FIFA World Cup 2018 Machine Learning Predicts the Possible Champion
Winners Of FIFA: Germany, Brazil, Or Spain; Machine Learning Shades Some Light

Will the last year’s winners be able to defend their cup this year? Or will Brazil take revenge for its shameful defeat of 1-7? Or will Spain become champions after 8 years? Who knows! FIFA 2018 is giving World Wide Web hard time as fans from all over the world are searching for anything that is remotely related to FIFA. The finale of FIFA is most likely to become the most widely viewed sports event in the history. Every fan has turned into a seer, predicting the possible winner of the World Cup. However, scientists at the Technical University of Dortmund in Germany took a helping hand of machine learning to pinpoint the champion of FIFA 2018.

The most widely used approach is by going through the statistics of bookmakers. These organizations use professional statisticians to predict the winners of any match that will kick off in the next few weeks. They hold huge databases, by using they analyze and conclude the probability of a certain team’s win and their odds to do so. According to several bookmakers, Brazil is the most favorite winner of FIFA 2018, followed by Germany and Spain. The craze of machine learning made its mark on FIFA world too. Machine-learning techniques outperform the traditional statistical approaches and for that reason, Andreas Groll and his team at the Technical University of Dortmund in Germany created a novel technology to foresee the outcome of this year’s football World Cup. The team used a combinational machine-learning method known as a random-forest approach to identify the most-likely winner.

The random-forest method is a recent breakthrough to analyze the large database by avoiding downsides of data-mining. The usual method is based on the idea that the outcomes of future events can be determined by calculating each outcome with some set of training data. However, the random-forest method does not calculate every possible outcome but considers random outcomes. Groll and his colleagues used this approach, by considering several factors that affect the outcome such as country’s GDP, population, FIFA’s ranking of national teams, the average age of team players, number of Champions League players in a team, and whether a country has a home advantage or not.

Plugging all these factors, the machine-learning algorithm predicts that Spain is the most likely winner, with a probability of 17.8 percent. However, there are several factors to consider. Germany is likely to face strong opposition while clearing the group phase of the tournament, but Spain does not have a strong competitor in its group. Statistically speaking, Germany has 58 percent of chance of reaching quarter-finals whereas Spain has 73 percent chance. If both somehow make it to quarter-finals, they have about equal chance of winning. However, Spain is the most likely winner as Germany will have to tackle strong opponents and high chance to drop out in knockout matches.

However, Groll has conducted this experiment 100,000 times and there was the result when Germany wins the FIFA World Cup. However, according to Groll, Germany’s odds are 1 in 100,000. So, there you go. Place your bets on Spain as it is a clear winner according to the machine. However, if Germany qualifies for quarter-finals, it will become the first runner, making it difficult for machines to predict the outcome. And who knows, Germany may prevail again.


  1. I am curious to find out what blog system you’re utilizing? I’m having some minor security issues with my latest blog and I would like to find something more safe. Do you have any solutions?

  2. Greetings from Carolina! I’m bored to death at work so I decided to check out your blog on my iphone during lunch break. I love the info you present here and can’t wait to take a look when I get home. I’m surprised at how quick your blog loaded on my phone .. I’m not even using WIFI, just 3G .. Anyhow, wonderful site!

  3. The root of your writing while appearing reasonable in the beginning, did not really work properly with me after some time. Someplace within the paragraphs you managed to make me a believer but only for a while. I still have got a problem with your leaps in assumptions and you would do nicely to help fill in all those breaks. If you actually can accomplish that, I could undoubtedly be amazed.


Please enter your comment!
Please enter your name here