Three decades of detailed Bundesliga statistics

You might not know this yet, but the German Bundesliga is the most technologically advanced European league when it comes to data analysis and innovation. This is especially true in fan engagement and narrative building - an intriguing angle that sets it apart as a truly unique football league.

Think I’m exaggerating?

The Deutsche Fußball Liga, responsible for the league’s management, is currently actively involved in the implementation of IT in four core areas:

1. Creation of Match Facts with AI-powered fan engagement;
2. AI Live Ticker, a system creating compelling live commentary for matches;
3. Streamlining the media production process with generative AI;
4. Data-driven player performance and coaching.

Especially in a highly demanding environment such as modern football, control over the match statistics is what sets professionals apart from bare amateurs. That’s why DataHub.io decided to create a database for the German Bundesliga, encompassing over 30 seasons of detailed information on one of the major European leagues.

1. The German Bundesliga dataset identikit

Let's cut to the chase: what will you find in our German Bundesliga dataset collection?

DataHub.io provides Bundesliga data spanning from the 1993-94 season to the present. The variables covered are progressive, offering increasingly detailed and extensive data as more information becomes available each season. The current dataset, updated daily, includes over 20 variables per game.

Football professionals need clear, in-depth, and constantly updated insights about matches. With that in mind, our dataset starts with basic match details - such as teams, dates, and referees - before diving deeper into match dynamics:

• Results and goals at half-time and full-time;
• Total and on-target shots per team;
• Fouls committed per team;
• Yellow and red cards per team;
• Corners per team.

To give you a preview of the data structure, we've included five full dataset samples covering the 1996 to 2000 seasons.

2. Highlights - The dataset features

The German Bundesliga dataset belongs to a broader collection that DataHub.io wrapped, including all the information football professionals chase with curated datasets for the five major European leagues.

With our comprehensive datasets, we fill the gaps in current football open-source data, offering a sound toolkit to inform decision-making that suits both football statistics amateurs and high-ranking professionals. Bearing the goal of sharing perfectly clean data in mind, our datasets guarantee:

• Labeling consistency, making cross-comparison agile both transnationally and temporarily;
• Progression, with growing available information for each season reflecting football’s data evolution in thirty years;
• Synchrony, with daily updates currently runs through Travis-CI.

We take pride in providing data that caters not only to passionate fans but also to coaches, journalists, bookmakers, and potential investors.

How? By allowing a seamless combination of in-depth research on past seasons with real-time analysis of current developments, guiding each user on their unique journey inside the world’s most popular sport.

3. How to use the German Bundesliga datasets

Let’s talk business: our data engineers have designed all our football datasets with professionals in mind. The German Bundesliga dataset is no exception, with its depth and consistency making it a valuable asset for various kinds of football-related businesses.

Now, let’s explore the specific ways professionals in the football industry can leverage the DataHub.io dataset:

• Investors and stakeholders: in the 2022/23 season, Bundesliga clubs experienced significant revenue growth of 22%, reaching a total of €3.8 billion. This increase was the largest among Europe's 'big five' leagues. Notably, Borussia Dortmund's revenue grew to €514 million in the 2023/24 season (source: Deloitte), possibly representing a good business partner.

  • Data-driven money allocation
  • Spotting the most consistent clubs
  • Individuate possibly profitable underdogs

• Team management: alongside the general Deutsche Fußball Liga AI-led innovation through the glass-to-grass strategy, Bayern Munich has been the first team to openly invest in a dedicated data analysis department led by Michael Niemeyer, that directly advises the coach and technical staff about possible. This decision was taken abroad also by Manchester City and AS Roma amongst others.

  • Improve performance and organization
  • Craft targeted training sessions
  • Individuation of critical spots
  • Matchday preparation

• Marketing and advertisement: sports narratives and their publicities are at the center of Bundesliga priorities, as also shown by the AI-based commentary partnership with Amazon Web Services. Can the German league be a good showcase? Suffice it to say that in the 2023-24 season, media accounted for 34% of its total revenues (source: Statista).

  • Spot possible partnerships
  • Identify the most consistent and/or spectacular teams
  • Evaluate the team’s possible public appeal

• Betting industry: according to Grand View Research, the European sports betting market was valued at approximately USD 33.75 billion in 2023 and is projected to grow at a compound annual growth rate (CAGR) of 9.9% from 2024 to 2030. German Bundesliga is not among the top-rated betting leagues, which may represent a challenge, but also a gambling market with less competitors.

  • Bookmaking support
  • Individuation of profitable commercial partners
  • Leverage data to maximize returns on odd wagers

• Journalists and content creators: as we have already mentioned, the German Bundesliga puts a strong stress on football narratives, coming to the point of implementing AI to generate compelling live commentaries of the matches. However, match statistics are still the main pillar to write high-level specialized articles.

  • Building hype before a game
  • Postgame analysis
  • Recalling iconic matches of the past
  • Agile creation of half-time flashcards

All in all, our German Bundesliga datasets make data on football actionable and useful in supporting decision-making for a wide range of experts, from team management to the bookmaking industry.

4. Recap table

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