# Polymarket Rewards Scraper (`parsebird/polymarket-rewards-scraper`) Actor Scrape Polymarket markets with active liquidity rewards. Get daily reward rates, max spread requirements, min share sizes, competitiveness scores, and real-time pricing data. Filter by category, reward rate, and keyword. - **URL**: https://apify.com/parsebird/polymarket-rewards-scraper.md - **Developed by:** [ParseBird](https://apify.com/parsebird) (community) - **Categories:** Agents, Automation, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $1.49 / 1,000 polymarket rewards data 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 ### Polymarket Rewards Scraper Scrape [Polymarket](https://polymarket.com/rewards) markets with active liquidity rewards. Get daily reward rates, max spread requirements, min share sizes, competitiveness scores, and real-time pricing data. Filter by category, reward rate, and keyword. Fast API-based scraping — no browser needed.
Extract Polymarket liquidity reward data — daily USDC reward rates, spread requirements, competitiveness scores, outcome prices, and volume — powered by public APIs for maximum speed and reliability.

ParseBird Polymarket Suite   •  Prediction market data at scale
 Leaderboard
Top traders, wallets, P&L, positions 		 Markets
Prices, volume, liquidity, outcomes 		 Rewards
➤ You are here
##### Copy to your AI assistant Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor. ```` parsebird/polymarket-rewards-scraper on Apify. Call: ApifyClient("TOKEN").actor("parsebird/polymarket-rewards-scraper").call(run\_input={...}), then client.dataset(run\["defaultDatasetId"]).list\_items().items for results. Key inputs: category (string, ""/"politics"/"sports"/"crypto"/"pop-culture"/"middle-east"/"business"/"science", default ""), minRewardRate (number, default 0), maxResults (integer, 1-5000, default 500), keyword (string, default ""), sortBy (string, "rewardRate"/"competitive"/"volume"/"liquidity", default "rewardRate"). Full actor spec: fetch build via GET https://api.apify.com/v2/acts/parsebird~polymarket-rewards-scraper (Bearer TOKEN). Get token: https://console.apify.com/account/integrations ```` ### What does Polymarket Rewards Scraper do? This Actor scrapes Polymarket's prediction markets that have active liquidity reward programs. Market makers earn USDC rewards for placing competitive limit orders on qualifying markets. This scraper extracts the reward configuration and market data for every rewarded market. For each rewarded market, the scraper collects: - **Reward data** — daily USDC reward rate, max spread requirement, min share size - **Competitiveness** — how competitive the market-making is (0–1 score) - **Market data** — question, outcomes, outcome prices, last trade price, bid/ask spread - **Volume metrics** — total volume, 24h volume - **Liquidity** — current market liquidity - **Price changes** — 1-day price change ### Why scrape Polymarket rewards? - **Market making** — Find the most rewarding markets to provide liquidity on - **Reward optimization** — Compare reward rates, spread requirements, and competitiveness to maximize earnings - **Strategy research** — Identify markets where rewards outweigh the risk of adverse selection - **Data analysis** — Build datasets of reward programs for research, modeling, or dashboards - **Competitive intelligence** — Monitor which markets Polymarket is incentivizing and how competitive they are - **Automated alerts** — Schedule runs to detect new high-reward markets or changes in reward rates ### How to use 1. Go to the [Polymarket Rewards Scraper](https://apify.com/parsebird/polymarket-rewards-scraper) page on Apify Store 2. Click **Try for free** 3. Configure your input: - **Category** — All, Politics, Sports, Crypto, Pop Culture, Middle East, Business, Science - **Min Reward Rate** — Filter out low-reward markets (USDC/day) - **Max Results** — How many markets to return (1–5,000) - **Keyword** — Search for specific topics - **Sort By** — Reward Rate, Competitiveness, Volume, or Liquidity 4. Click **Start** and wait for the run to finish 5. Download your data in JSON, CSV, Excel, or connect via API ### Input parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `category` | enum | `""` (all) | Market category: Politics, Sports, Crypto, Pop Culture, Middle East, Business, Science | | `minRewardRate` | number | `0` | Minimum daily reward rate in USDC | | `maxResults` | integer | `500` | Maximum markets to return (1–5,000) | | `keyword` | string | `""` | Search for specific topics (case-insensitive) | | `sortBy` | enum | `rewardRate` | Sort by: `rewardRate`, `competitive`, `volume`, `liquidity` | ### Output data Each result represents one rewarded prediction market: | Field | Type | Description | |-------|------|-------------| | `question` | string | Market question | | `outcomes` | array | Outcome labels (e.g., ["Yes", "No"]) | | `outcomePrices` | array | Outcome prices (e.g., [0.55, 0.45]) | | `rewardsDailyRate` | number | Daily USDC reward rate for this market | | `rewardsMaxSpread` | number | Maximum allowed spread to qualify for rewards | | `rewardsMinSize` | number | Minimum order size (shares) to qualify for rewards | | `competitive` | number | Competitiveness score (0–1, higher = more competitive) | | `volume` | number | Total trading volume (USD) | | `volume24hr` | number | 24-hour trading volume | | `liquidity` | number | Current market liquidity | | `bestBid` | number | Best bid price | | `bestAsk` | number | Best ask price | | `spread` | number | Bid-ask spread | | `lastTradePrice` | number | Last trade price | | `oneDayPriceChange` | number | 24-hour price change | | `endDate` | string | Market resolution deadline | | `rewardStartDate` | string | When the reward program started | | `slug` | string | Market slug | | `marketUrl` | string | Full Polymarket URL | | `scrapedAt` | string | ISO timestamp of when the data was scraped | #### Example output ```json { "question": "Next PM of Hungary - Péter Magyar?", "outcomes": ["Yes", "No"], "outcomePrices": [0.62, 0.38], "rewardsDailyRate": 2000, "rewardsMaxSpread": 3.5, "rewardsMinSize": 200, "competitive": 0.91, "volume": 5200000.00, "volume24hr": 2170000.00, "liquidity": 180000.00, "bestBid": 0.61, "bestAsk": 0.63, "spread": 0.02, "lastTradePrice": 0.62, "oneDayPriceChange": 0.01, "endDate": "2026-12-31T00:00:00Z", "rewardStartDate": "2025-07-23", "slug": "next-pm-of-hungary-peter-magyar", "marketUrl": "https://polymarket.com/event/next-pm-of-hungary-peter-magyar", "scrapedAt": "2026-04-12T10:00:00.000Z" } ```` ### Use with the Apify API ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run = client.actor("parsebird/polymarket-rewards-scraper").call(run_input={ "minRewardRate": 100, "maxResults": 50, "sortBy": "rewardRate", }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(f"{item['question'][:50]} — ${item['rewardsDailyRate']}/day — Comp: {item['competitive']:.2f}") ``` ### Pricing This Actor uses **Pay-per-event** pricing: | Event | Cost | Rate | |-------|------|------| | `pm-rewards-data` | $0.00149 | $1.49 per 1,000 markets | Each rewarded market returned incurs one charge. **Cost examples:** - 100 markets: $0.15 - 500 markets (default): $0.75 - 1,000 markets: $1.49 - 5,000 markets: $7.45 You only pay for the markets actually returned. ### Tips and best practices - **Start with defaults** — Run with default settings to see all rewarded markets sorted by reward rate. - **Filter by reward rate** — Set `minRewardRate` to focus on markets worth your capital. Rates below 1 USDC/day are often placeholder values. - **Check competitiveness** — A `competitive` score near 1.0 means many market makers are already competing. Lower scores may offer easier reward capture. - **Spread requirements matter** — `rewardsMaxSpread` defines how tight your quotes must be. Lower values require tighter spreads. - **Min share size** — `rewardsMinSize` is the minimum order size to qualify. Higher values require more capital. - **Use keyword search** — Find rewarded markets on specific topics (e.g., "bitcoin", "election", "FIFA"). - **Schedule regular runs** — Set up hourly or daily runs to detect new reward programs or rate changes. - **No browser needed** — This Actor uses Polymarket's public REST APIs directly, so it's fast and doesn't require Playwright or residential proxies. ### Integrations Connect this Actor to your workflow: - **Google Sheets** — Export results directly - **Webhooks** — Trigger actions when new data arrives - **API** — Access data programmatically via the Apify API - **Zapier / Make** — Automate downstream workflows ### Limitations - The scraper scans all active markets (~50,000) to find rewarded ones (~5,700), since the API doesn't support server-side reward filtering. Using a category filter significantly reduces scan time. - The **Earnings** and **Percent** columns shown on the Polymarket rewards page are user-specific and require wallet authentication — they cannot be scraped. - Some markets may have `null` values for `bestBid`, `bestAsk`, or `spread` if the order book is empty. - Reward rates and competitiveness scores change frequently — data reflects a point-in-time snapshot. # Actor input Schema ## `category` (type: `string`): Filter rewarded markets by category. Leave empty to include all categories. ## `minRewardRate` (type: `number`): Only include markets with a daily reward rate at or above this threshold. Set to 0 to include all rewarded markets. ## `maxResults` (type: `integer`): Maximum number of rewarded markets to return. ## `keyword` (type: `string`): Search for specific topics. Filters markets where the question contains this keyword (case-insensitive). Leave empty to skip. ## `sortBy` (type: `string`): How to sort the results. ## Actor input object example ```json { "category": "", "minRewardRate": 0, "maxResults": 500, "keyword": "", "sortBy": "rewardRate" } ``` # Actor output Schema ## `dataset` (type: `string`): No description # 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("parsebird/polymarket-rewards-scraper").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("parsebird/polymarket-rewards-scraper").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 parsebird/polymarket-rewards-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parsebird/polymarket-rewards-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Polymarket Rewards Scraper", "description": "Scrape Polymarket markets with active liquidity rewards. Get daily reward rates, max spread requirements, min share sizes, competitiveness scores, and real-time pricing data. Filter by category, reward rate, and keyword.", "version": "1.1", "x-build-id": "9FB2WaKOjgNgDpOcf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parsebird~polymarket-rewards-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parsebird-polymarket-rewards-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parsebird~polymarket-rewards-scraper/runs": { "post": { "operationId": "runs-sync-parsebird-polymarket-rewards-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parsebird~polymarket-rewards-scraper/run-sync": { "post": { "operationId": "run-sync-parsebird-polymarket-rewards-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "category": { "title": "Category", "enum": [ "", "politics", "sports", "crypto", "pop-culture", "middle-east", "business", "science" ], "type": "string", "description": "Filter rewarded markets by category. Leave empty to include all categories.", "default": "" }, "minRewardRate": { "title": "Minimum Daily Reward Rate (USDC/day)", "minimum": 0, "type": "number", "description": "Only include markets with a daily reward rate at or above this threshold. Set to 0 to include all rewarded markets.", "default": 0 }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of rewarded markets to return.", "default": 500 }, "keyword": { "title": "Keyword Search", "type": "string", "description": "Search for specific topics. Filters markets where the question contains this keyword (case-insensitive). Leave empty to skip.", "default": "" }, "sortBy": { "title": "Sort By", "enum": [ "rewardRate", "competitive", "volume", "liquidity" ], "type": "string", "description": "How to sort the results.", "default": "rewardRate" } } }, "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 } } } } } } } } } } ```