After four long years, the World Cup in Qatar has finally arrived, and the Internet is going crazy. Be it your news feed or social media, everyone has something to say about it. And, of course, one of the favorite topics is who will win the World Cup.
Both football fans and statisticians come up with their predictions based on different sources, such as emotions and hard numbers. Some people rely on apps like FIFA World Cup Predictor Game or World Cup 2022 – Bracket – Calculator Qatar to calculate the outcome of this tournament.
But that’s not all: octopuses, cats, and even a psychic camel all weigh in on who will be the lucky team to bring the cup back home. No World Cup prediction would be possible without it being subject to our overlords, the AI.
Machine Learning and World Cup predictions
Luckily for us, we still haven’t reached the point where an AI can become self-aware. Without getting into much detail, it’s best to think of AI today as several different branches, all exceptionally good at certain things. One of these areas is Machine Learning.
In Machine Learning, the AI is trained with many examples and sets of data so it can better ‘predict’ something. For example, you give it a million parameters about a specific flower type, and it eventually will be able to distinguish that flower from all others.
But since nobody cares about flowers and we all care about who will win the World Cup, Machine Learning has been tasked with determining who will be the lucky winner. Our future masters have a couple of interesting things to say.
Brazil’s the favorite
Well, we didn’t need an AI to guess that one. But it’s still interesting to know why different Machine Learning models all reach the same conclusion.
Here’s an excellent example for Python programmers on how to build a model to predict the winner. In case programming’s not your thing, it’s still interesting to know why machines come to this conclusion. In this case, the developer collected all data from World Cup matches since 1930 and their goals. Then, using a mathematical formula that he considers fitting with these events, let the machine run and predict.
The final is Brazil vs. France, with Netherlands and Portugal losing in the semi-finals. This end result is also backed by the Alan Turing Institute, which, using other parameters, reached the same conclusion.
Argentina, France, and the Netherlands lag behind
In most models, Brazil wins the World Cup. Nevertheless, there are quite a few who place good odds on Argentina being the champion, followed by Netherlands, Germany, and France. For instance, the University of Innsbruck ran 100,000 simulations to reach this conclusion.
Some Machine Learning enthusiasts clarify that odds are very important. For example, in this model, the match between Argentina and Netherlands offers just a 1% of advantage for the latter. This is a very low percentage, which means Argentina has a 49% chance of winning the match. As you can see, tables can turn into matches like that at any moment.
Interestingly, most researchers mention that these results don’t differ much from what common sense predicts. These teams are regular favorites in each World Cup, and it’s no wonder, other teams, perhaps with less soccer tradition, have very low odds of winning. For example, in some models, the USA team only has a 0.6% chance of winning the World Cup.
There are many unpredictable factors in this year’s World Cup
Most of these predictions are based on purely statistical facts. This means they evaluate how they won, how many goals for and against they had, and other parameters. There is no way of knowing if a key player will get injured, which can completely change the outcome of a game.
Researchers also mention this World Cup is of particular interest because it’s held in November, unlike previous World Cup tournaments, which are held in the Summer. This is a new variable, and nobody knows how it will impact teams.
For instance, players from some countries may have had less resting time from their local tournaments, which would put them at a disadvantage. Weather is another issue. Will the dry and hot Qatar weather influence the outcome? Very likely, yes, but nobody knows how.
Is it safe to bet your life on it?
While the technology behind Machine Learning is impressive, always remember they’re models. This means it may or may not adjust to reality. So if you were considering mortgaging your house to place a bet on Brazil, you better think it through.
The fact is that probabilities are just that, probabilities. Let’s analyze the case of the University of Innsbruck, which ran 100,000 simulations. The fact that Brazil’s odds are 15% means that, for every hundred simulations, Brazil won 15. That is, 85 other teams won the rest. Not so great when you think about it from this perspective, huh?
Of course, as the World Cup progresses the odds will change, as with any sports event. Then, it’s likely that one team will stand out with even more chances of winning than right now. But perhaps by then, your dog might have predicted the outcomes better than any other model.
And it will be a grand day when living beings defeat machines once more.