NHL Odds API

NHL prices from the same endpoint as every other tournament we carry. tournamentId 234, sportId 15.

17Fixtures scheduledfrom /v4/tournaments
197Bookmakers quoted58 independent prices, 20 days out
145Market familiessportId 15

63 of those fixtures fall inside the next 30 days, pulled in 10 day windows on tournamentId.

Measured live at 2026-09-09 21:48 UTC. This page is regenerated from the API, so the numbers move.

Get a free API key Read the docs

Quick start: NHL fixtures and prices

Copy it as it stands. It was run against the live API before this page rendered.

import datetime as dt
import time

import requests

API_KEY = "YOUR_API_KEY"
BASE_URL = "https://api.oddspapi.io/v4"


def get(path, params):
    """The key is the query parameter apiKey, never a header.
    Read the status code first: a 429 body is valid JSON too."""
    query = dict(params, apiKey=API_KEY)
    for attempt in range(3):
        response = requests.get(f"{BASE_URL}/{path}", params=query, timeout=180)
        if response.status_code == 429:
            time.sleep(5 * (attempt + 1))
            continue
        if response.status_code == 404:
            return None
        response.raise_for_status()
        return response.json()
    raise RuntimeError("rate limited on /" + path)


# tournamentId filters /v4/fixtures and lifts the 10 day range cap, so a
# whole month arrives in one call. It also cuts the payload about 20x.
fixtures = get("fixtures", {
    "tournamentId": 234,
    "from": "2026-09-09",
    "to": "2026-10-09",
}) or []
print(len(fixtures), "NHL fixtures")

# The same bet ships under more than one market id on several sports, so
# resolve the result market from /v4/markets by name and read every id that
# maps to it. Reading one id drops part of the board.
MAIN_MARKET_IDS = ["151", "153"]

# hasOdds is a flag, not a depth signal, and it is false on every finished
# fixture. Boards open on their own clock, so the fixtures nearest kick-off
# carry the prices, and a fixture already in play often has the result market
# suspended. Read the ones still ahead of us, soonest first.
now = dt.datetime.now(dt.timezone.utc).strftime("%Y-%m-%dT%H:%M:%S.000Z")
upcoming = sorted(
    (f for f in fixtures if f["hasOdds"] and f["startTime"] > now),
    key=lambda f: f["startTime"],
)
for fixture in upcoming[:10]:
    odds = get("odds", {
        "fixtureId": fixture["fixtureId"],
        "bookmakers": "pinnacle,bet365,draftkings",
    })
    boards = (odds or {}).get("bookmakerOdds") or {}
    printed = False
    for slug, board in boards.items():
        for market_id in MAIN_MARKET_IDS:
            market = board["markets"].get(market_id)
            if not market:
                continue
            # players is keyed "0" on a match market. On a player prop it is
            # keyed by player id, so never hardcode "0" outside this case.
            prices = {
                outcome_id: leg["players"]["0"]["price"]
                for outcome_id, leg in market["outcomes"].items()
                if leg["players"]["0"]["active"]
            }
            if prices:
                print(fixture["participant1Name"], "v",
                      fixture["participant2Name"], slug, market_id, prices)
                printed = True
    if printed:
        break
    time.sleep(1.0)

Run against the live API at 2026-09-09 21:53 UTC. First line of output: 63 NHL fixtures

Bookmakers pricing NHL

197 bookmakers quoted, 58 independent prices, 20 days before kick-off, on Carolina Hurricanes v Florida Panthers, measured 2026-09-09 21:06 UTC. Identical price tuples are grouped before the second count, because distinct slugs publish the same price and cloneOf does not track that.

and 49 more on https://oddspapi.io/sportsbooks

Counted from one /v4/odds call with no bookmaker filter, on the main result market for the sport. Regional feeds of one brand are shown once and link to that brand.

Market families

Read off /v4/markets and filtered on the sport. A family that carries many market ids is a ladder, with one id per line, so resolve a market on its name and collect every id that maps to it.

Market family Market ids Type
Regular Time Result 1 Match market
Winner (incl. overtime and penalties) 1 Match market
Total 25 Match market
Total (incl. overtime and penalties) 25 Match market
First Period Total 20 Match market
Second Period Total 20 Match market
Third Period Total 20 Match market
Handicap 31 Match market
Handicap (incl. overtime and penalties) 31 Match market
First Period Handicap 23 Match market
Second Period Handicap 23 Match market
Third Period Handicap 23 Match market

Read the study

NHL Odds API study. The write-up behind these numbers, with the code that produced them.

Other Ice Hockey tournaments

Questions developers ask

What is the NHL tournamentId?

234, on sportId 15. Confirm it against /v4/tournaments?sportId=15 before you hardcode it; the endpoint returns the id, the slug and the count of scheduled fixtures on one object.

How many bookmakers price a NHL fixture?

197 bookmakers quoted Carolina Hurricanes v Florida Panthers, and those group into 58 independent prices once identical price tuples are collapsed, measured 2026-09-09 21:06 UTC. Group the tuples before you average, because distinct slugs publish the same price.

How far ahead can I pull NHL fixtures?

17 fixtures were scheduled at 2026-09-09 21:48 UTC. /v4/fixtures caps the from and to range under 10 days when sportId is the only filter, and adding tournamentId lifts that cap.

Pull the NHL board yourself

The free tier reads the same endpoints as the paid one. Pass tournamentId=234 and the payload drops about 20x against a sport wide call.

Get a free API key Read the docs