PYTHON ODDS API

Python Odds API for Football Betting Data

Pull UK football odds into Python using plain REST JSON, no proprietary SDK required. Works straight away with requests or httpx.

Get API access Docs

Odds API for Python

import requests
r = requests.get(BASE + "/events", headers={"X-Api-Key": KEY})

JSON over HTTPS, authenticated with an X-Api-Key header.

WHY PYTHON DEVELOPERS NEED THIS

Build football odds tools without wrestling with a bookmaker's SDK

Anyone building odds comparison tables, alert bots, tipster tools, or backtesting scripts in Python needs a data source that behaves predictably. Scraping bookmaker sites is slow, breaks constantly, and is hard to maintain in a production script. A REST API returning consistent JSON slots straight into pandas, asyncio, or a scheduled job, so you spend time on your product instead of on parsing HTML. This page covers what you need before you touch a single endpoint.

Odds comparison tools

Python developers building odds comparison sites need one consistent JSON feed rather than several bookmaker websites to scrape. A single call with requests or httpx can populate a dataframe or database table, which is far easier to keep running than a set of fragile scrapers.

Alerting and notification bots

Telegram and Discord bots that flag value bets or odds movements need structured data they can poll on a schedule. Clean JSON responses fit naturally into Python's scheduling and asyncio libraries without any custom HTML parsing.

Tipster and prediction tools

Tipster platforms and prediction models need current and historical odds to calculate implied probabilities and track accuracy over time. Python's data stack, including pandas and NumPy, works directly with plain JSON odds data, so there is no bespoke SDK to learn.

Research and backtesting

Analysts backtesting betting strategies need consistent odds across matches and bookmakers to model returns accurately. A plain REST response can be pulled directly into a research script or notebook, keeping the whole pipeline simple to reproduce.

Endpoints Python apps call most

Start with events and odds. Add history or arbitrage by plan.

GET /v1/football/events?schedule_date=YYYY-MM-DD&has_odds=true&per_page=25

GET /v1/football/events/EVENT_ID/odds?package=core&odds_format=decimal

GET /v1/football/events/EVENT_ID/odds/best?odds_format=decimal

Replace EVENT_ID with an event_id from the events endpoint.

Example JSON your Python code parses

Best odds payload for a quick compare loop.

{
  "event_id": "evt_123",
  "odds_format": "decimal",
  "markets": [
    {
      "key": "1x2",
      "best": [
        { "name": "Home", "odds": 2.02, "bookmaker_code": "UO004" },
        { "name": "Draw", "odds": 3.45, "bookmaker_code": "UO018" },
        { "name": "Away", "odds": 3.78, "bookmaker_code": "UO006" }
      ]
    }
  ]
}

What you can build