Predicting the finalists and semi-finalists of the 2020 Euros - using the ELO rating system and random forest machine learning algorithm

After nearly a year of delay, the UEFA Euro 2020 tournament is finally upon us – and the excitement at Idiro is real. Twenty-four teams will battle it out to see who will be the best in Europe. Things are finally heating up not only for the competitors but for the analysts, bookmakers, and average punters making their picks. Don’t worry we’ve got you covered. We’ve predicted the finalists & semi-finalists for this year’s competition.

Everybody has their own techniques for formulating a prediction. Whether it be extensive research of a team and player’s performance over a multitude of games or consulting their local marine life (see Paul the Octopus!). We haven’t consulted any Pundits for this prediction instead, we let AI & machine learning (prescriptive analytics) do the heavy lifting for us. We created a model based on the historical ELO rating performance of teams in the Euros. 

The ELO rating system was originally devised as a method of measuring chess players’ ratings relative to each other. 

The basic principle is that every player (training set) is given a score and whenever one player beats another they take a certain amount of points from the loser. The bigger the gap in the ELO rating, the bigger the point gain/loss, the smaller the gap, the smaller the gain/loss. Eventually, over a large enough sample of games, the future events should be obvious. 

This rating system now applies to numerous games and sports, including soccer. Using the ELO rating, random forest learning model and several other factors such as rating changes over the past year, the number of home and away matches, and the number of goals scored, we’ve created a predictive model to find our picks for who’ll make it to the finals.

Our random forest model has predicted Spain and Portugal. Both teams are sitting at around 5th and 6th for odds of reaching the finals across bet making sites – which is not bad. 

The ELO system does have limitations when it comes to team sports predictions, as it can’t account for individual performances or changes to the line-up, but it still provides a solid statistical background for making value bets. 

So, tell us what you think in the comments below? Who are you backing for the finals and would you put the house on it? 

If you like this post, here is a link to some more of our work.

 

Maurice O’Neill 
Data Scientist

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