Use case

AI and data products

Whole seasons as JSON, CSV or Parquet, our own win-probability model, and docs your agent can read — clean data with stable ids, no scraping.

Get a free API keyGet a free API keyRead the docs

The build, step by step

  1. Whole seasons

    Export a league season — fixtures, standings, top players — in one file (Business).

    POST /v2/exports

  2. A model, live

    Our in-play win probability for football, with its whole curve (Pro and Business).

    GET /v2/fixtures/{id}/win-probability

  3. Docs for agents

    llms.txt and a Markdown copy of every page, so an assistant can call the API correctly.

    sportsapi.app/llms.txt

A season into your pipeline

Start an export, read the win probability of a match — the same key, the same envelope.

Python
from sportsapi import SportsAPI

client = SportsAPI()  # reads SPORTSAPI_API_KEY

job = client.exports.create(league=league_id, season=season_id, format="parquet")
status = client.exports.get(job["data"]["id"])

wp = client.fixtures.win_probability(fixture_id)
Which plan

Business for season exports and the full history; Pro for the win-probability model.

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