Sportradar Alternative: Shop 289 Books on One NBA Fixture

Why Developers Search for a Sportradar Alternative

Sportradar sells official sports data to sportsbooks, broadcasters and leagues. If you need licensed statistics or a feed bound to a league’s rights, they are a sensible call.

Their odds products are a different fit for a developer. Sportradar splits odds into six APIs, and the US-focused Odds Comparison Prematch API lists nine feeds on its overview page: MGM, DraftKings, FanDuel, BetRivers, PointsBet, Bet365.US.NJ, WilliamHillNewJersey, ESPNbetCom and a “Consensus” line. The real-time product, Live Odds, has no self-serve trial. Their docs send you to a sales representative.

We read the NBA opening-night boards on 20 Oct 2026 at 13:08 UTC to see what those nine feeds leave out. Each of the first six fixtures carried 282 to 289 bookmakers on OddsPapi. On all six, the best price on participant 1 came from ProphetX, Kalshi or Novig, and none of those three is on Sportradar’s Prematch list. This post shows the board, the guard that keeps stale prices out of a best-price scan, and the Python to run it yourself.

Sportradar vs OddsPapi: Feature Comparison

This table covers Sportradar’s odds products only. On licensed statistics, Sportradar wins; the honesty section below says where.

The two products serve different buyers. Sportradar sells to sportsbook operators, broadcasters and enterprises. OddsPapi sells to developers and quants who want every price on a fixture from one call.

Sportradar’s Nine Prematch Feeds, Mapped to OddsPapi Slugs

If you have code written against OC Prematch, most of the list maps across. Prices below are the 2-way Winner market on Detroit Pistons v Boston Celtics, read at 13:13 UTC on 20 Oct 2026.

The same board also carried Pinnacle at 2.03 / 1.884, Caesars, Hard Rock Bet and Circa Sports, plus the books outside a US retail list:

What the Extra Books Buy You: NBA Opening Night

We read six NBA boards at 13:08 UTC on 20 Oct 2026 and kept a book only if it passed the stale-price guard in Step 4 below. “Best of board” pairs the highest price on each side from any usable book. “Best of 7 US books” does the same inside the seven mapped feeds above, where they passed the guard.

Read three things off that table:

• Close to zero margin across the full board. Pairing the best price on each side across all usable books gave -0.25% to 0.26%. Inside the seven US books it gave 2.61% to 3.53%. The best-of-board figure uses exchange back prices before commission, so treat it as the best available price, not a free arbitrage.
• Exchanges set the top of the board. ProphetX, Kalshi or Novig held the best participant-1 price on 6 of 6 boards. Betfair Exchange held the best participant-2 price on four. For how much stake sits behind those prices, read NBA exchange depth.
• 288 books collapse to about 60 prices. Many slugs are skins of one feed and quote the same pair. Dedupe on the price pair before you average or count.

Six Odds APIs vs One Key

Sportradar’s odds overview lists six odds products, each with its own reference:

OddsPapi puts pre-match, in-play, outrights and player props behind one key: /v4/odds for the current board, /v4/historical-odds for the price history and /v4/markets for the market catalogue. You learn one schema, and you get every market on a fixture in one response.

Pricing and Access

Sportradar does not publish odds pricing. For Live Odds, the documentation says:

“Reach out to your sales representative for trial access to the Live Odds API.”

OddsPapi has a self-serve price builder on the pricing page, and a free account can call /v4/odds and /v4/historical-odds before you pay for anything. Sign up, take the key, and run the code below.

Python Tutorial: Replace Sportradar’s Odds Comparison Calls

Every snippet below ran live at 13:13 UTC on 20 Oct 2026. The output comments are copied from that run. Run them in order; each step uses variables from the one before it.

Step 1: Discover Sports

import requests

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

r = requests.get(f"{BASE}/sports", params={"apiKey": API_KEY})
r.raise_for_status()
sports = r.json()
print(f"{len(sports)} sports available")

basketball = next(s for s in sports if s["slug"] == "basketball")
print(f"Basketball sportId: {basketball['sportId']}")
# > 70 sports available
# > Basketball sportId: 11

Step 2: List NBA Fixtures

Filter on tournamentId as well as sportId. NBA is tournament 132. The tournament filter cuts the payload, and it lifts the 10-day range cap that applies when sportId is the only filter. A 404 here means an empty window, so handle it before you raise on other errors.

import time
from datetime import datetime, timedelta, timezone

time.sleep(1.0)
today = datetime.now(timezone.utc).date()
r = requests.get(f"{BASE}/fixtures", params={
    "apiKey": API_KEY,
    "sportId": 11,
    "tournamentId": 132,          # NBA
    "from": f"{today}T00:00:00",
    "to": f"{today + timedelta(days=3)}T00:00:00",   # midnight UTC: covers 3 full days
})
if r.status_code == 404:
    fixtures = []                 # 404 = empty window, not an error
else:
    r.raise_for_status()          # a 429 must not read as "no fixtures"
    fixtures = r.json()
nba = sorted((f for f in fixtures if f.get("hasOdds")), key=lambda f: f["startTime"])
print(f"{len(nba)} NBA fixtures with odds")
for f in nba[:3]:
    print(f"  {f['fixtureId']}  {f['participant1Name']} v {f['participant2Name']}  {f['startTime']}")
# > 15 NBA fixtures with odds
# >   id1100013273682354  Detroit Pistons v Boston Celtics  2026-10-20T19:00:00.000Z
# >   id1100013273682356  New York Knicks v Philadelphia 76ers  2026-10-20T23:00:00.000Z
# >   id1100013273682414  San Antonio Spurs v Oklahoma City Thunder  2026-10-21T01:30:00.000Z

Step 3: Every Book on One Fixture

One call returns every bookmaker’s price for every market on the fixture. Market 111 is the basketball Winner, which includes overtime. Outcome 111 is participant 1 and 112 is participant 2.

time.sleep(1.0)
fixture_id = nba[0]["fixtureId"]
r = requests.get(f"{BASE}/odds", params={"apiKey": API_KEY, "fixtureId": fixture_id})
r.raise_for_status()
bm_odds = {s: v for s, v in r.json()["bookmakerOdds"].items()
           if not s.startswith("pinnacle+") and s != "demo"}   # internal test feeds
print(f"{len(bm_odds)} books on this fixture")

def moneyline(book):
    """Market 111 = Winner (incl. overtime). Outcome 111 = participant 1, 112 = participant 2."""
    try:
        out = book["markets"]["111"]["outcomes"]
        return out["111"]["players"]["0"], out["112"]["players"]["0"]
    except (KeyError, TypeError):
        return None

for slug in ["pinnacle", "draftkings", "fanduel", "betmgm", "bet365",
             "betfair-ex", "kalshi", "novig.us", "prophetx", "stake"]:
    ml = moneyline(bm_odds.get(slug, {}))
    if ml:
        print(f"  {slug:<11} {ml[0]['price']:>6} / {ml[1]['price']:<6}")
# > 289 books on this fixture
# >   pinnacle      2.03 / 1.884
# >   draftkings    2.02 / 1.82
# >   fanduel        2.0 / 1.85
# >   betmgm         2.0 / 1.83
# >   bet365        1.96 / 1.81
# >   betfair-ex    2.08 / 1.92
# >   kalshi       2.083 / 1.887
# >   novig.us     2.083 / 1.887
# >   prophetx      2.09 / 1.901
# >   stake         1.99 / 1.79

Step 4: Best-Price Scan With a Stale-Price Guard

A naive best-price loop over 289 books finds prices that are a day old. On the Spurs v Thunder board, three offshore slugs that share one feed still showed 2.23 on the Thunder from the day before, and a naive scan read that as a 4% arbitrage. The guard below drops a book whose whole feed has not moved in the last hour, and a market that froze while the rest of the book moved on. It also reads the book-level suspended and bookmakerIsActive flags, which you can trust pre-match.

def ts(s):
    return datetime.fromisoformat(s.replace("Z", "+00:00"))

def last_move(book):
    """Newest changedAt the book has on ANY price on this fixture."""
    stamps = [ts(p["changedAt"])
              for m in book.get("markets", {}).values()
              for o in m["outcomes"].values()
              for p in o["players"].values() if p.get("changedAt")]
    return max(stamps, default=None)

def usable_books(bm_odds, max_book_age=timedelta(minutes=60), max_lag=timedelta(hours=6)):
    now = datetime.now(timezone.utc)
    keep = {}
    for slug, book in bm_odds.items():
        if book.get("suspended") or book.get("bookmakerIsActive") is False:
            continue                              # book-level flags (pre-match)
        ml = moneyline(book)
        newest = last_move(book)
        if not ml or newest is None or not (ml[0].get("active") and ml[1].get("active")):
            continue
        if now - newest > max_book_age:           # whole feed has gone quiet
            continue
        if any(newest - ts(p["changedAt"]) > max_lag for p in ml):
            continue                              # this market froze while the book moved on
        keep[slug] = (ml[0]["price"], ml[1]["price"])
    return keep

books = usable_books(bm_odds)
print(f"{len(books)} usable books, {len(set(books.values()))} distinct price pairs")

best1 = max(books.items(), key=lambda kv: kv[1][0])
best2 = max(books.items(), key=lambda kv: kv[1][1])
print("Best participant 1:", best1[0], best1[1][0])
print("Best participant 2:", best2[0], best2[1][1])
print(f"Best-of-board margin: {(1/best1[1][0] + 1/best2[1][1] - 1)*100:.2f}%")

us7 = {s: books[s] for s in ["betmgm", "draftkings", "fanduel", "betrivers",
                             "bet365", "williamhill", "thescore"] if s in books}
u1 = max(p[0] for p in us7.values()); u2 = max(p[1] for p in us7.values())
print(f"Best of {len(us7)} US books: {u1} / {u2}, margin {(1/u1 + 1/u2 - 1)*100:.2f}%")
# > 244 usable books, 59 distinct price pairs
# > Best participant 1: prophetx 2.09
# > Best participant 2: betfair-ex 1.92
# > Best-of-board margin: -0.07%
# > Best of 6 US books: 2.05 / 1.85, margin 2.83%

On that run, williamhill had not repriced anything on the fixture in the last hour, so the guard dropped it and six of the seven US books remained. Run the same loop over every fixture you track and you have the base of a line-shopping tool. To turn the board into a fair price, de-vig the deduped consensus rather than one book.

Step 5: Price History From the Same Key

/v4/historical-odds takes up to 3 bookmakers per call. The response shape differs from /odds: the top-level key is bookmakers, and players["0"] is a list of snapshots, oldest first. The feed records a snapshot whether or not the price moved, so collapse repeats before you count moves.

time.sleep(1.0)
r = requests.get(f"{BASE}/historical-odds", params={
    "apiKey": API_KEY,
    "fixtureId": fixture_id,
    "bookmakers": "pinnacle,draftkings,fanduel",   # 3 per call, max
})
r.raise_for_status()
hist = r.json()["bookmakers"]          # NOT bookmakerOdds
for slug, book in hist.items():
    snaps = book["markets"]["111"]["outcomes"]["111"]["players"]["0"]   # a LIST here
    moves = [s for i, s in enumerate(snaps) if i == 0 or s["price"] != snaps[i-1]["price"]]
    print(f"{slug:<11} {len(snaps):>5} snapshots, {len(moves):>4} price moves, "
          f"since {snaps[0]['createdAt'][:10]}")   # oldest first
# > draftkings   1334 snapshots,   16 price moves, since 2026-08-12
# > fanduel       893 snapshots,   38 price moves, since 2026-09-12
# > pinnacle      112 snapshots,   50 price moves, since 2026-09-28

DraftKings opened this fixture in August and moved its price 16 times. Pinnacle opened on 28 September and moved 50 times. That history is what you backtest a model against, or export to CSV.

Where Sportradar Wins

If you shop for a Sportradar alternative, know what you give up. OddsPapi does not cover everything Sportradar does, and it is not meant to.

If you run risk for a sportsbook or overlay official stats on a broadcast, call Sportradar. If you want cross-bookmaker odds for arbitrage, value betting or backtesting, a full Sportradar stack charges you for parts you will not use.

Migration Notes

• Authentication: OddsPapi takes the key as the query parameter ?apiKey= on every call. It is never a header.
• IDs: sports, tournaments and markets are numeric. Basketball is sportId=11, NBA is tournamentId=132, and soccer is sportId=10. Query /v4/sports for the full list.
• Markets: one global catalogue at /v4/markets. The same bet can ship under more than one market ID (basketball has 111 Winner incl. overtime and 113 Regular Time Result, 3-way), so resolve on the market name and keep the clock in mind.
• Refresh model: Sportradar Live Odds feeds refresh every 15-30 seconds. OddsPapi REST returns the current board when you call it (sleep about 1 second between calls to the same endpoint), and the WebSocket pushes changes as they arrive.
• Staleness: read changedAt on every price. A book can keep a withdrawn market at active: true, so compare each price to the newest move the same book made on the fixture (Step 4).

Building for a sportsbook or a trading desk?

The same data runs OddsPapi’s B2B feed: a WebSocket stream with per-channel cursors and resume-and-replay, opening and closing line values for CLV, and a per-outcome settlement result on /v4/settlements once a fixture finishes. The B2B reference lives at docs.oddspapi.io. Start with a free key at oddspapi.io. Pricing is usage-based, so a desk pays for the bookmakers, sports and request volume it reads. For how vendors in this market price, see enterprise odds feed pricing.

Frequently Asked Questions

Is OddsPapi a direct replacement for Sportradar?

For odds aggregation, line shopping, arbitrage, value betting and backtesting, yes. For licensed league statistics, official play-by-play or integrity contracts, no. Those are Sportradar’s core products, and OddsPapi does not sell them.

How many bookmakers does Sportradar’s Odds Comparison cover compared with OddsPapi?

Sportradar’s OC Core lists 140+ bookmakers, and the US-focused OC Prematch lists 9 feeds, one of them a consensus line. OddsPapi’s catalogue holds 366 bookmaker slugs, and one NBA opening-night fixture carried 289 of them on 20 Oct 2026.

Can I get a free trial of Sportradar’s Live Odds API?

Sportradar’s Live Odds documentation says the product is unavailable for a self-issued trial and sends you to a sales representative. OddsPapi is self-serve: sign up, take the key, and call the API.

Does OddsPapi have Pinnacle, Singbet, SBOBET and Betfair Exchange?

Yes. All four are slugs in the catalogue (pinnacle, singbet, sbobet, betfair-ex), and all four priced the Pistons v Celtics Winner on 20 Oct 2026 in the same /odds response as DraftKings and FanDuel.

What about Polymarket, Kalshi and Novig?

They are bookmaker slugs in the same feed: polymarket, polymarket.us, kalshi and novig.us. Exchange books carry a back/lay ladder under exchangeMeta. See the Novig API guide and the Polymarket API guide.

Is the historical odds endpoint free?

Yes. /v4/historical-odds is part of the free tier. It takes up to 3 bookmakers per call, so loop over bookmaker groups to pull a full board.

Read the Board Before You Book the Call

If your project does not need licensed play-by-play, you do not need a procurement cycle to read odds. Get a free OddsPapi key, run the five steps above on tonight’s slate, and compare the board you get with the nine feeds on Sportradar’s Prematch list.

Related reading:

• Best Odds APIs in 2026: 6 Providers Compared
• Odds API Pricing in 2026
• Genius Sports Alternative
• OpticOdds API Alternative
• OddsJam API Alternative
• The Odds API Alternative