coin toss, which is an independent event.

Another example that’s very appropriate because of the Monte Carlo connection is a roulette example.

You’ll notice some roulette players tracking what’s happened on the previous spins. They’re hoping to find a pattern for what number is “hot” or what number is “due.”

If the ball lands on a red number 8 times in a row, some roulette players will bet on red because that color must be hot. Others will bet on black because black must be due.

But the probability of getting red or black is the same on the next spin as it was on all the previous spins. It’s a simple formula, too.

You take the number of ways you can get a black result (or a red result) and divide it by the total number of possible results.

An American roulette wheel has 38 numbers on it. 18 of them are red. The probability is 18/38, or 47.37%, regardless of what happened on the previous spins.

It’s impossible to get an edge at a gambling game when dealing with independent events based on the previous results. People who fall prey to The Gambler’s Fallacy often change the size of their bets based on this irrational thinking.

Now that you know better, you don’t have to fall prey to this cognitive bias ever again.

## 2. Ratio Bias

This describes the tendency to like large samples over small samples even when the probability is better with the small sample. This looks like a silly enough bias to someone who can do math, but it’s common among gamblers.

Most people don’t know how to calculate probability to begin with, even though it’s a simple concept. Probability is just a number between 0 and 1 that describes how likely it is for something to happen. An event with a 0 probability will never happen. An event with a 100% probability will always happen.

For example, if you toss a coin, the probability of getting a result of 6 is 0%. The only 2 results are heads are tails. Since they’re equally likely, the probability of getting heads is 50%. The probability of getting tails is also 50%. The probability of getting either heads OR tails is 100%. One of those 2 outcomes will always happen.

Let’s take a look at ratio bias though. Suppose you have a jar with 100 marbles in it, and 16 of them are black. You’re going to be on drawing a black marble out of the jar. The probability of getting a black marble is 16%. (16 divided by 100).

You have another jar with 10 marbles in it, and 2 of them are black. The probability of drawing the black marble is 20%. That’s more likely than drawing a black marble from the jar with 100 marbles in it.

Most gamblers, though, would rather draw from the jar with 100 marbles in it than the jar with 10 marbles in it, even though the odds of winning are better with the smaller jar.

I’m not sure what causes this bias, but I understand that it’s psychological and common. I suspect that it mostly has to do with the lack of experience with calculating probabilities and making decisions based on them.

## 3. Preferring the Most Likely Outcome

This one seems like it wouldn’t be an error, but it is. Gamblers prefer to bet on the outcome that is more likely to occur. At first glance, that makes sense. After all, why wouldn’t you want to bet on the outcome that’s more likely to result in a win?

But just betting on the outcome that’s more likely to win doesn’t take into account how much you’ll win. Sometimes the better bet, from an expected value perspective, is the bet that is less likely to win. The payout might be so large that your expected value is much better.

This is another example of how people who don’t understand math make mistakes based on cognitive biases.

As with the other psychological factors in this post, it’s easier to explain this with an example:

Suppose you’re choosing between 2 potential sports bets.

The first is a bet on the Cowboys to win against the Cleveland Browns. The book requires you to bet $100, but if you win, you only get $20.

On the other hand, you also have the option of betting on the Browns. If you risk $100, you stand to win $500 if they win.

The Cowboys are the clear favorite. But if you can calculate the implied odds of these bets, you can see that the bet on the underdog is clearly better from an expected value standpoint.

Let’s assume, just for giggles, that the Browns only have a 25% chance of winning.

If you bet on the Cowboys, you’ll win $20 on 3 of those bets, but you’ll lose $100 on one of those bets. Your net loss is $40. You won $60, but you lost $100.

If you bet on the Cowboys, you’ll lose $100 on 3 of those bets, but you’ll win $500 on one of those bets. That’s a net profit of $200.

But the tendency most people have is to take the bet on the Cowboys, even though it’s a negative expectation bet. The bet on the Browns has so much upside that it’s a positive expectation bet, even though you’re more likely to lose.

If you consistently make bets with a positive expectation, over the course of a lifetime, you’ll profit. If you consistently make bets with a negative expectation, over the course of a lifetime, you’ll lose money.

The tendency to bet on the most likely outcome ignores the payoff of the bets, and it results in a lot of sports bettors ignoring a lot of potentially positive expectation situations.

## 4. The Tendency to Not Bet Against the Outcome You Prefer

Not all sports bettors are sports fans, but most of them are. And there’s an overwhelming tendency for sports fans to have a favorite team. Unfortunately, when you have a favorite team, you’re much less likely to bet against them—even if it’s a really great bet.

In fact, a lot of bettors are so wrapped up in the success of their team that they’ll turn down a free $5 bet against that team.

Think about that for a minute.

Sports bettors are often so irrationally attached to their team’s success that they’ll turn down free money if it means rooting against their team. There are almost no bets available with a higher expectation than a free $5 bet.

This relates to the psychology of identity. Sports fans become so attached to the idea of being a “Texas Rangers fan” or a “Dallas Cowboys fan” that it becomes worth more than money to them.

This is the opposite of rational, by the way. If you think about it, your identification with a team is purely emotional. There’s nothing rational about being a Dallas Cowboys instead of being a Cleveland Browns fan, other than the fact that one team is more likely to win more often. (That’s the Cowboys, by the way, writes the Texan on the other end of your monitor.)

Modern online sports books often take bets on political contests, too—like elections. It’s hard to imagine being a Democrat and betting on Trump to win the 2016 election, even though the payoff was significant. Of course, he was also a notorious longshot.

At the same time, Republicans were unlikely to place a bet on Clinton, even though she was the clear favorite. No amount of changes in the payoffs or odds would be likely to change their minds.

This is also identity-based. It’s hard to justify ignoring a rational, potentially profitable bet based on this kind of identification, but that’s why it’s a cognitive bias, right?

## 5. Optimism Bias

Most gamblers tend to be too optimistic about events they’re hoping for. The classic example is the gambler who’s a big fan of the home team in a game. He’s likely to overestimate their chances of winning.

Studies have been done where fans of an underdog team in the NFL were offered even money. They often bet on their team even though the odds are against them.

This is so similar to #4 that it’s almost the same thing. It’s just the flip side of that tendency. Just as you’re less likely to bet against your favorite team or candidate, you’re also more likely to overestimate your favorite’s chances of winning.

Many Democrats probably fell prey to this one in the 2016 election. I know I did.

## Conclusion

Betting is at its most profitable when it’s at its most rational. Unfortunately, most gamblers don’t bet like Mr. Spock from *Star Trek*. We’re emotional creatures with sometimes strange and irrational psychologies.

The more you can thwart those tendencies, the better off you’ll be as a gambler. Understanding where those biases lie is the first step in overcoming them and making more rational wagers.