WORLD CUP ML MODEL (Quarterfinals edition)

Let's predict the winners of the World Cup quarterfinals using machine learning. And my model predicts that Spain will win by 1-0 and everyone thought it we were most of the round of 16 games. So let's predict France vs Spain vs Belgium, Norway vs Argentina vs Switzerland. I'm getting from the data source, filling in the gaps with the Football Data API. The type of model I built is an XGBoost, which is a bunch of stacked decision trees which work together to predict a win or a loss. And for this, I trained it on 20 distinct features which I got from multiple tournaments across La Liga, Copa America, and many more. And if you want to try my model, build models just like this one, Axon on the App Store. And if you're on Android, go to axonlearn.app. And after compiling all the model on the Spain game, giving just 51% confidence to Spain winning, with an expected score of 1-1 at the end of regular time, expected to win in either extra time or penalties. For the Argentina and Switzerland game, the model is 58% confident that Argentina will win with an expected score of 2-1. And for the France and Morocco game, the model is 55% confident that France will win. So let's see what Mbappe can do. Expected score of 2-1. Finally, for the England and Norway game, the model is 58% confident and it thinks that England will win. So let's see if the Japan theory holds up and there's an expected score of 2-1. Let me know what other predictions you want to see.