'Kicker' & Driblab: salary expenses and advanced statistics in the Bundesliga

'Kicker' & Driblab: relationship between spending and advanced statistics in the Bundesliga

There are many ways in which advanced data can be used to draw conclusions, make decisions or perform interesting journalistic analysis. Without going any further, the German newspaper 'Kicker', in its pages focused on business, has made a report connecting the efficiency in spending of the Bundesliga clubs with the expected points and points achieved according to Driblab's models.

The purpose of this collaboration was to explain how much it cost each team to generate a point in the standings and how profitable and efficient their spending was based on two variables, expected points and points scored, and to see which teams scored more points while spending less. The benchmark was the spending on salaries for the 2021-22 season (both first team squad and club staff).

In the table attached at the end we can see, on the one hand, the difference between the expected points of each team, depending on the merits accumulated in each match through the generation of own chances and chances against, and the total points obtained. On the other hand, the salary expenses and what differential, positive or negative, each team had between its league ranking and its budget among all the teams.

The Expected Points model starts from the Expected Goals of a match. Once we have the xG of each team, we elaborate, through a distribution model, what would have happened if we simulated the same match thousands of times, getting to know, precisely, what probability each team would have to win, draw and lose with the same expected goals generated.

In this way, we obtain a probability percentage for each team and sign (win, draw, opponent's win). The data is available to explain reality in a multitude of areas. This is one of the many new ways to generate valuable journalistic content applied to football.

Founded in 2017 as a consultancy, Driblab has driven innovation through data in all aspects of professional football. Thanks to a transversal model, its database collects and models statistics in all directions. From converting matches and videos into bespoke data for training academies to developing cutting-edge technology, helping clubs, federations and representative agencies in talent scouting and transfer markets. Driblab’s smart data is used by clubs all over the world, with success stories such as Dinamo Zagreb, Real Betis and Girondins Bordeaux among others. Here you can find out more about how we work and what we offer.

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