# Horse Racing Pulse (`0xgollum/horse-racing-pulse`) Actor Tracks live PMU (France) horse-racing odds for races still open to betting, and flags implied-probability steamers and drifters between runs. - **URL**: https://apify.com/0xgollum/horse-racing-pulse.md - **Developed by:** [0xGollum](https://apify.com/0xgollum) (community) - **Categories:** Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $2.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Horse Racing Pulse 🐎 **A shortening price is one of the oldest tells in racing. Catch it before the off.** Pari-mutuel odds aren't fixed by a bookmaker — they float with the betting pool right up to post time. When real money (often smart money) lands on a horse, its price shortens fast. This actor watches that movement across every PMU race still open for betting, continuously. ### What you get Two row types: - **Snapshot** — current odds + implied probability for every horse in every tracked race - **Signal** — a named, fired condition: | Signal | Meaning | |--------|---------| | `steamer` | A horse's implied probability jumped between runs — money coming in fast, price shortening | | `drifter` | A horse's implied probability faded between runs — confidence draining, price lengthening | ### Sources (public, no API key, no proxy) **PMU** (Pari Mutuel Urbain) — France's official pari-mutuel operator, exposes a fully public, key-less JSON API used by its own web and app clients. Covers French tracks (flat, trot, jump) plus a handful of foreign tracks PMU takes bets on. No account, no login, no proxy needed. Only races still open for betting are scanned (`PROGRAMMEE`, `ROUGE_AUX_PARTANTS`, `DEPART_DANS_TROIS_MINUTES` status) — finished races are skipped automatically, so every run's actionable. ### Use cases - **Punters** — spot steamers before the crowd, avoid drifters - **Value bettors** — price movement is a core tell for market confidence shifts - **Content & tipster sites** — power previews with live movement data - **Bots & automations** — feed clean signals into your own alerting pipeline ### Input (all optional) | Field | Default | Description | |-------|---------|--------------| | `max_races` | `20` | How many soonest-starting active races to scan per run | | `movement_threshold_pct` | `5` | Minimum implied-probability change (percentage points) between runs to fire a signal | | `only_signals` | `false` | Skip snapshots, only push steamer/drifter rows | ### Output ```json { "type": "signal", "signal": "steamer", "hippodrome": "CHANTILLY", "num_reunion": 1, "num_course": 8, "race_name": "LE ROI SOLEIL", "horse_num": 4, "horse_name": "INGEBORG", "prob_change_pct": 6.8, "current_cote": 5.2, "current_prob_pct": 19.2, "previous_prob_pct": 12.4, "message": "INGEBORG (#4) at CHANTILLY R1C8: odds shortened to 5.2 (12.4% -> 19.2% implied) — money coming in fast." } ```` ### Pricing **Pay per result:** **$0.002 per row** (snapshots + signals). ### Tips - **Schedule it** every 10–15 min during racing hours to catch steam as it builds toward post time; movement between two runs is what triggers a signal, so it needs a persistent schedule (not one-off runs) to be useful. - Lower `movement_threshold_pct` for more sensitivity (more signals, more noise) or raise it to only catch big moves. - Races close to post time move fastest — `max_races` is sorted soonest-first by default. *** *⚠️ Not betting advice. Odds movement reflects market activity, not a guaranteed outcome. This actor surfaces public odds data — it does not place bets or guarantee profit.* # Actor input Schema ## `max_races` (type: `integer`): How many soonest-starting races still open for betting to scan per run. ## `movement_threshold_pct` (type: `number`): Minimum implied-probability change (in percentage points) between runs to fire a steamer/drifter signal. Default 5. ## `only_signals` (type: `boolean`): If true, skip snapshot rows and only push steamer/drifter signal rows. ## Actor input object example ```json { "max_races": 20, "movement_threshold_pct": 5, "only_signals": false } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("0xgollum/horse-racing-pulse").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("0xgollum/horse-racing-pulse").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call 0xgollum/horse-racing-pulse --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=0xgollum/horse-racing-pulse", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Horse Racing Pulse", "description": "Tracks live PMU (France) horse-racing odds for races still open to betting, and flags implied-probability steamers and drifters between runs.", "version": "0.1", "x-build-id": "0Ermcp9yuT6PaQdwi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/0xgollum~horse-racing-pulse/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-0xgollum-horse-racing-pulse", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/0xgollum~horse-racing-pulse/runs": { "post": { "operationId": "runs-sync-0xgollum-horse-racing-pulse", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/0xgollum~horse-racing-pulse/run-sync": { "post": { "operationId": "run-sync-0xgollum-horse-racing-pulse", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "max_races": { "title": "Max active races", "type": "integer", "description": "How many soonest-starting races still open for betting to scan per run.", "default": 20 }, "movement_threshold_pct": { "title": "Movement threshold (percentage points)", "type": "number", "description": "Minimum implied-probability change (in percentage points) between runs to fire a steamer/drifter signal. Default 5.", "default": 5 }, "only_signals": { "title": "Only output signals", "type": "boolean", "description": "If true, skip snapshot rows and only push steamer/drifter signal rows.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```