The sports betting data landscape has fractured into two distinct parallel universes.<\/p>\n
On one side, you have the Traditional Sportsbooks<\/strong> (DraftKings, Pinnacle, Bet365). They operate on a “Fixed Odds” model, managed by risk teams and algorithms. They are the giants of volume and liquidity.<\/p>\n On the other side, you have the rising Prediction Markets<\/strong>: Polymarket<\/strong> (Crypto\/Polygon) and Kalshi<\/strong> (CFTC-Regulated). These operate on an “Order Book” model, where prices are set purely by supply and demand from users.<\/p>\n For developers and quantitative bettors, this split is an opportunity. When two markets try to price the same event using different mechanisms, inefficiencies are guaranteed<\/strong>.<\/p>\n In this guide, we’ll show you the new way<\/strong> to access Polymarket and Kalshi data: through OddsPapi’s unified API<\/strong>. One API key. One request. Polymarket, Kalshi, Pinnacle, and 300+ sportsbooks\u2014all normalized and ready to compare.<\/p>\n Before diving into the code, here’s the landscape:<\/p>\n The bottom line:<\/strong> Why juggle 3 different APIs with 3 different data formats when you can get everything in one call?<\/p>\n Before diving into code, you need to understand the fundamental difference between these market types.<\/p>\n Both Kalshi and Polymarket function like the Nasdaq. They use a CLOB (Central Limit Order Book)<\/strong>.<\/p>\n Sportsbooks function like a casino dealer.<\/p>\n The opportunity:<\/strong> When these two systems price the same event differently, you can exploit the gap.<\/p>\n Here’s the old way to get Polymarket data:<\/p>\n The new way?<\/strong> One API call:<\/p>\n OddsPapi doesn’t just give you the midpoint. For prediction markets, you get the full order book via This gives you:<\/p>\n Kalshi is CFTC-regulated and available to US residents. OddsPapi includes Kalshi as a bookmaker with Coverage Note:<\/strong> Kalshi’s sports coverage focuses on major US events (NFL spreads, totals, player props). For Kalshi-only markets like elections or economic indicators, you’ll still need their direct API. But for sports betting arbitrage? OddsPapi has you covered.<\/p>\n Kalshi excels at non-sports prediction markets. If you need elections, weather, or economic data, here’s their public endpoint:<\/p>\n This is where OddsPapi saves you the most time. The old approach required manual conversion:<\/p>\n With OddsPapi, all prices come pre-normalized to decimal odds.<\/strong> Polymarket, Kalshi, Pinnacle, Bet365\u2014they’re all in the same format, ready to compare.<\/p>\n Understanding the math helps you interpret the data:<\/p>\nQuick Comparison: The Old Way vs. OddsPapi<\/h2>\n
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\n \nFeature<\/th>\n Polymarket Direct<\/th>\n Kalshi Direct<\/th>\n OddsPapi (Unified)<\/th>\n<\/tr>\n<\/thead>\n \n Data Sources<\/strong><\/td>\n Polymarket only<\/td>\n Kalshi only<\/td>\n Polymarket + Kalshi + 300+ Sportsbooks<\/strong><\/td>\n<\/tr>\n \n Price Format<\/strong><\/td>\n $0.00\u2013$1.00 shares<\/td>\n 1\u00a2\u201399\u00a2 contracts<\/td>\n Decimal odds (normalized)<\/strong><\/td>\n<\/tr>\n \n Auth Required<\/strong><\/td>\n No (read-only)<\/td>\n No (public endpoints)<\/td>\n 1 API Key (covers everything)<\/strong><\/td>\n<\/tr>\n \n Data Normalization<\/strong><\/td>\n DIY conversion<\/td>\n DIY conversion<\/td>\n Already done for you<\/strong><\/td>\n<\/tr>\n \n Order Book Depth<\/strong><\/td>\n Yes (via CLOB)<\/td>\n Yes (bid\/ask)<\/td>\n Yes (via exchangeMeta)<\/strong><\/td>\n<\/tr>\n \n Arbitrage Detection<\/strong><\/td>\n Must combine with sportsbook API<\/td>\n Must combine with sportsbook API<\/td>\n Compare all sources in one response<\/strong><\/td>\n<\/tr>\n \n Python Libraries<\/strong><\/td>\n py-clob-client, gamma-api<\/td>\n requests + JWT handling<\/td>\n Just requests<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n Part 1: Understanding the Market Types<\/h2>\n
Prediction Markets (The Order Book Model)<\/h3>\n
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Traditional Sportsbooks (The Dealer Model)<\/h3>\n
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Part 2: Accessing Polymarket via OddsPapi<\/h2>\n
# The OLD way - juggling multiple libraries\npip install py-clob-client\nfrom py_clob_client.client import ClobClient\n\nclient = ClobClient(\"https:\/\/clob.polymarket.com\")\nmarkets = client.get_simplified_markets()\n# Then manually normalize prices...\n# Then separately query sportsbooks...\n# Then try to match events across APIs...<\/code><\/pre>\nimport requests\n\nAPI_KEY = \"YOUR_ODDSPAPI_KEY\"\nBASE_URL = \"https:\/\/api.oddspapi.io\/v4\"\n\n# Get Polymarket + Pinnacle + Bet365 in ONE request\nresponse = requests.get(\n f\"{BASE_URL}\/odds\",\n params={\n \"apiKey\": API_KEY,\n \"fixtureId\": \"id1400003167969464\", # Any NFL\/NBA fixture\n \"bookmakers\": \"polymarket,pinnacle,bet365\"\n }\n)\ndata = response.json()\n\n# All odds already normalized to decimal format\npolymarket = data['bookmakerOdds'].get('polymarket', {})\npinnacle = data['bookmakerOdds'].get('pinnacle', {})\nbet365 = data['bookmakerOdds'].get('bet365', {})<\/code><\/pre>\nThe exchangeMeta: Full Order Book Depth<\/h3>\n
exchangeMeta<\/code>:<\/p>\n# Polymarket response includes order book depth\n{\n \"price\": 1.786, # Already in decimal odds\n \"exchangeMeta\": {\n \"back\": [\n {\"cents\": 0.56, \"price\": 1.786, \"size\": 7144.62, \"limit\": 4000.99},\n {\"cents\": 0.57, \"price\": 1.754, \"size\": 271737.16, \"limit\": 154890.18},\n {\"cents\": 0.58, \"price\": 1.724, \"size\": 460004.85, \"limit\": 266802.81}\n ],\n \"lay\": [\n # Opposing side of the book\n ]\n }\n}<\/code><\/pre>\n\n
Part 3: Accessing Kalshi via OddsPapi<\/h2>\n
liveOdds: true<\/code>.<\/p>\n# Include Kalshi in your query\nresponse = requests.get(\n f\"{BASE_URL}\/odds\",\n params={\n \"apiKey\": API_KEY,\n \"fixtureId\": \"YOUR_FIXTURE_ID\",\n \"bookmakers\": \"kalshi,polymarket,pinnacle\"\n }\n)\n\ndata = response.json()\nkalshi = data['bookmakerOdds'].get('kalshi', {})<\/code><\/pre>\nWhen to Use Kalshi Directly<\/h3>\n
import requests\n\n# For non-sports Kalshi markets (elections, etc.)\nurl = \"https:\/\/api.elections.kalshi.com\/trade-api\/v2\/markets\"\nparams = {\"limit\": 10, \"status\": \"open\"}\n\nresponse = requests.get(url, params=params)\nmarkets = response.json().get('markets', [])<\/code><\/pre>\nPart 4: Data Normalization (Already Done)<\/h2>\n
# The OLD way - manual conversion\ndef share_to_decimal(share_price):\n \"\"\"Convert $0.56 share price to 1.786 decimal odds\"\"\"\n return 1 \/ share_price\n\ndef cents_to_decimal(cents):\n \"\"\"Convert 56\u00a2 Kalshi price to 1.786 decimal odds\"\"\"\n return 1 \/ (cents \/ 100)\n\ndef american_to_decimal(american):\n \"\"\"Convert -150 to 1.667 decimal odds\"\"\"\n if american > 0:\n return (american \/ 100) + 1\n else:\n return (100 \/ abs(american)) + 1<\/code><\/pre>\nReference: The Math Behind the Conversions<\/h3>\n