International Football Match Results
1872–March 2026
Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- Not documented — confirm reuse terms with the seller
- Source / creator
- Not documented
- Collection method
- Supplier description: 20 columns across 49,215 rows. Sourced from publicly available international football records, enriched with confederation mappings, tournament tier classifications, and computed analytics fields. Ideal for sports analytics, historical trend analysis, prediction modeling, and FIFA ranking research.
- Coverage / snapshot
- 1872–March 2026
- Data last updated
- Not documented
- Update schedule
- Not documented
Sample structure score: 100 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 10 sample records (CSV) on 2026-10-09. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 50 / 50 | 200 of 200 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 30 / 30 | 200 of 200 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| date | 0 / 10 | string | 0 / 10 |
| year | 0 / 10 | number | 0 / 10 |
| decade | 0 / 10 | string | 0 / 10 |
| month | 0 / 10 | number | 0 / 10 |
| home_team | 0 / 10 | string | 0 / 10 |
| away_team | 0 / 10 | string | 0 / 10 |
| home_score | 0 / 10 | number | 0 / 10 |
| away_score | 0 / 10 | number | 0 / 10 |
| total_goals | 0 / 10 | number | 0 / 10 |
| goal_difference | 0 / 10 | number | 0 / 10 |
| result | 0 / 10 | string | 0 / 10 |
| tournament | 0 / 10 | string | 0 / 10 |
| tournament_tier | 0 / 10 | string | 0 / 10 |
| city | 0 / 10 | string | 0 / 10 |
| country | 0 / 10 | string | 0 / 10 |
| neutral_venue | 0 / 10 | boolean | 0 / 10 |
| home_confederation | 0 / 10 | string | 0 / 10 |
| away_confederation | 0 / 10 | string | 0 / 10 |
| match_type | 0 / 10 | string | 0 / 10 |
| penalty_shootout | 0 / 10 | string | 0 / 10 |
About this data
49,215 international soccer match results spanning 150+ years across 333 national teams and 193 tournaments. Each record includes match date, teams, scores, tournament tier, venue, confederation, and penalty indicator. Sourced from public records with added confederation mappings and computed analytics fields.
Retrieve with your agent or Python
Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.
Download the Python examplepython3 retrieve-dataset.py e9f0cefb-7269-4468-a779-f9cb047fc75c --output dataset.bin
Full supplier documentation
Schema
| Name | Type | Description |
|---|---|---|
| date | string | |
| year | string | |
| decade | string | |
| month | string | |
| home_team | string | |
| away_team | string | |
| home_score | string | |
| away_score | string | |
| total_goals | string | |
| goal_difference | string | |
| result | string | |
| tournament | string | |
| tournament_tier | string | |
| city | string | |
| country | string | |
| neutral_venue | string | |
| home_confederation | string | |
| away_confederation | string | |
| match_type | string | |
| penalty_shootout | string |
Sample Data
Preview a sample of the data before downloading.
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For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "International Football Match R" })
// Found: e9f0cefb-7269-4468-a779-f9cb047fc75c
get_download_url({ dataset_id: "e9f0cefb-7269-4468-a779-f9cb047fc75c" }) // free — sign in with MCP OAuth first# Free dataset — sign in or use your account API key: curl https://api.databazaar.io/datasets/e9f0cefb-7269-4468-a779-f9cb047fc75c/download-url -H "Authorization: Bearer $DATABAZAAR_API_KEY"