You can make your sports predictions any which way you want, whether that’s based solely on gut feelings or hours of research using mathematics, psychology, and a hint of intuition. Obviously one method is better than the other, and if you’re looking to get better at making sports predictions and be as good as the algorithms used by the pros, you need to master these three things.
Understanding Probability and Randomness
At the foundation of any sports prediction lies a very basic truth: no outcome is ever certain. The most fundamental step toward making better predictions for champions league betting or any other sport, for that matter, is embracing probabilistic reasoning. Even in matchups where one side is completely outmatched, there is still the chance for an upset. Anything from an injury on the field to strategic blunders can cause your “sure” bet to be a losing one.
This is where you need to get a sense for expected value, or a combination of how likely your prediction is to be right and the value of the different potential outcomes, such as your bet being right or not. If you’ve played poker, you know that EV is a huge part of the decision-making process, and even if your gut is telling you one thing, EV may force you to go the other way, as it is a more mathematically sound way to think about the game and your predictions.
Another note about probability to mention is to never think that something is “due”. This is the equivalent of betting on 17 at a roulette table because it hasn’t come up in the last 100 spins, so it must be “due” to come up. If a team is on a losing streak, they’re not “due” for a win at any moment in the future. They’re due for a win when their skills and players earn them one, and that can be predicted with data and statistical models.
Using Data and Statistical Models
Modern sports predictions are data-driven more than ever. With computers getting more powerful by the day, data points for sports number in the millions and are routinely crunched by algorithms to help determine who might be the winner of the next matchup.
While you can let computer programs do the hard work for you, it helps to be literate in basic statistical techniques like regression analysis and probabilistic simulations. If you don’t have the mind for stats, machine learning models trained on years of performance data are available, but it does help to understand the basics of stats if you want to get better at predicting sports outcomes.
Avoiding Cognitive Biases
We already mentioned one cognitive bias you need to avoid as a sports bettor, which is to never think a team or player is “due”. However, there are other things to look out for as well. Confirmation bias and recency bias are two others to avoid.
Confirmation bias is where you look for information that confirms your own beliefs, so if you think Team A is going to win, you start reading articles talking about why Team A is on a hot streak rather than looking at the potential of Team B or how Team A might fare differently in this situation.
Recency bias, on the other hand, is exactly what it sounds like: the tendency for us humans to overemphasize the importance of recent events. Recent wins or losses should be taken into account, but just because Team A wiped the floor with Team B, it doesn’t mean they’re going to do it again the next time they face off against each other.
It helps to keep a journal of your predictions and to analyze what went wrong or what went right. Pre-mortem techniques, where you imagine how a prediction might go wrong and identify factors that could cause your expected outcome not to come to fruition, is a great exercise to help avoid cognitive biases.
