{"id":3053,"date":"2026-06-19T10:00:00","date_gmt":"2026-06-19T10:00:00","guid":{"rendered":"https:\/\/oddspapi.io\/blog\/?p=3053"},"modified":"2026-06-15T13:44:39","modified_gmt":"2026-06-15T13:44:39","slug":"sportsbook-odds-feed-websocket-pipeline","status":"publish","type":"post","link":"https:\/\/oddspapi.io\/blog\/sportsbook-odds-feed-websocket-pipeline\/","title":{"rendered":"Sportsbook Odds Feed: WebSocket-First Pricing Pipeline for Operators"},"content":{"rendered":"<h2>Your Odds Feed Is Your Pricing Engine<\/h2>\n<p>If you run a sportsbook, a trading desk, or any platform that prices markets in real time, your odds feed is not infrastructure \u2014 it is your product. A two-second delay exposes you to arbitrageurs. A stale line on a bookmaker that just moved lets sharp money in before you can close. A feed that drops and reconnects from scratch means a gap in your audit trail you cannot explain to regulators.<\/p>\n<p>Most operators discover this after an incident. The generic developer APIs on the market were built for analysts polling once every five seconds \u2014 not for operators who need to act on a price change in under a second. OddsPapi&#8217;s B2B feed, documented at <a href=\"https:\/\/docs.oddspapi.io\/\">docs.oddspapi.io<\/a>, is built for the second use case.<\/p>\n<h2>Why Current Solutions Break at Operator Scale<\/h2>\n<p>There are three ways operators typically try to source aggregated bookmaker data. All three have structural problems at production scale.<\/p>\n<figure class=\"wp-block-table\">\n<table>\n<thead>\n<tr>\n<th>Approach<\/th>\n<th>Time to Production<\/th>\n<th>Coverage<\/th>\n<th>Stale Detection<\/th>\n<th>Failure Mode<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><strong>Scraping<\/strong><\/td>\n<td>Days (then breaks monthly)<\/td>\n<td>What you can parse<\/td>\n<td>None \u2014 you don&#8217;t know<\/td>\n<td>Rate limit, DOM change, legal risk<\/td>\n<\/tr>\n<tr>\n<td><strong>Bilateral data contract<\/strong><\/td>\n<td>Months (NDA, integration, UAT)<\/td>\n<td>One bookmaker per contract<\/td>\n<td>Depends on partner SLA<\/td>\n<td>Feed drops silently, no fallback<\/td>\n<\/tr>\n<tr>\n<td><strong>Generic developer REST API<\/strong><\/td>\n<td>Hours<\/td>\n<td>Wide but polling-only<\/td>\n<td>None \u2014 timestamps only<\/td>\n<td>Rate limit, polling gap, no stale signal<\/td>\n<\/tr>\n<tr>\n<td><strong>OddsPapi B2B (WebSocket)<\/strong><\/td>\n<td>Hours<\/td>\n<td>200+ bookmakers, one connection<\/td>\n<td>Built-in <code>staleOdds<\/code> flag<\/td>\n<td>Cursor resumes from last event, no gap<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n<p>The gap between a REST polling architecture and a WebSocket-first architecture is not academic. At 10-second polling intervals you miss every price movement that opens and closes between polls \u2014 which, for sharp books during live in-play, can be dozens per minute. The <a href=\"https:\/\/oddspapi.io\/blog\/how-often-odds-apis-update\/\">polling vs WebSocket explainer<\/a> covers the update cadence in detail.<\/p>\n<h2>OddsPapi B2B: WebSocket-First Architecture<\/h2>\n<p>The B2B feed is structured as a set of typed channels. Each channel delivers a specific data type; your systems subscribe to exactly what they need and nothing else. Authentication is a single login frame sent after connection, which returns your access tier (<code>access.live<\/code> and <code>access.pregame<\/code>) and your starting cursor position.<\/p>\n<h3>The Channel Set<\/h3>\n<figure class=\"wp-block-table\">\n<table>\n<thead>\n<tr>\n<th>Channel<\/th>\n<th>What It Delivers<\/th>\n<th>Typical Consumer<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><code>odds<\/code><\/td>\n<td>High-throughput real-time betting odds from 200+ bookmakers<\/td>\n<td>Pricing engine, line-monitoring, arbitrage detector<\/td>\n<\/tr>\n<tr>\n<td><code>bookmakers<\/code><\/td>\n<td>Per-bookmaker feed status, including <code>staleOdds<\/code> flag<\/td>\n<td>Trading safety layer \u2014 pause automation on stale<\/td>\n<\/tr>\n<tr>\n<td><code>fixtures<\/code><\/td>\n<td>Match metadata, status transitions, participant mapping<\/td>\n<td>Market lifecycle management<\/td>\n<\/tr>\n<tr>\n<td><code>scores<\/code><\/td>\n<td>Period and final scores, scoped to <code>fixtureId<\/code><\/td>\n<td>In-play risk management, live market suspension<\/td>\n<\/tr>\n<tr>\n<td><code>clocks<\/code><\/td>\n<td>Live match clock \u2014 period, elapsed time, stopped state<\/td>\n<td>In-play pricing model input, suspension timing<\/td>\n<\/tr>\n<tr>\n<td><code>injuries<\/code> \/ <code>lineups<\/code> \/ <code>stats<\/code><\/td>\n<td>Player-level supplementary data<\/td>\n<td>Pre-match model refresh, prop market triggers<\/td>\n<\/tr>\n<tr>\n<td><code>futures<\/code> \/ <code>oddsFutures<\/code><\/td>\n<td>Season-long and outright market metadata and prices<\/td>\n<td>Outright book management, election\/politics markets<\/td>\n<\/tr>\n<tr>\n<td><code>currencies<\/code><\/td>\n<td>Global exchange rates including crypto<\/td>\n<td>Multi-currency settlement, crypto book pricing<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n<p>Every odds message is keyed by <code>{fixtureId}:{bookmaker}:{outcomeId}:{playerId}<\/code>. This composite key means your downstream systems can merge updates into a local state without a join \u2014 a single dict lookup routes each message to the right market position.<\/p>\n<h2>The staleOdds Flag: Your Automated Trading Safety Net<\/h2>\n<p>The most important field in the B2B feed is not a price \u2014 it is <code>staleOdds<\/code>, a boolean delivered on the <code>bookmakers<\/code> channel.<\/p>\n<p>When OddsPapi&#8217;s aggregation layer loses connectivity to a source bookmaker, it does not silently continue serving the last known price. It flips <code>staleOdds: true<\/code> for that bookmaker. Your system&#8217;s correct response is to suspend any automated strategy that references that bookmaker&#8217;s line until <code>staleOdds<\/code> returns to <code>false<\/code>.<\/p>\n<p>This matters most in two scenarios:<\/p>\n<ul>\n<li><strong>Automated arbitrage<\/strong>: An arb scanner comparing Pinnacle to Bet365 on a live in-play market needs to know if either leg is quoting a price that is 90 seconds old. Without <code>staleOdds<\/code>, a false arb triggers a losing position.<\/li>\n<li><strong>Model-driven line setting<\/strong>: If your model uses an external sharp book as a price anchor, a stale anchor means your lines diverge from the market without a signal that anything is wrong.<\/li>\n<\/ul>\n<pre class=\"wp-block-code\"><code>import asyncio, json\nimport websockets\n\n# Simplified B2B connection sketch \u2014 see docs.oddspapi.io for full spec\nasync def feed():\n    async with websockets.connect(\"wss:\/\/YOUR_B2B_ENDPOINT\") as ws:\n\n        # Login frame\n        await ws.send(json.dumps({\n            \"action\": \"login\",\n            \"apiKey\": \"YOUR_B2B_KEY\",\n            \"receiveType\": \"json\"          # or \"zstd\" \/ \"zstd-dict\" \/ \"binary\"\n        }))\n        login_resp = json.loads(await ws.recv())\n        # login_resp[\"access\"][\"live\"] == True for live feed access\n\n        # Subscribe to odds + bookmaker status channels\n        await ws.send(json.dumps({\n            \"action\": \"subscribe\",\n            \"channels\": [\"odds\", \"bookmakers\"]\n        }))\n\n        # Maintain stale state per bookmaker slug\n        stale = {}\n\n        async for raw in ws:\n            msg = json.loads(raw)\n            channel = msg.get(\"channel\")\n\n            if channel == \"bookmakers\":\n                slug = msg[\"bookmaker\"]\n                stale[slug] = msg.get(\"staleOdds\", False)\n                if stale[slug]:\n                    print(f\"ALERT: {slug} feed is stale \u2014 pausing strategies\")\n\n            elif channel == \"odds\":\n                slug = msg[\"bookmaker\"]\n                if stale.get(slug):\n                    continue   # Do not act on prices from a stale source\n                process_price(msg)\n\nasyncio.run(feed())\n<\/code><\/pre>\n<p>The <code>staleOdds<\/code> check is a one-line guard, but it is the difference between a trading system that survives bookmaker connectivity incidents and one that compounds losses on phantom prices.<\/p>\n<h3>The participantsRotated Flag<\/h3>\n<p>A second safety flag on the <code>fixtures<\/code> channel: <code>participantsRotated<\/code>. This signals that the bookmaker&#8217;s home\/away assignment differs from OddsPapi&#8217;s canonical mapping for that fixture. If your moneyline parser maps outcome 1 to &#8220;home win&#8221; and the source book has the teams inverted, every position you open on that outcome is on the wrong side. Check this flag before writing any outcome to your market model.<\/p>\n<h2>Resume and Replay: No Data Loss on Disconnect<\/h2>\n<p>WebSocket connections drop. The question is what happens when they do.<\/p>\n<p>The B2B feed maintains per-channel cursors via two fields: <code>entryId<\/code> and <code>serverEpoch<\/code>. Your client stores these with every message. On reconnect, you send your last known cursor and the server replays any events you missed during the gap \u2014 up to the <code>resumeWindowMs<\/code> (default 60 seconds).<\/p>\n<p>The recovery pattern has two branches:<\/p>\n<ul>\n<li><strong>Short disconnect (within resume window)<\/strong>: Send last cursor on login. Server replays missed events, then continues the live stream. No data loss, no manual reconciliation.<\/li>\n<li><strong>Long disconnect (outside resume window)<\/strong>: Server responds with <code>snapshot_required<\/code>. Fetch a REST snapshot via <code>GET \/fixtures\/odds<\/code> to rebuild your state, then reconnect with a fresh cursor. Worst case is one REST call \u2014 not an open-ended data hole.<\/li>\n<\/ul>\n<p>The design goal is explicit in the docs: &#8220;short interruptions resume with no data loss.&#8221; That guarantee is only possible because cursors are server-side state tied to the feed delivery, not client-reconstructed timestamps. This is a different architecture from &#8220;reconnect and re-subscribe&#8221; approaches where the gap is whatever you missed during downtime.<\/p>\n<h2>Compression Options for High-Throughput Environments<\/h2>\n<p>Raw JSON odds messages are verbose. At scale \u2014 hundreds of bookmakers, dozens of live in-play fixtures, high-cadence markets \u2014 the wire cost of uncompressed JSON becomes the constraint.<\/p>\n<figure class=\"wp-block-table\">\n<table>\n<thead>\n<tr>\n<th>Mode<\/th>\n<th>Compression Ratio vs JSON<\/th>\n<th>Use Case<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><code>json<\/code><\/td>\n<td>1x (baseline)<\/td>\n<td>Development, debugging, low-volume monitoring<\/td>\n<\/tr>\n<tr>\n<td><code>binary<\/code> (MessagePack)<\/td>\n<td>~2-3x<\/td>\n<td>Latency-sensitive, low overhead deserialization<\/td>\n<\/tr>\n<tr>\n<td><code>zstd<\/code><\/td>\n<td>~5-6x<\/td>\n<td>High-throughput pipelines where bandwidth is the cost<\/td>\n<\/tr>\n<tr>\n<td><code>zstd-dict<\/code><\/td>\n<td>~7-9x<\/td>\n<td>Maximum compression; server re-sends dictionary on reconnect<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n<p>For a trading desk processing 100+ live fixtures simultaneously across 200 bookmakers, the difference between <code>json<\/code> and <code>zstd-dict<\/code> is roughly an 8x reduction in ingress bandwidth and a corresponding reduction in the time your parse pipeline is blocked on I\/O. The <code>receiveType<\/code> is set in the login frame \u2014 no separate negotiation required.<\/p>\n<h2>Settlement: Closing the Pricing Loop<\/h2>\n<p>A pricing feed that does not connect to settlement is half a pipeline. When a market closes, you need per-outcome results for bet grading and a final score for reconciliation.<\/p>\n<p>The settlement endpoint delivers both:<\/p>\n<pre class=\"wp-block-code\"><code>import requests\n\n# Settlement for a closed fixture\nr = requests.get(\n    \"https:\/\/api.oddspapi.io\/v4\/fixtures\/settlement\",\n    params={\n        \"apiKey\": \"YOUR_KEY\",\n        \"fixtureId\": \"id1000001234567890\"\n    }\n)\nsettlement = r.json()\n\n# settlement[\"outcomes\"] \u2014 dict of outcomeId -> {result: \"won\"|\"lost\"|\"void\", score, margin}\n# settlement[\"scores\"]   \u2014 final score per period\n# settlement[\"status\"]   \u2014 \"Finished\" when grading is final\n\nfor outcome_id, result in settlement[\"outcomes\"].items():\n    grade_bet(outcome_id, result[\"result\"])\n<\/code><\/pre>\n<p>This covers fixture markets. Futures settlement is listed as in development in the current documentation \u2014 outright markets are priced live but require a separate grading flow for now.<\/p>\n<h2>CLV Analytics: Measuring Your Execution Quality<\/h2>\n<p>Closing Line Value (CLV) is the benchmark that separates informed line movement from noise. For trading desks and market makers, CLV tells you whether your lines were tighter or looser than the market consensus at close \u2014 which is the most accurate forward-looking signal of whether your pricing model is capturing value.<\/p>\n<p>The CLV endpoint returns opening line value (OLV) and closing line value (CLV) for any completed fixture:<\/p>\n<pre class=\"wp-block-code\"><code>r = requests.get(\n    \"https:\/\/api.oddspapi.io\/v4\/fixtures\/odds\/clv\",\n    params={\n        \"apiKey\": \"YOUR_KEY\",\n        \"fixtureId\": \"id1000001234567890\",\n        \"bookmakers\": \"pinnacle\"\n    }\n)\nclv_data = r.json()\n\n# Per outcome: opening price, closing price, implied probability shift\n# Use Pinnacle as the sharp benchmark for no-vig CLV calculation\n<\/code><\/pre>\n<p>Pair this with your historical trade log and you can measure, by market and sport, whether your book was consistently ahead of or behind the closing line. For more on building this kind of analytical layer, see the <a href=\"https:\/\/oddspapi.io\/blog\/expected-value-betting-python-ev-clv\/\">CLV and EV benchmarking guide<\/a> and the <a href=\"https:\/\/oddspapi.io\/blog\/historical-odds-csv-excel-backtesting\/\">historical odds export tutorial<\/a>.<\/p>\n<h2>The Full Operator Pipeline<\/h2>\n<p>The B2B feed is designed to carry data from price discovery through to market settlement without requiring you to stitch together separate services:<\/p>\n<ol>\n<li><strong>Pre-match<\/strong>: Subscribe to <code>fixtures<\/code> and <code>odds<\/code> channels. Receive opening lines from 200+ bookmakers. Use the Pinnacle or sharp-book anchor for no-vig pricing. Set your opening line.<\/li>\n<li><strong>In-play<\/strong>: Add <code>clocks<\/code> and <code>scores<\/code> channels. React to match-state changes. Monitor <code>bookmakers<\/code> channel for <code>staleOdds<\/code> \u2014 suspend automated strategies on any stale source. Check <code>participantsRotated<\/code> before updating any outcome mapping.<\/li>\n<li><strong>Post-match<\/strong>: Call <code>\/fixtures\/settlement<\/code> for per-outcome results and final scores. Grade bets. Run CLV audit against <code>\/fixtures\/odds\/clv<\/code> to benchmark your line&#8217;s execution quality.<\/li>\n<\/ol>\n<p>The <a href=\"https:\/\/oddspapi.io\/blog\/websocket-odds-api-real-time-betting-data\/\">WebSocket overview for developers<\/a> covers the real-time delivery concepts in detail. The <a href=\"https:\/\/oddspapi.io\/blog\/white-label-turnkey-api-betting-platform\/\">white-label vs API vs turnkey decision guide<\/a> is worth reading if you are still evaluating whether a full B2B data integration is the right architecture for your stage. For a broader comparison of data providers, see the <a href=\"https:\/\/oddspapi.io\/blog\/best-odds-apis-2026-comparison\/\">2026 odds API buyer&#8217;s guide<\/a>.<\/p>\n<h2>Bookmaker Coverage and Futures<\/h2>\n<p>The B2B feed covers the same bookmaker catalog as the rest of the OddsPapi network \u2014 Sharps (Pinnacle, SBOBet, Singbet), US operators (DraftKings, FanDuel, BetMGM), global softs, crypto books (1xBet, Stake, BC.Game), and exchanges (Betfair, Polymarket, Kalshi). For exchanges, the <code>odds<\/code> channel delivers depth-of-book ladder data \u2014 <code>back<\/code> and <code>lay<\/code> as ordered lists of price levels \u2014 not a single scalar price.<\/p>\n<p>Futures markets (outrights, season winners, elections, prediction-market topics) are delivered on separate <code>futures<\/code> and <code>oddsFutures<\/code> channels, with CLV available via <code>\/futures\/odds\/clv<\/code>.<\/p>\n<h2>Access and Status<\/h2>\n<p>The B2B feed is available to licensed operators, trading firms, and enterprise platforms. Access is tiered by API key \u2014 <code>access.live<\/code> for in-play data, <code>access.pregame<\/code> for pre-match. Full documentation and connection specs are at <a href=\"https:\/\/docs.oddspapi.io\/\">docs.oddspapi.io<\/a>. Feed status and uptime history are tracked at the <a href=\"https:\/\/oddspapi-v5.instatus.com\">OddsPapi status page<\/a>.<\/p>\n<p>For technical integration questions: support@oddspapi.io. For access and commercial terms: contact@oddspapi.io.<\/p>\n<h2>Frequently Asked Questions<\/h2>\n<h3>What is the difference between the OddsPapi B2B feed and the v4 developer API?<\/h3>\n<p>The v4 API (api.oddspapi.io\/v4) is a REST API designed for individual developers and analysts \u2014 hobbyist scripts, data exploration, smaller-scale applications. The B2B feed (docs.oddspapi.io) is a WebSocket-first architecture built for operators who need real-time delivery, stale detection, resume\/replay cursors, compression, and settlement integration. Different product, different access tier, different SLA.<\/p>\n<h3>How does staleOdds work in practice?<\/h3>\n<p>The <code>staleOdds<\/code> flag is delivered on the <code>bookmakers<\/code> WebSocket channel. When OddsPapi detects that a bookmaker&#8217;s feed has gone silent, it sets <code>staleOdds: true<\/code>. Your client should suppress prices from that bookmaker in automated strategies until the flag clears to <code>false<\/code>.<\/p>\n<h3>What happens if my WebSocket connection drops?<\/h3>\n<p>Send your last <code>entryId<\/code> and <code>serverEpoch<\/code> cursor on reconnect. If within the resume window (default 60 seconds), the server replays missed events with no data loss. Beyond the window, fetch one REST snapshot to rebuild state before resuming.<\/p>\n<h3>Is compression mandatory?<\/h3>\n<p>No. The default is <code>json<\/code>. Switch to <code>zstd-dict<\/code> (7-9x size reduction vs JSON) when throughput or bandwidth becomes a constraint. The receive type is set in the login frame per connection.<\/p>\n<h3>Does the feed cover futures and outright markets?<\/h3>\n<p>Yes. Season-long outrights and prediction market topics (elections, economics, crypto) are delivered on <code>futures<\/code> and <code>oddsFutures<\/code> channels. CLV for futures is available via <code>\/futures\/odds\/clv<\/code>.<\/p>\n<p><script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What is the difference between the OddsPapi B2B feed and the v4 developer API?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The v4 API is a REST API for individual developers and analysts. The B2B feed is a WebSocket-first architecture for operators who need real-time delivery, stale detection, resume\/replay cursors, compression, and settlement integration.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"How does staleOdds work?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"The staleOdds flag is delivered on the bookmakers WebSocket channel. 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