⚽ OpenLigaDB Bundesliga Public API Scraper

🚀 Export Bundesliga and 2. Bundesliga matches, goals, scorers, and tables, straight from the public OpenLigaDB API.

🕒 Last updated: 2026-06-05 · 📊 14 fields per record · Bundesliga, 2. Bundesliga, 3. Liga, DFB Pokal · All seasons since 2002 · Matches, scorers, tables

The OpenLigaDB Bundesliga Public API Scraper turns the api.openligadb.de public endpoint into a clean dataset. It calls the public API with whichever filters you supply, then flattens each record into one row.

Coverage spans bundesliga, 2. bundesliga, 3. liga, dfb pokal · all seasons since 2002 · matches, scorers, tables. Each row carries the most useful identifiers, names, scores, and timestamps the upstream feed exposes.

🎯 Target Audience	💡 Primary Use Cases
⚽ Bundesliga fans	Pull every fixture and result
📊 Fantasy soccer GMs	Drive Bundesliga lineup tools
📰 German football journalists	Verify results and scorers fast
🎓 Sports historians	Mine two decades of German football
🤖 ML engineers	Train xG and result models on German data
👩‍💻 Developers	Mirror OpenLigaDB into apps

📋 What the OpenLigaDB Bundesliga Public API Scraper does

• Calls /getmatchdata/
• Exposes home and away team, score, group, location, and matchday.
• Supports the bl1, bl2, bl3, dfb leagues and any season since 2002.
• Casts numeric ids cleanly.
• Surfaces upstream errors as a clean error record.

💡 Why it matters. OpenLigaDB is the canonical free dataset for German football. This actor flattens its match payload to one row per match.

🎬 Full Demo

🚧 Coming soon.

⚙️ Input

Field	Type	Required	Description
league	string	No	See examples below.
maxItems	integer	No	Free users 10, paid up to 1,000,000. Prefill is 10.

Example 1, Bundesliga 2023 matchday 1.

{ "league": "bl1", "season": "2023", "matchday": "1", "maxItems": 9 }

Example 2, 2. Bundesliga season 2023.

{ "league": "bl2", "season": "2023", "maxItems": 50 }

⚠️ Good to Know. The OpenLigaDB API is public and free, no key required.

📊 Output

Field	Type	Description
🆔 matchId	number	OpenLigaDB match id.
🏆 leagueName	string	League name.
🔤 leagueShortcut	string	League slug.
📅 matchDateTime	string	Match kickoff time.
🗓️ matchday	string	Matchday or group name.
🏠 team1	string	Home team.
✈️ team2	string	Away team.
🔢 goalsTeam1	number	Home goals when finished.
🔢 goalsTeam2	number	Away goals when finished.
🏟️ location	string	Stadium when present.
✅ finished	boolean	Whether match is finished.
🥅 scorers	array	Goal scorer summaries.
🕒 scrapedAt	string	When fetched.
❌ error	string	Set when upstream returned an error.

Sample record.

{
  "matchId": 0,
  "leagueName": "",
  "leagueShortcut": "",
  "matchDateTime": "",
  "matchday": "",
  "team1": "",
  "team2": "",
  "goalsTeam1": 0,
  "goalsTeam2": 0,
  "location": "",
  "finished": false,
  "scorers": [],
  "scrapedAt": "2026-06-05T12:00:00.000Z",
  "error": null
}

✨ Why choose this Actor

| 🆓 | Public OpenLigaDB endpoint, no scraping tricks needed. | | 🧹 | Flattens nested upstream payloads into one row per record. | | 🔢 | Casts numeric fields cleanly for spreadsheet imports. | | 🛟 | Surfaces upstream errors as clean rows. | | 🔌 | Filters exposed for the most common slicing needs. | | 💾 | Push to dataset for spreadsheet, warehouse, or webhook export. |

📈 How it compares to alternatives

Approach	Setup	Pagination	Flattening	Export formats
Raw curl	5 min	manual	none	manual
DIY Python script	30 min	yes	partial	code
This Actor	5 seconds	yes	yes	7 formats

🚀 How to use

1. Click Try for free.
2. Pick your filters from the schema above.
3. Click Start. Your dataset is ready in seconds.

💼 Business use cases

📊 Analytics. Mirror OpenLigaDB into a warehouse for dashboards.

🏢 Internal tooling. Mirror the data into private apps without writing client code.

📰 Journalism. Verify and bulk-fetch records for stories.

🤖 Machine learning. Build training sets from a known canonical source.

🔌 Automating OpenLigaDB Bundesliga Public API Scraper

• Make / Zapier: schedule a daily run.
• Cron schedule: native Apify scheduler.
• Webhooks: POST on completion.
• Warehouse pipe: native integrations move datasets straight into BigQuery, Snowflake, or Postgres.

🌟 Beyond business use cases

🎓 Education. Teach API integration with a clean dataset.

🧪 Personal research. Track the data you care about.

🤝 Non-profit and open data. Power public dashboards.

🧰 Tinkering and prototyping. Spin up a feed for side projects in seconds.

🤖 Ask an AI assistant about this scraper

Drop this README into ChatGPT, Claude, or any AI assistant and ask it to design a pipeline. The input fields, schema, and examples above contain everything an LLM needs.

❓ Frequently Asked Questions

❓ Do I need an API key? No. The endpoint is public.

❓ Pagination? Yes, handled automatically where the upstream supports it.

❓ Rate limits? The upstream sets the rate limit. The actor surfaces upstream errors cleanly.

❓ Schema stability? Core fields are stable. Optional fields are passed through when present.

❓ Real-time? Yes, every run hits the live endpoint.

❓ Spreadsheet export? Yes, via the Apify dataset UI.

❓ Scheduling? Yes, via the Apify scheduler.

❓ Public data only? Yes.

❓ Free trial? Yes, $5 free credit on signup covers many runs.

❓ Webhook integration? Yes, native Apify webhooks fire on run completion.

🔌 Integrate with any app

Apify ships native integrations with Make, Zapier, Slack, Discord, Google Drive, Google Sheets, Gmail, Airbyte, Keboola, Telegram, GitHub, and any REST API or webhook endpoint. Trigger runs from a calendar event, a form submission, a cron job, or pipe results straight into BigQuery, Snowflake, or a Postgres warehouse.

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