{"id":2952,"date":"2026-06-05T10:00:00","date_gmt":"2026-06-05T10:00:00","guid":{"rendered":"https:\/\/oddspapi.io\/blog\/?p=2952"},"modified":"2026-05-31T14:24:32","modified_gmt":"2026-05-31T14:24:32","slug":"world-cup-odds-api-2026-fifa","status":"publish","type":"post","link":"https:\/\/oddspapi.io\/blog\/world-cup-odds-api-2026-fifa\/","title":{"rendered":"World Cup Odds API: Live 2026 FIFA World Cup Odds from 350+ Bookmakers (Free)"},"content":{"rendered":"

The 2026 FIFA World Cup kicks off on June 11<\/strong> with Mexico vs South Africa at the Estadio Azteca, then runs 104 matches across the USA, Canada and Mexico through July 19. If you’re building a model, a line-shopping tool, or just want to track where the sharp money is going, you need odds data — for every group-stage match, every knockout tie, all 48 teams.<\/p>\n

The problem: FIFA’s official data partners (Sportradar, Genius Sports) sell that feed on enterprise contracts with a sales call attached. Scraping Bet365 breaks the moment they change a CSS class. And the generic “free” sports APIs give you ~20 soft bookmakers and zero sharps.<\/p>\n

This guide shows you the third option: pull live World Cup odds from 350+ bookmakers<\/strong> — including Pinnacle, SBOBet, Bet365, DraftKings, FanDuel, plus prediction markets like Polymarket and Kalshi — through one JSON API, on a free tier that also includes historical data. Every code sample below was tested against the live feed three weeks before kickoff.<\/p>\n

Why the "Old Way" Doesn’t Work for the World Cup<\/h2>\n

World Cup traffic is the single biggest spike in the betting calendar. Everyone wants the data at once, and the usual routes all have a catch:<\/p>\n

\n\n\n\n\n\n\n\n\n
The Old Way<\/th>\nThe Catch<\/th>\nOddsPapi<\/th>\n<\/tr>\n<\/thead>\n
Official FIFA data (Sportradar \/ Genius)<\/td>\nEnterprise contract, sales call, opaque pricing<\/td>\nSelf-serve API key, free tier<\/td>\n<\/tr>\n
Scraping Bet365 \/ DraftKings<\/td>\nBreaks on every site change, IP bans, no sharps<\/td>\nStable JSON, 350+ books in one call<\/td>\n<\/tr>\n
Generic free sports APIs<\/td>\n~20 soft books, no Pinnacle, no historical data<\/td>\nPinnacle, SBOBet + prediction markets included<\/td>\n<\/tr>\n
Manual odds entry<\/td>\nStale within seconds during a match<\/td>\nReal-time, with full price history<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

OddsPapi aggregates the books that actually matter to a sharp bettor or a quant: the sharps<\/strong> (Pinnacle, SBOBet) that set the market, the US books<\/strong> (DraftKings, FanDuel, BetMGM) your readers actually use, and the prediction markets<\/strong> (Polymarket, Kalshi) that frequently price tighter than the bookmakers. For a deeper dive on soccer specifically, see our Football Odds API guide<\/a>.<\/p>\n

What’s Already in the Feed<\/h2>\n

Three weeks out, every World Cup fixture already carries odds. On a marquee group match like Brazil vs Morocco<\/strong>, the feed returned 18 bookmakers<\/strong> on the Full Time Result, and Pinnacle alone priced 62 distinct markets<\/strong> on that single fixture. Here’s the spread of coverage:<\/p>\n

\n\n\n\n\n\n\n\n\n\n
Market<\/th>\nMarket ID<\/th>\nBooks (3 weeks out)<\/th>\n<\/tr>\n<\/thead>\n
Full Time Result (1X2)<\/td>\n101<\/code><\/td>\n18<\/td>\n<\/tr>\n
Over\/Under 2.5 Goals<\/td>\n1010<\/code><\/td>\n15<\/td>\n<\/tr>\n
Both Teams To Score<\/td>\n104<\/code><\/td>\n13<\/td>\n<\/tr>\n
Over\/Under 1.5 \/ 3.5<\/td>\n108<\/code> \/ 1012<\/code><\/td>\n11<\/td>\n<\/tr>\n
Asian Handicap (multiple lines)<\/td>\n1068<\/code>, 1072<\/code>, 1076<\/code>…<\/td>\n1–6<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

Book counts grow as kickoff approaches and margins tighten — the numbers above are an early-line snapshot, not the peak. By matchday you’ll see well over 100 books on the headline fixtures.<\/p>\n

The Tutorial: World Cup Odds in Python<\/h2>\n

Four steps: authenticate, find the World Cup fixtures, pull the odds, and parse the nested JSON. You’ll need an OddsPapi API key<\/a> (free) and the requests<\/code> library.<\/p>\n

Step 1: Authentication<\/h3>\n

OddsPapi uses a query-parameter API key, not<\/strong> a header. This trips up a lot of people coming from other APIs.<\/p>\n

import requests\n\nAPI_KEY = \"YOUR_API_KEY\"\nBASE_URL = \"https:\/\/api.oddspapi.io\/v4\"\n\n# Auth is a query param, never a header\nresp = requests.get(f\"{BASE_URL}\/sports\", params={\"apiKey\": API_KEY})\nprint(resp.status_code)  # 200\n<\/code><\/pre>\n
Step 2: Find the World Cup Fixtures<\/h3>\n
Soccer is sportId=10<\/code>. The World Cup lives under the international<\/code> category with tournamentSlug=\"world-cup\"<\/code>. Fetch fixtures in a date window (max 10 days per call) and filter on the tournament name:<\/p>\n
def get_world_cup_fixtures(date_from, date_to):\n    r = requests.get(f\"{BASE_URL}\/fixtures\", params={\n        \"apiKey\": API_KEY,\n        \"sportId\": 10,\n        \"from\": date_from,   # \"2026-06-11\"\n        \"to\": date_to,       # \"2026-06-20\" (max 10 days apart)\n    })\n    fixtures = r.json()\n    # Filter to the FIFA World Cup tournament\n    wc = [f for f in fixtures if f.get(\"tournamentName\") == \"World Cup\"]\n    return wc\n\nmatches = get_world_cup_fixtures(\"2026-06-11\", \"2026-06-20\")\nfor f in matches:\n    print(f[\"startTime\"][:10], f[\"participant1Name\"], \"vs\",\n          f[\"participant2Name\"], \"| hasOdds:\", f[\"hasOdds\"])\n\n# 2026-06-11 Mexico vs South Africa   | hasOdds: True\n# 2026-06-13 USA vs Paraguay          | hasOdds: True\n# 2026-06-13 Brazil vs Morocco        | hasOdds: True\n# ...\n<\/code><\/pre>\n
Only fixtures with hasOdds: True<\/code> return a price payload — every World Cup match qualifies. Grab the fixtureId<\/code> for the next step.<\/p>\n
Step 3: Pull the Odds<\/h3>\n
Hit \/odds<\/code> with the fixtureId<\/code>. Optionally pass a comma-separated bookmakers<\/code> list to narrow the response:<\/p>\n
def get_odds(fixture_id, bookmakers=None):\n    params = {\"apiKey\": API_KEY, \"fixtureId\": fixture_id}\n    if bookmakers:\n        params[\"bookmakers\"] = bookmakers  # \"pinnacle,bet365,draftkings\"\n    return requests.get(f\"{BASE_URL}\/odds\", params=params).json()\n\n# Brazil vs Morocco\nodds = get_odds(\"id1000001666456928\",\n                bookmakers=\"pinnacle,bet365,draftkings,fanduel,polymarket,kalshi\")\nbooks = odds[\"bookmakerOdds\"]\nprint(f\"{len(books)} bookmakers returned\")\n<\/code><\/pre>\n
Step 4: Parse the Nested JSON<\/h3>\n
The \/odds<\/code> response is deeply nested. The path to a price is bookmakerOdds[slug][\"markets\"][marketId][\"outcomes\"][outcomeId][\"players\"][\"0\"][\"price\"]<\/code>. For the Full Time Result (market 101<\/code>), the outcome IDs are 101<\/code> = Home, 102<\/code> = Draw, 103<\/code> = Away.<\/p>\n
def get_1x2(books, slug):\n    # Return (home, draw, away) decimal prices for a bookmaker, or None\n    try:\n        outs = books[slug][\"markets\"][\"101\"][\"outcomes\"]\n        return (\n            outs[\"101\"][\"players\"][\"0\"][\"price\"],  # Home\n            outs[\"102\"][\"players\"][\"0\"][\"price\"],  # Draw\n            outs[\"103\"][\"players\"][\"0\"][\"price\"],  # Away\n        )\n    except KeyError:\n        return None\n\nfor slug in [\"pinnacle\", \"bet365\", \"draftkings\", \"fanduel\", \"polymarket\", \"kalshi\"]:\n    line = get_1x2(books, slug)\n    if line:\n        print(f\"{slug:11} Brazil {line[0]}  Draw {line[1]}  Morocco {line[2]}\")\n\n# pinnacle    Brazil 1.625  Draw 3.79   Morocco 5.66\n# bet365      Brazil 1.6    Draw 4.0    Morocco 5.25\n# draftkings  Brazil 1.62   Draw 3.95   Morocco 5.75\n# fanduel     Brazil 1.56   Draw 4.0    Morocco 5.6\n# polymarket  Brazil 1.639  Draw 4.348  Morocco 5.556\n# kalshi      Brazil 1.613  Draw 4.348  Morocco 5.556\n<\/code><\/pre>\n
Note the prediction markets.<\/strong> Polymarket’s prices on OddsPapi are already converted to decimal odds (not the native 0–1 share price), so you can drop them straight into a comparison alongside the sportsbooks.<\/p>\n
Line Shopping: Find the Best World Cup Price<\/h2>\n
With 350+ books in one payload, finding the best available price for any outcome is a loop. Always filter on active<\/code> — suspended or stale prices will otherwise poison your scan.<\/p>\n
def best_price(books, market_id, outcome_id):\n    best_slug, best_odds = None, 0.0\n    for slug, bd in books.items():\n        try:\n            o = bd[\"markets\"][str(market_id)][\"outcomes\"][str(outcome_id)][\"players\"][\"0\"]\n            if o.get(\"active\") and o[\"price\"] > best_odds:\n                best_slug, best_odds = slug, o[\"price\"]\n        except (KeyError, TypeError):\n            continue\n    return best_slug, best_odds\n\n# Best price on each Brazil vs Morocco outcome (market 101)\nfor oid, label in [(\"101\", \"Brazil\"), (\"102\", \"Draw\"), (\"103\", \"Morocco\")]:\n    slug, price = best_price(books, 101, oid)\n    print(f\"Best {label}: {price} @ {slug}\")\n\n# Best Brazil: 1.639 @ polymarket\n# Best Draw:   4.348 @ kalshi\n# Best Morocco: 5.8  @ circasports\n<\/code><\/pre>\n
For a production-grade version of this with sharp-book whitelists and arb-sum sanity checks, see our Python line shopping guide<\/a>.<\/p>\n
De-Vig: What’s the Fair Price?<\/h2>\n
Pinnacle is the sharpest book in the market, so its no-vig line is the closest thing to a fair probability you’ll find. Strip the margin by normalising the implied probabilities:<\/p>\n
def devig_1x2(home, draw, away):\n    imp = [1\/home, 1\/draw, 1\/away]\n    total = sum(imp)               # the overround (> 1)\n    fair = [p\/total for p in imp]  # normalised true probabilities\n    fair_odds = [1\/p for p in fair]\n    return fair, fair_odds, (total - 1) * 100\n\nh, d, a = get_1x2(books, \"pinnacle\")  # 1.625, 3.79, 5.66\nfair, fair_odds, vig = devig_1x2(h, d, a)\nprint(f\"Pinnacle margin: {vig:.2f}%\")\nprint(f\"Fair Brazil  {fair[0]*100:.1f}%  ({fair_odds[0]:.3f})\")\nprint(f\"Fair Draw    {fair[1]*100:.1f}%  ({fair_odds[1]:.3f})\")\nprint(f\"Fair Morocco {fair[2]*100:.1f}%  ({fair_odds[2]:.3f})\")\n\n# Pinnacle margin: 5.59%\n# Fair Brazil  58.3%  (1.716)\n# Fair Draw    25.0%  (4.002)\n# Fair Morocco 16.7%  (5.976)\n<\/code><\/pre>\n
Interesting wrinkle in the early lines: the prediction markets were pricing tighter<\/em> than Pinnacle. On Brazil vs Morocco, Polymarket’s 1X2 overround was 2.01%<\/strong> and Kalshi’s 2.99%<\/strong>, versus Pinnacle’s 5.59%<\/strong> and Bet365’s 6.55%<\/strong>. Early-line margins are always wider than they’ll be on matchday, but the gap is a useful reminder to always check where the sharpest implied probability is coming from. Our consensus odds calculator<\/a> shows how to blend all 350+ books into a single fair line.<\/p>\n
Free Historical Odds for Backtesting<\/h2>\n
This is the differentiator most APIs charge for. The \/historical-odds<\/code> endpoint returns the full price history for a fixture — every snapshot, with timestamps — on the free tier. Note the response shape differs from \/odds<\/code>: the top-level key is bookmakers<\/code> (not bookmakerOdds<\/code>), and players[\"0\"]<\/code> is a list<\/strong> of snapshots, not a single dict. Max 3 bookmakers per call.<\/p>\n
def get_history(fixture_id, bookmakers):\n    r = requests.get(f\"{BASE_URL}\/historical-odds\", params={\n        \"apiKey\": API_KEY,\n        \"fixtureId\": fixture_id,\n        \"bookmakers\": bookmakers,  # max 3, e.g. \"pinnacle,bet365,draftkings\"\n    })\n    return r.json()\n\nhist = get_history(\"id1000001666456928\", \"pinnacle,bet365,draftkings\")\n# players[\"0\"] is a LIST of price snapshots:\nsnaps = hist[\"bookmakers\"][\"pinnacle\"][\"markets\"][\"101\"][\"outcomes\"][\"101\"][\"players\"][\"0\"]\nfor s in snaps[:5]:\n    print(s[\"createdAt\"], s[\"price\"])\n<\/code><\/pre>\n
Use this to measure Closing Line Value, track how the market moved on each team, or backtest a model against three weeks of group-stage drift. Pipe it to a spreadsheet with our CSV\/Excel export guide<\/a>.<\/p>\n
Beyond 1X2: Goals, BTTS & Asian Handicaps<\/h2>\n
The World Cup feed carries the full native market structure, not just match result. Look market names up via \/v4\/markets?sportId=10<\/code> rather than hardcoding the full catalog:<\/p>\n
\n\n\n\n\n\n\n\n\n
Market<\/th>\nMarket ID<\/th>\nOutcome IDs<\/th>\n<\/tr>\n<\/thead>\n
Over\/Under 2.5 Goals<\/td>\n1010<\/code><\/td>\n1010<\/code> Over \/ 1011<\/code> Under<\/td>\n<\/tr>\n
Both Teams To Score<\/td>\n104<\/code><\/td>\nYes \/ No<\/td>\n<\/tr>\n
Asian Handicap 0 (Draw No Bet)<\/td>\n1072<\/code><\/td>\nHome \/ Away<\/td>\n<\/tr>\n
Asian Handicap -0.5<\/td>\n1068<\/code><\/td>\nHome \/ Away<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n
Asian Handicaps are handled natively — no awkward two-way conversion. For the cross-book AH scanner, see our Asian Handicap API guide<\/a>.<\/p>\n
Get Your Free API Key<\/h2>\n
The World Cup is the highest-volume betting event of the four-year cycle. Whether you’re building a value scanner, a live dashboard, or a model to beat the closing line, OddsPapi gives you 350+ bookmakers, sharps, prediction markets, and free historical data through one JSON endpoint — no enterprise contract, no scraping.<\/p>\n
Stop scraping. Get your free OddsPapi API key →<\/a><\/strong><\/p>\n
Frequently Asked Questions<\/h2>\n
Does OddsPapi have 2026 World Cup odds?<\/h3>\n
Yes. All World Cup fixtures are in the feed with hasOdds: true<\/code>, filterable by tournamentName=\"World Cup\"<\/code> (slug world-cup<\/code>, category international<\/code>) under soccer (sportId=10<\/code>). Coverage includes group stage and knockout matches with 1X2, totals, BTTS and Asian Handicap markets.<\/p>\n
Which bookmakers are covered for the World Cup?<\/h3>\n
350+ books including sharps (Pinnacle, SBOBet), US books (DraftKings, FanDuel, BetMGM), UK\/EU books (Bet365), and prediction markets (Polymarket, Kalshi). A marquee group match like Brazil vs Morocco returned 18 books on the match result three weeks before kickoff, climbing past 100 by matchday.<\/p>\n
Is the World Cup odds data free?<\/h3>\n
Yes — the free tier includes live odds across 350+ bookmakers and historical price history, with a ~0.88s cooldown between calls to the same endpoint. No paid plan is required for the tutorial code in this guide.<\/p>\n
How do I get the World Cup winner \/ outright odds?<\/h3>\n
Outright tournament-winner markets are listed in the \/v4\/markets?sportId=10<\/code> catalog; query the catalog to find the current market ID, then pass the relevant fixtureId<\/code> to \/odds<\/code>. Match-level markets (1X2, totals, handicaps) are available on every fixture as shown above.<\/p>\n
Can I get historical World Cup odds for backtesting?<\/h3>\n
Yes. The \/historical-odds<\/code> endpoint returns the full snapshot history per fixture (up to 3 bookmakers per call) on the free tier. Use it to measure Closing Line Value or backtest a model against the group-stage market.<\/p>\n