# 🔮 Polymarket Odds, Whale Bets & Prediction Radar (`unrivaled_fortress/polymarket-prediction-odds-radar`) Actor

Extract real-time Polymarket prediction market betting odds, 24h trading volume, implied event probabilities, and breakout geopolitical/crypto events. Built for quants, newsrooms & AI agents.

- **URL**: https://apify.com/unrivaled\_fortress/polymarket-prediction-odds-radar.md
- **Developed by:** [David A](https://apify.com/unrivaled_fortress) (community)
- **Categories:** AI, Developer tools, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.95 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 🔮 Polymarket Prediction Odds, Whale Bets & Event Probabilities

Extract **real-time Polymarket prediction market betting odds, 24-hour trading volumes, market questions, and implied event probabilities** without API keys or authentication walls.

Built for **Quantitative Hedge Funds, Crypto Traders, Political Analysts, Newsrooms, and AI Autonomous Agents**.

***

### 🎯 Key Features

- **Real-Time Odds & Probabilities**: Extract implied probability percentages (`0-100%`), YES/NO share prices, and contract settlement questions.
- **Whale Volume & Liquidity Tracking**: Filter breakout markets by 24h volume ($ USD) and total market pool liquidity.
- **Categorical Filtering**: Filter by Politics & Elections, Crypto & DeFi, Macro Economy, Pop Culture, and Science/AI.
- **AI Agent Ready**: Perfect data oracle feed for LLMs (Claude, GPT-4, Cursor) analyzing current world probabilities.

***

### 💼 High-Value Use Cases

- **Geopolitical & Macro Hedge Fund Alpha**: Track real-time market probability of interest rate cuts, elections, and regulatory decisions before traditional polls report.
- **Autonomous AI Decision Agents**: Equip AI reasoning agents with ground-truth market odds via Apify MCP integrations.
- **Crypto & Event Arbitrage**: Monitor odds differences across prediction markets (Polymarket vs. Kalshi vs. PredictIt).

***

### ⚙️ Input Configuration

| Parameter | Type | Description | Default |
| :--- | :--- | :--- | :--- |
| `tagSlug` | Select | Category filter (`all`, `politics`, `crypto`, `pop-culture`, `business`, `science`). | `'all'` |
| `limit` | Integer | Max events to scan (5 to 100). | `25` |
| `minVolume24h` | Integer | Minimum 24h trading volume in USD. | `1000` |
| `orderBy` | Select | Sort order (`volume24hr`, `volume`, `startDate`). | `'volume24hr'` |

# Actor input Schema

## `tagSlug` (type: `string`):

Filter by market category (e.g. 'all', 'politics', 'crypto', 'pop-culture', 'business', 'science').

## `limit` (type: `integer`):

Maximum number of prediction events to extract.

## `minVolume24h` (type: `integer`):

Only return events with at least $X in 24h trading volume.

## `orderBy` (type: `string`):

Rank markets by highest 24h volume or total cumulative volume.

## Actor input object example

```json
{
  "tagSlug": "all",
  "limit": 25,
  "minVolume24h": 1000,
  "orderBy": "volume24hr"
}
```

# Actor output Schema

## `results` (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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("unrivaled_fortress/polymarket-prediction-odds-radar").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("unrivaled_fortress/polymarket-prediction-odds-radar").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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 unrivaled_fortress/polymarket-prediction-odds-radar --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,unrivaled_fortress/polymarket-prediction-odds-radar"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/IcHAX63Citq3kX9fH/builds/sJVqah3omufXfd56s/openapi.json