When we bet at the top offshore sportsbooks, we tend to focus completely on the games that interest us. But we lose sight of something that’s so close to us and so important: our own minds.
To be successful gamblers, to make our betting choices wisely, we have to appreciate the fact that it is we humans who are making these choices.
As humans with human minds, we are subject to psychological tendencies that influence our choices to such a significant extent that they can mislead us and induce us to make poor decisions with our bankrolls.
One of those psychological tendencies is the gambler’s fallacy.
Be Aware
We need to be aware of the gambler’s fallacy to become more successful gamblers.
So let’s define the gambler’s fallacy and provide examples before exploring ways to avoid it.
What Is The Gambler’s Fallacy About?
The gambler’s fallacy is a misjudgment of the probability of specific outcomes.
In the case of this fallacy, misjudgment occurs when one considers the relation of previous events to future ones.
What Gambler’s Fallacy Is Not
Sometimes, previous outcomes do determine the outcomes of future events. For example, let’s say that I have ten coins in a bag. Four coins are quarters, three are nickels, two are dimes, and one is a penny.
If I first remove a penny from the bag, then it is not an instance of the gambler’s fallacy to believe that I will not remove a penny from the bag when I reinsert my hand into the bag.
It is likewise not an instance of a gambler’s fallacy to believe that it is likelier that I will pull out a quarter, nickel, or dime.
The point here is that a dependent event influences the outcome of a later event. The first event changes the probability of certain things taking place.
Defining The Gambler’s Fallacy
The Gambler’s Fallacy is when you judge an event to be more or less likely because it follows from a random or independent event.
A random or independent event does not influence the statistical likelihood on whether certain specific events take place. It is a fallacy to believe in such a statistical relation between random or independent events and other events.
An Example
For example, let’s say that I have a coin and flip it. If it lands ten times on heads, I might think that, when I flip it again, it will certainly land on heads.
There are two things to note here.
This is a fallacy because, whenever I flip a coin, I have a 50 percent chance of getting heads or tails. Coin-flipping is an independent event because my chance of receiving heads or tails is always 50 percent.
No matter how many times I’ve already flipped the coin, the statistical probability of receiving heads or tails remains 50 percent.
Now, if I have not flipped any coins and if, upon planning to flip a coin ten times, I try to predict how many times the coin will land on heads, I can reasonably predict that the coin will land on heads five times.
While I am guessing the outcome of events, this is not an instance of gambler’s fallacy, because I am not misjudging the likelihood of any one coin-flip landing on heads or tails.
The Relevance to Sports Betting
The gambler’s fallacy is relevant to sports betting because we are trying to predict the outcome of specific events. To make these predictions, we often use the past as a guide.
For example, if the Titans beat the Colts eight times in a row, then we might be likelier to think that they will certainly beat the Colts again.
If the Yankees beat the Astros yesterday 17-0, we might think that the Yankees will score a lot of runs and beat Houston the following day.
The question of whether this is an instance of the gambler’s fallacy revolves around the statistical relationship between the Yankees’ 17-0 triumph yesterday and the Yankees-Astros game that is about to take place.
We have to ask: is the relationship between these two events like our example with the ten coins in the bag or like our example with flipping coins?
How To Avoid The Gambler’s Fallacy
This gets to the heart of the issue of avoiding the gambler’s fallacy. We have to ask what sort of objective basis can we locate in our analysis.
There have to be reasons to expect continuity that extend beyond a glance at the mere result. After all, a look at any team’s schedule in any sport indicates a wide variety of outcomes.
History Might Not Repeat Itself
Just because something happened in the past does not mean that it will repeat itself unless certain conditions responsible for those results repeat themselves.
For example, if the Packers beat the Vikings by 20 points, we should consider why they won by 20 points before we think that, because they won by 20 points, they will do so again.
If they won because their opponent missed its starting quarterback, then this item of knowledge can reasonably contribute to our certainty that, in the rematch, this result will repeat itself.
Granted, a football game is generally much more complicated than that it is the consequence of a single quarterback’s performance. Plus, quarterbacks perform differently in different games. So many different variables can change, that our expectation of the same result would have to run much more deeply.
If the rematch is played in the same location, if the players remain of equal ability — for example, if the backup quarterback still plays again and hasn’t progressed — then we can be more certain that the result will repeat itself.
Takeaways
One of the key takeaways from this discussion is that trends do not blindly repeat themselves.
However, certain key objective reasons can exist to explain them.
For example, maybe one defensive coordinator is just too start for a certain team’s quarterback, so he always and reliably struggles against that defense.We have to search for logical explanations to help predict the outcome of specific events.
