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Match Forecasts for FIFA World Cup

After the disappointing last World Cup, will Germany actually manage to fight back and compete for the title? Which nations will be the toughest competitors? Are there “secret favorites”? Univ. Prof. Dr. Daniel Memmert, Professor at the Institute of Exercise Training and Sport Informatics, conducts research on forecasts for football results.

Together with the mathematician Dr. Fabian Wunderlich, who is an expert in sports betting and has successfully finished his dissertation on the subject of sports forecasting and the usefulness of betting odds in sports science, they have developed a forecasting model that calculates the probability of each team to win individual matches or to be the World Cup Champion. These forecasts are published on a daily basis at FAZ.NET – being a perfect preparation for any betting game.

Please follow this link and you will find the links to the current match forecasts every day!

 

Background information

  • Who conducts the World Cup forecast?

Daniel Memmert is a Professor and Executive Head of the Institute of Exercise Training and Computer Science in Sport, German Sport University Cologne, Cologne, Germany, with a visiting assistant professorship 2014 at the University of Vienna (Austria). He studied maths and physical education for high school teaching and has trainer licences in soccer, tennis, snowboard, and skiing. Memmert received his PhD (basic cognition in team sports) and habilitation (creativity in team sports) in sport science from the Elite University of Heidelberg. In 2010 he was awarded 3rd place with Germany's most renowned German Olympic Sports Confederation (DOSB) Science Award. His special research areas of interests are cognitive science, human movement science, computer science, and sport psychology. He has 24 years of teaching and coaching experience, has an H-index of 58 (i10-Index 181), and has authored or co-authored more than 300 publications, 30 books and 30 book chapters, and he is an ad-hoc reviewer for several international psychology and computer science journals. He collaborates with researchers from the US, Canada, Brazil, and Spain. He transfers his expertise to business companies, the German Football National Team (DFB), and professional soccer clubs (e.g., 1. Bundesliga, Champions-/European League) and organize the first international master in “Performance Analysis/Game analysis”.

Fabian Wunderlich holds a Master’s degree in Business Mathematics, has worked in the sports betting industry for several years and successfully finished his dissertation on the topic of sports forecasting at the German Sport University Cologne. His primary area of expertise is the application of methods from computer science and mathematics to sports-related data. His research focuses on sports forecasting, sports betting, the use of betting odds in sports science as well as random influences in sports games.

Together, they have published a review article on sports forecasting (https://doi.org/10.1080/17461391.2020.1793002) and demonstrated the high random influence in football that ultimately makes forecasting a highly complex task (https://doi.org/10.1080/02640414.2021.1930685). In addition, they know about the excellent predictive power of betting odds and have studied the usefulness of betting odds for analysing performance and team strength of football teams (https://doi.org/10.1371/journal.pone.0198668). Other recent studies focus on the extent to which positional data (https://doi.org/10.1038/s41598-021-03157-3) or social media data (https://doi.org/10.1007/s13278-021-00842-z) can improve football forecasting models.

  • How does the method work?

In numerous studies, researchers have analysed a wide variety of methods that can be used to forecast the results of football matches. Typical examples of information that can be used for this purpose are previous results, official rankings, market values of players or betting odds.

As each fan may have his own preference on which information to trust, we will present information on four different aspects:

  • The performance in the last World Cup 2018.
  • The position in the FIFA World Ranking, which (since 2018) is based on the mathematical concept of Elo rating.
  • The market value of the team based on the website www.transfermarkt.de.
  • A percentage forecast based on data from the betting market.

The betting market in particular has been found to be a very accurate way to forecast sports events including football matches.

Several reasons may explain this finding: First, forecasts are the business model of bookmakers, who have a high financial incentive and the expertise to forecast them accurately. Second, in the betting market a large quantity of agents come together (different bookmakers, professional sports bettors and a huge number of recreational sports bettors). Thus, the final betting odds can be assumed to be a collaborative estimation of many agents, which (known as the concept of crowd wisdom) are usually much better than the estimation of individual experts. Third, the betting market can consider all relevant information, unlike other sources of forecasts such as rankings or previous results. In particular, this includes aspects like the home advantage, the tournament draw, psychological factors, the current squad and injured players.

From the data of the betting market, we can derive various probabilities, which we summarise in the World Cup forecast.

  • The overall tournament forecast, i.e. the probability of each national team to win the tournament, which obviously is adjusted during the tournament and in response to the results.
  • The forecast for each match, i.e. the probability of the outcome of each of the World Cup matches (win team 1, draw, win team 2).
  • For knockout matches, additionally the probability of advancing to the next round including possible extra time and penalty shootout.

Currently, the betting market considers Brazil (approx. 17% probability of victory) as the number one favourite, followed by France and Argentina (each approx. 12%) and England (approx. 10%). Germany is also not considered an outsider with about 8% probability to win the title. We will update these numbers again immediately before the start of the tournament and publish them in the FAZ.