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Kalshi Discovery Spider

Introduction

The Kalshi Discovery Spider is an Apify Actor designed to scrape and extract detailed prediction market data from Kalshi, a leading event-based trading platform. By inputting specific queries, users can discover contracts, market details, pricing, and trading volumes related to various topics like politics, economics, and companies. This tool empowers researchers, analysts, and businesses to access real-time, structured data for informed decision-making and trend analysis.

Features

• Comprehensive Data Extraction: Retrieves full contract details including tickers, titles, categories, tags, and topic keywords for targeted queries.
• Real-Time Pricing and Volume: Captures live bid/ask prices, last prices, price deltas, and trading volumes to track market dynamics.
• Flexible Query Support: Accepts multiple queries to explore diverse topics, enabling broad or niche market discovery.
• Structured Output: Delivers clean JSON data with nested market arrays, making it easy to integrate into analytics tools or databases.
• High Reliability: Built on Apify's robust infrastructure for consistent performance and error handling.
• Scalable and Efficient: Handles large datasets without rate limiting issues, ideal for batch processing and automated workflows.

Input Parameters

Parameter	Type	Required	Description	Example
Queries	Array of strings	No	A list of search terms to query Kalshi's prediction markets. Each query discovers related contracts and market data.	["elon", "politics"]

Example Usage

Input

{
  "Queries": ["elon"]
}

Output

[
  {
    "query": "elon",
    "type": "contract",
    "series_ticker": "KXMUSKOAI",
    "series_title": "Elon Win vs Open AI",
    "event_ticker": "KXMUSKOAI-26",
    "event_subtitle": "Before 2027",
    "event_title": "Will Elon win his case against OpenAI?",
    "category": "Politics",
    "tags": ["SCOTUS & courts"],
    "topic_keywords": ["AI", "California", "Elon Musk", "OpenAI", "Supreme Court"],
    "total_series_volume": 1067668,
    "total_volume": 1067668,
    "total_market_count": 1,
    "active_market_count": 1,
    "is_trending": false,
    "is_new": false,
    "is_closing": false,
    "is_price_delta": false,
    "search_score": 2400,
    "fee_type": "quadratic",
    "fee_multiplier": 1,
    "markets": [
      {
        "ticker": "KXMUSKOAI-26",
        "yes_subtitle": "Before 2027",
        "no_subtitle": "",
        "yes_bid": 41,
        "yes_ask": 42,
        "last_price": 41,
        "yes_bid_dollars": "0.4100",
        "yes_ask_dollars": "0.4200",
        "last_price_dollars": "0.4100",
        "price_delta": 0,
        "close_ts": "2027-01-01T15:00:00Z",
        "expected_expiration_ts": "2027-01-01T04:59:00Z",
        "open_ts": "2026-01-14T15:00:00Z",
        "rulebook_variables": {},
        "result": "",
        "score": 4108,
        "market_id": "",
        "title": "",
        "icon_url_dark_mode": "https://kalshi-fallback-images.s3.amazonaws.com/structured_icons/dark_diamond.webp",
        "icon_url_light_mode": "https://kalshi-fallback-images.s3.amazonaws.com/structured_icons/diamond.webp",
        "background_color_light_mode": "#AA00FF",
        "background_color_dark_mode": "#D24DFF",
        "previous_price": 41,
        "previous_price_dollars": "0.4100",
        "volume": 2135337
      }
    ],
    "product_metadata": {
      "categories": ["Politics"],
      "promoted_milestone_id": "",
      "scope": null,
      "series_frequency": "one_off",
      "series_tags": ["SCOTUS & courts"],
      "subcategories": {
        "Politics": ["SCOTUS & courts"]
      }
    },
    "actor_id": "Gs34ZRTE0F7Kh8J47",
    "run_id": "xIplCeAsKvdDOmr0H"
  }
  // Additional results omitted for brevity
]

Use Cases

• Market Research: Analyze trends in prediction markets for topics like politics or economics to inform investment strategies.
• Competitive Intelligence: Track contracts related to companies or individuals, such as Elon Musk, for business insights.
• Price Monitoring: Monitor bid/ask spreads and volumes for real-time trading signals.
• Content Aggregation: Gather data for blogs, reports, or dashboards on emerging market events.
• Academic Research: Study public sentiment and probabilities on future events through structured market data.
• Business Automation: Integrate into workflows for automated data feeds in financial analysis tools.

Installation and Usage

1. Search for "Kalshi Discovery Spider" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters (e.g., add queries).
4. Click "Start" to begin extraction.
5. Monitor progress in the log.
6. Export results in your preferred format (JSON, CSV, Excel).

Output Format

The output is a JSON array of objects, each representing a discovered contract. Key fields include: query (original search term), series_ticker and event_ticker (unique identifiers), event_title and category (descriptive info), markets (array of market details with pricing, timestamps, and volumes), and product_metadata (categorization and tags). This structure ensures easy parsing for analysis, with fields like yes_bid, last_price, and volume providing quantitative data.

Support

For custom/simplified outputs or bug reports, please contact:

• Email: support@getdataforme.com
• Subject line: "custom support"
• Contact form: https://getdataforme.com/contact/

We're here to help you get the most out of this Actor!

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