> ## Documentation Index > Fetch the complete documentation index at: https://oddsstream.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Odds > Query current bookmaker odds across all scraped markets. ## GET /api/odds Returns current bookmaker odds — one row per `(event × bookmaker × market_type × period)` combination. The `odds` field is an object keyed by selection text, making it easy to compare prices across bookmakers for the same market. For the full market breakdown of a single event (all bookmakers, all markets, grouped), use `GET /api/events/{id}` instead. ### Query Parameters | Parameter | Type | Default | Description | | ------------- | ------- | ------- | ----------------------------------------------------------- | | `sport` | string | — | Filter by sport name (e.g. `Football`, `Tennis`) | | `competition` | string | — | Filter by competition code (e.g. `EPL`, `NBA`) | | `bookmaker` | string | — | Filter by bookmaker name (e.g. `Winamax`, `Betclic`) | | `market_type` | string | — | Filter by market type (e.g. `moneyline`, `spread`, `total`) | | `is_live` | boolean | — | `true` = in-play only, `false` = pre-match only | | `limit` | integer | `100` | Max rows returned, up to 500 | ### Response ```json theme={null} { "data": [ { "bookmaker": "Betsson", "match_name": "Crystal Palace - West Ham United", "competition": "EPL", "sport": "Football", "market_type": "moneyline", "period": 0, "is_live": false, "odds": { "Crystal Palace": 3.40, "Draw": 3.25, "West Ham United": 2.10 }, "match_date": "2026-04-20T20:00:00Z", "scraped_at": "2026-04-20T14:11:09Z", "url": "https://www.betsson.fr/paris-sportifs/event/4237119.1" }, { "bookmaker": "Winamax", "match_name": "Crystal Palace - West Ham United", "competition": "EPL", "sport": "Football", "market_type": "moneyline", "period": 0, "is_live": false, "odds": { "Crystal Palace": 3.35, "Draw": 3.20, "West Ham United": 2.15 }, "match_date": "2026-04-20T20:00:00Z", "scraped_at": "2026-04-20T14:07:11Z", "url": "https://www.winamax.fr/paris-sportifs/sports/..." }, { "bookmaker": "Unibet.fr", "match_name": "Cleveland Cavaliers / Toronto Raptors", "competition": "NBA", "sport": "Basketball", "market_type": "player_prop", "period": 0, "is_live": false, "odds": { "RJ Barrett Rebounds Over 4.5": 2.12, "RJ Barrett Rebounds Under 4.5": 1.72 }, "match_date": "2026-04-20T23:00:00Z", "scraped_at": "2026-04-20T13:51:28Z", "url": null } ], "meta": { "count": 12847, "rate_limit_remaining": 295 } } ``` ### Response Fields | Field | Type | Description | | ------------- | ----------------------- | -------------------------------------------------------- | | `bookmaker` | string | Bookmaker name | | `match_name` | string | Canonical event name from the scraper | | `competition` | string | Competition code | | `sport` | string | Sport derived from competition code | | `market_type` | string | Market type — see table below | | `period` | integer | Time segment (0=full time, 1=1st half, etc.) | | `is_live` | boolean | `true` if this is an in-play market | | `odds` | object | Keyed by selection text → decimal odds value | | `match_date` | ISO-8601 string \| null | Scheduled kick-off (UTC) | | `scraped_at` | ISO-8601 string | When these odds were last scraped | | `url` | string \| null | Direct deep-link to this market on the bookmaker site | | `liquidity` | float \| null | Pinnacle max bet size (only populated for Pinnacle rows) | ### `odds` Object Format The `odds` field groups all selections for this `(bookmaker, event, market, period)` combination into a single object. Selection texts vary by market type: | Market Type | Typical `odds` keys | | ---------------------- | ------------------------------------------------------------- | | `moneyline` (football) | `"Home Team"`, `"Draw"`, `"Away Team"` | | `moneyline` (other) | `"Home Team"`, `"Away Team"` | | `spread` | `"Home Team +1.5"`, `"Away Team -1.5"` | | `total` | `"Over 2.5"`, `"Under 2.5"` | | `btts` | `"Yes"`, `"No"` | | `double_chance` | `"1X"`, `"X2"`, `"12"` | | `player_prop` | `"Player Name Stat Over X.X"`, `"Player Name Stat Under X.X"` | | `team_total` | `"Home Over 1.5"`, `"Home Under 1.5"` | *** ## GET /api/odds/live Same as `GET /api/odds` but returns only in-play events. Requires **Pro+ Live** plan. ### Query Parameters Identical to `GET /api/odds` (same filters, same `limit`). ### Notes * Live odds update every 5–10 seconds. Poll accordingly. * Bookmakers with live coverage: Betclic, Winamax (selected events), Unibet.fr (selected events). *** ## GET /api/odds/{bookmaker} Returns all current odds for a specific bookmaker. Equivalent to `GET /api/odds?bookmaker={bookmaker}` but slightly more efficient. ### Path Parameter | Parameter | Description | | ----------- | ----------------------------------------------------------------------------------------------- | | `bookmaker` | Exact bookmaker name (e.g. `Winamax`, `Betclic`) — use `GET /api/bookmakers` to get valid names | ### Query Parameters | Parameter | Type | Default | Description | | ------------- | ------- | ------- | -------------------------- | | `sport` | string | — | Filter by sport | | `competition` | string | — | Filter by competition code | | `market_type` | string | — | Filter by market type | | `is_live` | boolean | — | In-play filter | | `limit` | integer | `100` | Max rows, up to 500 | ### Response Same format as `GET /api/odds`. *** ## Code Examples ```bash theme={null} # All EPL moneyline odds curl "https://api.oddsstream.io/api/odds?competition=EPL&market_type=moneyline" \ -H "X-Api-Key: os_live_YOUR_KEY" # All Betclic odds curl "https://api.oddsstream.io/api/odds/Betclic" \ -H "X-Api-Key: os_live_YOUR_KEY" # All Winamax football spreads curl "https://api.oddsstream.io/api/odds/Winamax?sport=Football&market_type=spread" \ -H "X-Api-Key: os_live_YOUR_KEY" # Live basketball odds (Pro+ Live) curl "https://api.oddsstream.io/api/odds/live?sport=Basketball" \ -H "X-Api-Key: os_live_YOUR_KEY" ``` ```python theme={null} import requests API_KEY = "os_live_YOUR_KEY" # Get all LIG1 moneyline rows resp = requests.get( "https://api.oddsstream.io/api/odds", params={"competition": "LIG1", "market_type": "moneyline", "limit": 200}, headers={"X-Api-Key": API_KEY} ) rows = resp.json()["data"] # Group by match name to compare bookmakers from collections import defaultdict by_match = defaultdict(list) for row in rows: by_match[row["match_name"]].append(row) # Find best odds per selection for match, bookmaker_rows in by_match.items(): print(f"\n{match}") # Collect all selections from all bookmakers all_selections = {} for row in bookmaker_rows: for sel, odds in row["odds"].items(): if sel not in all_selections or odds > all_selections[sel]["odds"]: all_selections[sel] = {"odds": odds, "bookmaker": row["bookmaker"]} for sel, best in all_selections.items(): print(f" {sel}: {best['odds']} @ {best['bookmaker']}") ``` ```javascript theme={null} // Poll all EPL odds every 30 seconds async function pollOdds() { const resp = await fetch( "https://api.oddsstream.io/api/odds?competition=EPL&market_type=moneyline&limit=500", { headers: { "X-Api-Key": "os_live_YOUR_KEY" } } ); const { data, meta } = await resp.json(); console.log(`${data.length} odds rows, ${meta.rate_limit_remaining} requests remaining`); // Build lookup: match → bookmaker → odds const lookup = {}; for (const row of data) { if (!lookup[row.match_name]) lookup[row.match_name] = {}; lookup[row.match_name][row.bookmaker] = row.odds; } return lookup; } setInterval(pollOdds, 30_000); ```