The SEW Sports Economics research group is happy to present its project, called Soccer Analytics. In this project we developed our own and independent forecast for the German Bundesliga. The forecast is produced using empirical methods of the so-called machine learning.
(last update 24.08.2016)
On this page we present answers to the following questions: What is the range of final rankings of a team? Who are the favourites and underdogs in each specific game of the upcoming round? How the final table of the season will most likely look like? Which teams are the positive and negative surprises of the season so far?
We provide short explantions how the predictions are calculated and provide more details under further explanations. Additionally, we present results for other interesting analyses. We provide further analyses and assess forecast quality.
Summary: Not very surprising, Bayern Munich is the favourite to win the title, with a probability of 67%. There are also favourites for the second (BVB: 45%) and the third (LEV: 32%) positions. In addition, Wolfsburg, Schalke 04 and Gladbach seem to have a better chance to achieve additional spots in the European cups tournaments. With regard to relegation fights, it seems that last season promoted teams, Ingolstadt and Darmstadt, have the highest probability to finish the season in two bottom positions, which lead to Bundesliga 2.
Rank in the final table
The graph below shows how likely every team finishes on a certain rank. To calculate these probabilities, we simulate 50,000 different seasons by a computer program based on our prediction model. If you want to know how, please read our further explanations. The interactive graph shows how often each team finished in each position at the end of the simulated seasons. In further analyses, we also show probabilities to achieve different seasonal goals.
Here fans can check the probabilities according to which their team wins, looses or draws in the next round. It is often erroneously assumed that we predict the team with higher winning probability will win. This interpretation is misleading. You should think about the presented numbers in the following way: Imagine the same teams in the same situation play against each other 100 times. Then the reported probabilities show how many of these imaginary 100 games are expected to have the respective outcome.
Final Table forecast of the season 2016/17
This presents the most likely final table according to our forecast model. As we describe in more detail in our further explanations, our model calculates the expected points for each team in each forthcoming match of the season. The sum these predicted points and the current points provide the points shown in the the table.
In further analyses, the seasonal development of each team is graphically traced.
ER: Expected rank
EP: Expected points
Over- and underperformers
The graph below shows for each team whether its achievements so far are above (green) or below (red) the expectations. The bars show the difference between actually achieved points and points that a team was predicted to achieve so far according to the model in the beginning of the season.
For questions and suggestions please contact us via firstname.lastname@example.org.