Australian Sports Odds API in Python: The Complete Guide

The PuntersEdge API returns live odds from every major Australian bookmaker — Sportsbet, TAB, Ladbrokes, Neds, Betfair, Unibet, PointsBet and Betr — across AFL, NRL, racing, cricket, tennis, NBA and more, as clean REST/JSON. In this guide you'll go from zero to a working multi-bookmaker odds comparison.

1. Get a free API key

Create a key at the API platform — the free tier gives you 2,500 requests a month with no credit card. Every request authenticates with an X-API-Key header. Keep your key out of source control (use an environment variable in real projects).

2. Your first request: list the sports

Install the one dependency and list the available sports. The key field is what you'll pass to the odds endpoints.

# pip install requests
import requests

API = "https://api.puntersedge.online/v1"
HEADERS = {"X-API-Key": "YOUR_API_KEY"}

sports = requests.get(f"{API}/sports", headers=HEADERS).json()
for s in sports:
    print(s["key"], "—", s["title"])

# nrl — NRL
# afl — AFL
# nba — NBA  ...

3. Pull live odds for a sport

The /best-odds/{sport} endpoint returns each upcoming event with the best available price per selection already computed across all books — so you don't have to merge bookmaker feeds yourself. It returns a list of events; each event has a selections list, and each selection carries name, best_price and best_bookmaker.

events = requests.get(f"{API}/best-odds/nrl", headers=HEADERS).json()

for ev in events:
    print(f"\n{ev['home_team']} v {ev['away_team']}")
    for sel in ev["selections"]:
        print(f"  {sel['name']:24} {sel['best_price']:>6}  ({sel['best_bookmaker']})")

# Penrith Panthers v Brisbane Broncos
#   Penrith Panthers          1.65  (pointsbetau)
#   Brisbane Broncos          2.30  (sportsbet)

4. Surface the standout prices on the board

"Line shopping" — comparing the best available price for each selection — is a core concept when you work with odds data. Because the API returns best_price and best_bookmaker per selection, ranking the standout prices on the board is just a sort. (This is a data exercise — it makes no claim about outcomes or returns.)

def best_book_board(sport):
    events = requests.get(f"{API}/best-odds/{sport}", headers=HEADERS).json()
    rows = []
    for ev in events:
        for sel in ev["selections"]:
            rows.append((sel["best_price"], sel["name"], sel["best_bookmaker"]))
    # biggest prices first — the standout value on the board
    rows.sort(reverse=True)
    return rows[:10]

for price, name, book in best_book_board("nrl"):
    print(f"{price:>6}  {name:24} {book}")

5. Add racing

Racing is the highest-volume market in Australia. The /racing/next-to-go endpoint returns the next races to jump with their runners and live win prices per bookmaker — ideal for a next-to-go board or a price tracker.

data = requests.get(f"{API}/racing/next-to-go", headers=HEADERS).json()

for race in data["races"]:
    print(f"\n{race['venue']} R{race['race_number']} ({race['category']})")
    for r in race["runners"][:4]:
        best = max(r["bookmakers"], key=lambda b: b["win_price"])
        print(f"  {r['number']:>2} {r['name']:22} {best['win_price']:>6} ({best['key']})")

6. That's the whole integration

That's it — a few requests calls and one header. The same normalise-then-compare pattern works against any odds source, so nothing here locks you in. An official open-source Python SDK that wraps these endpoints (typed methods, retries, clean errors) is on the way; until then, the snippets above are all you need.

7. Production tips

• Auth & secrets: read the key from an env var (os.environ["PE_API_KEY"]), never commit it.
• Errors: the API uses standard codes — 401 bad key, 429 rate-limited, 5xx retry with backoff. Check resp.status_code before .json().
• Caching: odds change fast but not every second — cache responses for 10–30s to stay well inside your quota.
• Free tier: 2,500 requests/month is plenty for prototyping; upgrade when you ship.

Next steps

You now have live, multi-bookmaker Australian odds in a few lines of Python — the data layer behind comparison tools, dashboards, alerts and models. From here, explore the full endpoint set or browse coverage by bookmaker and sport.

PuntersEdge provides odds data for developers. 18+. Odds for information only — gamble responsibly.