{"id":3099,"date":"2026-07-09T10:00:00","date_gmt":"2026-07-09T10:00:00","guid":{"rendered":"https:\/\/oddspapi.io\/blog\/?p=3099"},"modified":"2026-06-21T16:22:44","modified_gmt":"2026-06-21T16:22:44","slug":"oddspedia-api-alternative","status":"publish","type":"post","link":"https:\/\/oddspapi.io\/blog\/oddspedia-api-alternative\/","title":{"rendered":"Oddspedia API Alternative: Raw JSON Odds from 350+ Books (Free Tier)"},"content":{"rendered":"

Hunting for an Oddspedia API<\/strong>? Here is the thing most developers find out only after signing up: Oddspedia is built for publishers<\/em>, not developers. Their product is a set of free, embeddable odds-comparison widgets<\/strong>, drop-in HTML blocks you paste onto a content site, plus a publisher-oriented data feed behind a dashboard login. It is a brand-awareness and affiliate play, and it is genuinely good at that job.<\/p>\n

But if you want raw odds in JSON<\/em>, the prices to feed a bot, a model, a line-shopping tool, or your own app, a widget is the wrong shape. This guide shows the honest difference between Oddspedia’s widget feed and a developer-first odds API, then pulls real MLB prices across 15 bookmakers with a free OddsPapi key in about ten lines of Python.<\/p>\n

Oddspedia vs OddsPapi: Widgets vs a Real API<\/h2>\n

Let us be fair to Oddspedia. Per their own site, “Oddspedia Widgets and API Data feeds are 100% free, no hidden fees,” and the widgets “cover more than 30 sports and more than 8000 competitions.” They update worldwide coverage daily and share it with publishers via widgets and a raw data feed. If you run a betting-content or affiliate site and want a polished, customizable odds table on the page in five minutes, that is exactly what Oddspedia is for.<\/p>\n

The catch for developers: the widgets are display objects<\/strong>, HTML\/JS you embed, and the data feed sits behind a registered-publisher dashboard (widgets.oddspedia.com\/dashboard<\/code>). It is designed for putting odds on a page<\/em>, not for querying prices programmatically and doing math on them. There is no self-serve developer REST key that returns clean JSON for any fixture.<\/p>\n

\n\n\n\n\n\n\n\n\n\n\n\n\n\n
 <\/th>\nOddspedia<\/th>\nOddsPapi<\/th>\n<\/tr>\n<\/thead>\n
Primary product<\/strong><\/td>\nEmbeddable odds widgets<\/td>\nRaw JSON odds API<\/td>\n<\/tr>\n
Built for<\/strong><\/td>\nPublishers & affiliates<\/td>\nDevelopers, modelers, bettors<\/td>\n<\/tr>\n
Output<\/strong><\/td>\nHTML\/JS widget on your page<\/td>\nJSON you parse and compute on<\/td>\n<\/tr>\n
Access<\/strong><\/td>\nPublisher dashboard login<\/td>\nSelf-serve API key, query param<\/td>\n<\/tr>\n
Price<\/strong><\/td>\nFree<\/td>\nFree tier<\/td>\n<\/tr>\n
Coverage<\/strong><\/td>\n30+ sports, 8000+ competitions<\/td>\n69 sports, 372 bookmakers<\/td>\n<\/tr>\n
Sharps & exchanges<\/strong><\/td>\nComparison display<\/td>\nPinnacle, Betfair, Polymarket, Kalshi in JSON<\/td>\n<\/tr>\n
Historical odds<\/strong><\/td>\nNot a developer feed<\/td>\nFree on every fixture<\/td>\n<\/tr>\n
Real-time<\/strong><\/td>\nDaily-updated display<\/td>\nREST + WebSocket push<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

The Pivot: A Widget Cannot Run Your Logic<\/h2>\n

You cannot write if best_price > pinnacle_fair: alert()<\/code> against an HTML widget. The moment you want to do<\/em> anything with odds, compare books, remove the vig, find the best line, detect movement, backtest a model, you need the numbers as data, not as a rendered table. Tools like jedibets<\/a> (a player-props odds screener with Discord alerts) exist precisely because punters want odds turned into actionable signals, not just a pretty grid.<\/p>\n

So let us get the raw numbers. Same odds-comparison idea Oddspedia renders visually, but as JSON you control. (If you want the full grid version, see our odds comparison API<\/a> guide; for the screener landscape, the Oddschecker API alternative<\/a> covers the same publisher-vs-developer split.)<\/p>\n

Tutorial: Raw Odds Comparison in Python<\/h2>\n

Step 1: Authenticate<\/h3>\n

Grab a free key. The one gotcha: the API key is a query parameter, not a header.<\/strong><\/p>\n

import requests\n\nAPI_KEY = \"YOUR_API_KEY\"\nBASE_URL = \"https:\/\/api.oddspapi.io\/v4\"\n\nr = requests.get(f\"{BASE_URL}\/sports\", params={\"apiKey\": API_KEY})\nprint(r.status_code)  # 200\n<\/code><\/pre>\n
Step 2: Find a Fixture<\/h3>\n
Discover fixtures for a sport over a date window (max 10 days), keeping only those with odds attached. MLB is sportId=13<\/code>.<\/p>\n
from datetime import date, timedelta\n\ntoday = date.today()\nparams = {\n    \"apiKey\": API_KEY,\n    \"sportId\": 13,                       # MLB\n    \"from\": today.isoformat(),\n    \"to\": (today + timedelta(days=2)).isoformat(),\n}\nfixtures = requests.get(f\"{BASE_URL}\/fixtures\", params=params).json()\ngames = [f for f in fixtures if f.get(\"hasOdds\")]\n\nfor f in games[:5]:\n    print(f[\"participant1Name\"], \"vs\", f[\"participant2Name\"], \"|\", f[\"fixtureId\"])\n<\/code><\/pre>\n
Our worked example: Philadelphia Phillies vs New York Mets<\/strong> (fixtureId id1300010963301993<\/code>).<\/p>\n
Step 3: Pull Every Book’s Price<\/h3>\n
Hit \/odds<\/code> and walk the nested structure: bookmakerOdds -> {slug} -> markets -> {marketId} -> outcomes -> {outcomeId} -> players[\"0\"] -> price<\/code>. The MLB moneyline (“Winner incl. extra innings”) is market 131<\/strong>, with outcomes 131<\/strong> (home) and 132<\/strong> (away). Always check active<\/code> before trusting a price.<\/p>\n
fid = \"id1300010963301993\"\nbooks = requests.get(f\"{BASE_URL}\/odds\",\n                     params={\"apiKey\": API_KEY, \"fixtureId\": fid}).json()[\"bookmakerOdds\"]\n\ndef moneyline(slug):\n    outs = books.get(slug, {}).get(\"markets\", {}).get(\"131\", {}).get(\"outcomes\", {})\n    row = {}\n    for oid in (\"131\", \"132\"):\n        node = outs.get(oid, {}).get(\"players\", {}).get(\"0\", {})\n        if node and node.get(\"active\"):\n            row[oid] = node[\"price\"]\n    return row\n\nfor slug in sorted(books):\n    p = moneyline(slug)\n    if p:\n        print(f\"{slug:18} PHI {p.get('131')}  NYM {p.get('132')}\")\n<\/code><\/pre>\n
Real output, 11 active books on the moneyline:<\/p>\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Bookmaker<\/th>\nPhillies<\/th>\nMets<\/th>\n<\/tr>\n<\/thead>\n
pinnacle (sharp)<\/td>\n1.584<\/td>\n2.56<\/td>\n<\/tr>\n
polymarket<\/td>\n1.587<\/td>\n2.632<\/td>\n<\/tr>\n
kalshi<\/td>\n1.587<\/td>\n2.632<\/td>\n<\/tr>\n
fanduel<\/td>\n1.54<\/td>\n2.54<\/td>\n<\/tr>\n
draftkings<\/td>\n1.53<\/td>\n2.53<\/td>\n<\/tr>\n
caesars<\/td>\n1.526<\/td>\n2.58<\/td>\n<\/tr>\n
betmgm<\/td>\n1.53<\/td>\n2.55<\/td>\n<\/tr>\n
hardrockbet<\/td>\n1.50<\/td>\n2.70<\/td>\n<\/tr>\n
pointsbet.com.au<\/td>\n1.53<\/td>\n2.60<\/td>\n<\/tr>\n
williamhill<\/td>\n1.526<\/td>\n2.58<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n
Step 4: De-Vig the Sharp and Find the Best Line<\/h3>\n
This is what a widget cannot do for you. De-vig Pinnacle for a fair-probability anchor, then sweep every book for the best available price on each side.<\/p>\n
pin = moneyline(\"pinnacle\")              # {'131': 1.584, '132': 2.56}\ninv = 1\/pin[\"131\"] + 1\/pin[\"132\"]\nprint(f\"Pinnacle overround: {(inv-1)*100:.2f}%\")\nprint(f\"Fair: PHI {1\/(1\/pin['131']\/inv):.3f}  NYM {1\/(1\/pin['132']\/inv):.3f}\")\n\ndef best(oid):\n    quotes = [(moneyline(s).get(oid), s) for s in books]\n    return max((q for q in quotes if q[0]), default=(None, None))\n\nprint(\"Best Phillies:\", best(\"131\"))\nprint(\"Best Mets:\", best(\"132\"))\n<\/code><\/pre>\n
Result: Pinnacle’s overround is just 2.19%<\/strong> (no-vig fair line PHI 1.619 \/ NYM 2.616, so the Phillies are a 61.8% favorite). The best available prices were 1.587 on the Phillies<\/strong> (Polymarket and Kalshi) and 2.70 on the Mets<\/strong> (HardRock). That HardRock 2.70 is 6.7% better than DraftKings’ 2.53 on the exact same bet, and it sits above Pinnacle’s de-vigged fair, the best available price here, though as a soft outlier, not a guaranteed edge. You only see that gap when the odds are data you can sort, never from a rendered widget. That sweep is the core of line shopping in Python<\/a>.<\/p>\n
Free Historical Odds for Backtesting<\/h2>\n
One more thing Oddspedia’s publisher feed is not built for: pulling a fixture’s full price history to backtest. OddsPapi exposes it free on \/historical-odds<\/code>, where players[\"0\"]<\/code> is a list<\/em> of timestamped snapshots (note the different shape from the live endpoint, max three bookmakers per call).<\/p>\n
h = requests.get(f\"{BASE_URL}\/historical-odds\",\n                 params={\"apiKey\": API_KEY, \"fixtureId\": fid,\n                         \"bookmakers\": \"pinnacle,fanduel,draftkings\"}).json()\nsnaps = h[\"bookmakers\"][\"pinnacle\"][\"markets\"][\"131\"][\"outcomes\"][\"131\"][\"players\"][\"0\"]\nfor s in snaps[:5]:\n    print(s[\"createdAt\"], s[\"price\"])\n<\/code><\/pre>\n
Where Oddspedia Fits<\/h2>\n
To keep it honest: if you run a betting-affiliate or content site and want free, attractive, daily-updated odds-comparison widgets across 30+ sports with zero backend work, Oddspedia is a great fit and OddsPapi is not trying to be that. Their widgets, broad competition coverage, and publisher-friendly free model are a real strength for the brand-awareness use case.<\/p>\n
But if you are a developer building software, an arb scanner, a value model, an odds dashboard, a price-movement alert bot, you need odds as queryable JSON with sharp, exchange, and prediction-market prices and a real-time push channel. That is a different product, and it is the one OddsPapi ships. Weighing several feeds? Our best odds APIs of 2026<\/a> buyer’s guide ranks them by use case.<\/p>\n
FAQ<\/h2>\n
Does Oddspedia have a public API?<\/h3>\n
Oddspedia offers free widgets and a publisher data feed, accessed through a registered dashboard at widgets.oddspedia.com. It is aimed at publishers embedding odds-comparison displays, not at developers who want self-serve raw JSON odds. For a developer-first REST API, OddsPapi returns JSON for any fixture with a free key.<\/p>\n
Is Oddspedia free?<\/h3>\n
Yes. Per Oddspedia, their widgets and API data feeds are “100% free, no hidden fees,” monetized through affiliate partnerships. OddsPapi also offers a free tier with a self-serve key.<\/p>\n
What is the difference between an odds widget and an odds API?<\/h3>\n
A widget is rendered HTML\/JS you embed to display<\/em> odds on a page. An API returns raw odds as JSON you can parse, compare, de-vig, and compute on, which is what you need to build bots, models, or apps.<\/p>\n
How many bookmakers can I compare with OddsPapi?<\/h3>\n
372 bookmakers across 69 sports, including sharps (Pinnacle), exchanges (Betfair), and prediction markets (Polymarket, Kalshi). On this MLB example, 15 books priced the fixture and 11 quoted an active moneyline.<\/p>\n
Can I get historical odds for backtesting?<\/h3>\n
Yes, free. The \/historical-odds<\/code> endpoint returns the full timestamped price history for a fixture (up to three bookmakers per call).<\/p>\n
Get Raw Odds, Not Just a Widget<\/h2>\n
Oddspedia is a solid widget product for publishers. But if you need the numbers, sharp lines, exchange and prediction-market prices, and free history, in JSON you can actually build on, you can have them in the next five minutes. Start with the free odds API guide<\/a>, then get your free OddsPapi API key<\/a><\/strong> and pull your first real odds comparison today.<\/p>\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
Oddspedia ships free odds widgets for publishers, not a developer API. Get raw JSON odds from 372 bookmakers with a free OddsPapi key. 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