TheSportsDB Scraper: Teams, Leagues & Stadiums avatar

TheSportsDB Scraper: Teams, Leagues & Stadiums

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Pay per usage

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TheSportsDB Scraper: Teams, Leagues & Stadiums

TheSportsDB Scraper: Teams, Leagues & Stadiums

Look up sports teams by name via the public TheSportsDB API: league, sport, stadium, capacity, formation year and badge. No login, no proxy, no browser.

Pricing

Pay per usage

Rating

0.0

(0)

Developer

Naimur Hasan

Naimur Hasan

Maintained by Community

Actor stats

0

Bookmarked

2

Total users

1

Monthly active users

6 days ago

Last modified

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TheSportsDB Scraper

Looks up sports teams by name through the public TheSportsDB API: league, sport, stadium, capacity, formation year and badge. No proxy, no browser.

Input

FieldTypeNotes
teamNamesarrayRequired. Team names, e.g. ["Arsenal", "Chicago Bulls"].
includeStadiumCapacitybooleanLook up each team's venue for its capacity. Default true.
apiKeystringOptional. Your own TheSportsDB key; empty uses the free test key.

Output

One row per matched team: teamId, team, alternateNames, sport, league, country, formedYear, stadium, stadiumLocation, stadiumCountry, venueId, stadiumCapacity, website, badgeUrl, description.

Notes

  • The old free key 3 was permanently disabled. It answers HTTP 403 with a plain-text notice naming its replacement, the test key 123, which is what this Actor uses when no apiKey is given.
  • The free key is shared by every anonymous caller, so its rate limit is a pool rather than a per-user budget: a burst gets HTTP 429 with a Cloudflare HTML page, and once tripped the block persists for a while rather than clearing on the next request. Requests are spaced 800 ms apart and retried with a capped backoff. Supplying your own apiKey avoids the pool entirely, and is worth doing for anything beyond a handful of names.
  • Capacity moved off the team record. intStadiumCapacity is gone; teams now carry an idVenue and the capacity lives on the venue. Filling the column costs one extra request per team, so it can be switched off when looking up many names.
  • A name can match more than one team across different sports and countries, so the row count can exceed the number of names submitted.
  • Every numeric field arrives as a string upstream ("60338"); they are converted to numbers here so capacity and formation year sort correctly.
  • A name with no match is logged and skipped; the run only fails if nothing matched at all.