Predicting Results and Goals with Machine Learning
I have created a model to predict the outcome of the FIFA World Cup games
We are now one week deep into the FIFA World Cup 2022. More than 20 games have already occurred with some pretty “predictable” results, as well as some surprises, what is somewhat not uncommon in football (or soccer, whatever you want to call it).
A couple of days before the championship’s kick off, I started to see some posts with these nice models from other data scientists trying to predict the outcome of the games and, of course, predict the champion. After all, the World Cup is one of the most desired trophies in this sport.
For me, as a football lover (I am Brazilian, I call it football because the game is played with the feet… :-) ), I got double interested: (1) for the challenge of creating a model and practicing data science skills; (2) to work with such an interesting topic.
So, I went ahead and created a classification model to predict the result of the game (win, draw, lose). But I also wanted to be able to know the final score of the game, so I could play with my friends in those small betting competition to see who gets more results right. Therefore, I also created another model to predict that.
