2018 World Cup Predictions using different methodologies

Here I share to you differents predictions analysis for know the winner of 2018 World Cup:

  • 2018 World Cup Predictions using decision trees: She using classification models over a dataset of historic football results that includes attributes from the playing teams by rating them in attack, midfield, defence, aggression, pressure, chance creation and building ability. This last training data was a result of merging international matches results with AE games ratings of the teams considering the timeline of the matches with their respective statistics. Final predictions show the four countries with the most chances of getting to the semifinals as France, Brazil, Spain and Germany while giving Spain as the winner.
  • Machine learning predicts World Cup winner (MIT): Researchers have predicted the outcome after simulating the entire soccer tournament 100,000 times. The better estimate comes from combining the odds from lots of different bookmakers. This approach suggests Brazil is the clear favorite to win the 2018 World Cup, with a probability of 16.6 percent, followed by Germany (12.8 percent) and Spain (12.5 percent).
  • Who will win the world cup? So we make the prediction of EL PAIS: The ranking has been made using the Elo method, inspired by the one used in chess and other sports. This model says that Brazil is the favorite to win the World Cup, yes, but also that it has only one option in five to win.
  • Football World Cup 2018 Predictions: Germany vs Brazil in the final, and more: FIFA world rankings, Elo ratings, TransferMarkt team value, and Betting odds are the methodologies used in this research. The results brought up some interesting takeaways: Germany come out on top, but only slightly ahead of Brazil. Following them there’s a slight gap, before Spain and France complete the top 4.
    The Elo ranking system and the betting odds appear the most similar, both naming an identical top five (the four mentioned above and Argentina). Saudi Arabia come out on bottom, ranking last for each system, bar TransferMarkt team value, who have Panama slightly below.
  • Another Prediction for the FIFA World Cup 2018: The idea is that in each simulation run of a tournament, we find team winner, runners-up, third and fourth etc. N times of simulation runs e.g. 10k returns a list of winners with highest probability to be ranked top. This model says that Brazil is the favorite to win the World Cup.
  • Sankey Diagram for the 2018 FIFA World Cup Forecast: The probabilistic forecast from the bookmaker consensus model for the 2018 FIFA World Cup is visualized in an interactive Sankey diagram, highlighting the teams’ most likely progress through the tournament.  This model says that Brazil is the favorite to win the World Cup.
  • On Elo based prediction models for the FIFA Worldcup 2018: It is based on Poisson regression models that include the Elo points of the teams as covariates and incorporates differences of team-specific effects. Based on the model estimates for single matches Monte-Carlo simulations are used to estimate probabilities for reaching the different stages in the FIFA World Cup 2018 for all teams. We propose two score functions for ordinal random variables that serve together with the rank probability score for the validation of our models with the results of the FIFA World Cups 2010 and 2014. All models favor Germany as the new FIFA World Champion.


What do you think it’s the best Predictions? Of course, for me the best predictions are that the winner is Spain 😉


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