A public results page is not necessarily a usable dataset.
A match page may show the score from a rainy Saturday in 2008, but collecting an entire season could still mean copying hundreds of rows by hand. Free to view means the result can be read in a browser; it does not mean the records are available as a file.
A CSV download, a JSON archive, or an API provides data that can be sorted and analysed without scraping pages. Before settling on a source, it is worth checking whether the download includes the needed seasons, leagues and fields—and what its terms allow.
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- Openfootball football.json
- Statsbomb open data
- Football apiBest for downloadable results, odds, and league statistics.
Football-Data.co.uk offers season-by-season CSV downloads for historical football analysis. The files can be opened in a spreadsheet to examine results—for example, the data behind record league points totals. Some files also include betting odds and other match statistics. It is a practical first stop when match-level rows are more useful than browsing individual results pages.
Community-maintained historical results available as JSON files.
OpenFootball is a community-maintained GitHub project with downloadable JSON files of historical fixtures and results. It is a useful starting point when the goal is to load schedules and scores into an app or analysis script, rather than work through odds-heavy CSVs. No match-page scraping is required.
Before relying on it, check the available competitions, inspect a file’s format, and look at the update history. A listed league may not include the seasons needed for a particular project. For missing years or a second source to compare, consult historical football statistics websites.
Best for event-level analysis of selected competitions.
A final score shows who won, but not where shots came from or how a team moved the ball. StatsBomb Open Data provides downloadable JSON files with match details, lineups, and on-pitch events for selected competitions. Those events make it possible to examine questions such as shot locations or passing patterns that results tables cannot answer.
The files take more preparation than a season CSV: matches and their event records need to be connected by match ID, and the nested JSON may need flattening before spreadsheet analysis.
Open Data covers selected competitions and seasons, not a complete history of league results. A missing event file should not be treated as a match with no shots. For long-run scorelines and totals, download football goals data from a results-focused source instead.
Subscription access to fixtures, standings, and statistics.
Sportmonks provides structured football fixtures, results, standings, and statistics through an API. It suits projects that need to run the same queries regularly and add new results alongside older records. For a broader comparison, see historical football data API options.
List the competitions and years needed. For team-level comparisons, check whether the historical records set by football teams cover the seasons in question.
Separate must-haves, such as dates and scores, from extras such as odds or event details.
Choose a format the project can use, and decide whether occasional downloads or regular updates are needed.
Count matches against an independent fixture list. Look for blank scores, duplicate games, and columns that change meaning or format.
Note the source, download date, and any gaps found. Expand to more seasons only if the test file fits.
A small trial file is easier to inspect than a full archive. If its coverage or fields fall short, switching sources early avoids cleaning data the project cannot use.
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