NBA prices from the same endpoint as every other tournament we carry. tournamentId 132, sportId 11.
Measured live at 2026-09-09 21:47 UTC. This page is regenerated from the API, so the numbers move.
Quick start: NBA 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": 132,
"from": "2026-09-09",
"to": "2026-10-29",
}) or []
print(len(fixtures), "NBA 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 = ["111", "113"]
# 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: 16 NBA fixtures
Bookmakers pricing NBA
179 bookmakers quoted, 42 independent prices, 41 days before kick-off, on Detroit Pistons v Boston Celtics, measured 2026-09-09 21:04 UTC. Identical price tuples are grouped before the second count, because distinct slugs publish the same price and cloneOf does not track that.
and 46 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) | 1 | Match market |
| Over Under (incl. overtime) | 401 | Match market |
| Over Under Second Half (incl. overtime) | 180 | Match market |
| Over Under Fourth Quarter (incl. overtime) | 100 | Match market |
| Over Under First Half | 90 | Match market |
| Over Under Second Half | 90 | Match market |
| Over Under First Quarter | 50 | Match market |
| Over Under Fourth Quarter | 50 | Match market |
| Over Under Second Quarter | 50 | Match market |
| Over Under Third Quarter | 50 | Match market |
| Handicap (incl. overtime) | 321 | Match market |
Read the study
NBA Odds API study. The write-up behind these numbers, with the code that produced them.
Other Basketball tournaments
Questions developers ask
What is the NBA tournamentId?
132, on sportId 11. Confirm it against /v4/tournaments?sportId=11 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 NBA fixture?
179 bookmakers quoted Detroit Pistons v Boston Celtics, and those group into 42 independent prices once identical price tuples are collapsed, measured 2026-09-09 21:04 UTC. Group the tuples before you average, because distinct slugs publish the same price.
How far ahead can I pull NBA fixtures?
21 fixtures were scheduled at 2026-09-09 21:47 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 NBA board yourself
The free tier reads the same endpoints as the paid one. Pass tournamentId=132 and the payload drops about 20x against a sport wide call.
