| title | description | date | authors | |
|---|---|---|---|---|
30 Years of History - The Most Comprehensive Serie A Dataset Available |
Football open data - structured stats for journalists, analysts & managers. Updated daily. |
2025-01-31 |
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In the early 2000s, AC Milan built Milan Lab - a performance analysis system that used medical, physical, and tactical data to manage player fitness. It helped extend the careers of stars like Paolo Maldini and Clarence Seedorf. While rivals relied on instinct and tradition, Milan used data-driven insights on player fatigue, injury prevention, and tactical efficiency - leading to Champions League triumphs and Serie A dominance.
Fast-forward to today, and every high-level football professional - coaches, investors, journalists, and bookmakers - knows that data is the game behind the game.
That’s why we built the Italian Serie A Dataset, a goldmine of detailed match data from 1990-1991 to the current season designed for those who want to make smarter bets, sharper analyses, and better performance.
From tactical deep dives to investment insights, this dataset offers everything from full-time results to advanced metrics like shot accuracy, disciplinary records, and corner patterns. We value the football industry professionals’ need for reliable information on a wide range of statistics. That’s why we decided to address more than 20 variables for each game:
- Home and away team;
- Date and referee;
- Results and goals both at half-time and full-time.
For the ones looking for even more detailed information, we included also each team’s counts for:
- Total and on-target shots;
- Fouls committed;
- Yellow and red cards;
- Corners.
Last but not least, data visualization can be complex when dealing with large amounts of data, which is why you can easily consult our previews for the last five seasons of the English Premier League.
The Italian Serie A dataset is part of a DataHub project that collected and structured comprehensive data on the five major European football leagues.
Our datasets are aimed at filling the many gaps in football open sources, and we are proud to say that we now offer a reliable toolkit to back informed decision-making for any interested professional.
In each of our datasets on the five major European football leagues, we have valued:
- Labeling consistency, allowing for agile cross-season comparison from 1993 up to the present day;
- Progression, with growing available information for each season reflecting football’s evolution in thirty years;
- Synchrony, granting daily updates to our dataset for the current season through Travis-CI.
Thus, the Italian Serie A dataset is a great fit for coaches, journalists, bookmakers, and possible investors. Allowing both in-depth research about previous seasons and up-to-date exploration of the current developments, it is thought to never leave the user behind.
Although the high usability of the Italian Serie A dataset makes it accessible to fans and amateurs, it is no secret that DataHub.io engineers crafted this open-source repository with professionals in mind.
We think indeed that its depth and consistency make it highly suitable for many football-related businesses.
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Investors and stakeholders: the Italian Serie A showed interesting revenue increases in the last years, with a 21% increase just between the 2021-2022 and 2022-2023 seasons. Deloitte moreover ranked Juventus, AC Milan, FC Inter, and Napoli within the top 20 revenue-generating clubs globally.
- Data-driven money allocation
- Spotting the most consistent clubs
- Individuate possibly profitable underdogs
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Betting industry: few know that the Italian Serie A is the second most profitable league for betting in Europe, reaching €2.75 billion in 2023 - with almost half of it coming from the region Campania.
- Bookmaking support
- Individuation of profitable commercial partners
- Leverage data to maximize returns on odd wagers
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Team management: the Italian football league is particularly active in improving its data analysis capability. In 2019, all teams had access to the Football Virtual Coach software, providing real-time statistics during the game (source: Sky Sport). Nowadays, both AS Roma and FC Inter are collaborating with external for data management (Source: analyisport).
- Improve performance and organization
- Craft targeted training sessions
- Individuation of critical spots
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Journalists and content creators: the Italian Serie A is one of the most competitive leagues in the world, recently having surpassed Spain in the UEFA ranking and aiming to have two additional spots for the next Champions League (source: Tutto Atalanta). Its strong hinge on tactical aspects makes sound data crucial in crafting engaging narratives.
- Building hype before a game
- Postgame analysis
- Recalling iconic matches of the past
- Agile creation of half-time flashcards
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Advertisement: the labeling consistency of the dataset makes comparisons between teams kids play, immediately spotting both winning and goal trends. This feature can even back cross-country comparisons, as the Italian Serie A dataset is part of a broader collection including data for the European fabulous-five.
- Spot possible partnerships
- Identify the most consistent and/or spectacular teams
- Evaluate the team’s possible public appeal
To sum up, our Italian Serie A dataset makes data on football actionable and useful in supporting decision-making for a wide range of experts, from team management to the bookmaking industry.
| NAME | Italian Serie A (football) |
|---|---|
| N° OF DATASETS | 32 |
| FORMAT | JSON, CSV |
| TYPES OF VARIABLES | date, string, integer |
| SEASONS | From 1990-91 up to the current one |
| UPDATES | Daily |
| BASIC STATISTICS | Home and Away Team Date and Referee Half Time Result (HTR) Goals per team - half time (HTHTG; HTATG) Goals per team - full-time (FTHG; FTAG) |
| ADVANCED STATISTICS PER TEAM | Shots (HS; AS) Shots on target (HST; AST) Fouls committed (HF; AF) Yellow cards (HY; AY) Red cards (HR; AR) Corners (HC; AC) |
| SOURCE | Football-Data |
| AVAILABILITY | Free and open-source |
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