# Monitor positive Polymarket Kalshi spreads

**Use case:** 

Filter matched Mark Kelly contracts to positive gross two-leg spreads for a scheduled monitoring workflow.

## Input

```json
{
  "keywords": [
    "Mark Kelly"
  ],
  "maxItems": 10,
  "maxMarketsPerVenue": 5000,
  "minMatchConfidence": 0.4,
  "maxExpiryDifferenceHours": 720,
  "estimatedFeesPercent": 0,
  "minNetSpreadPercent": 0,
  "minLiquidityUsd": 0,
  "includeNonProfitable": false
}
```

## Output

```json
{
  "rank": {
    "label": "Rank",
    "format": "integer"
  },
  "matchedTitle": {
    "label": "Contract",
    "format": "string"
  },
  "candidateArbitrage": {
    "label": "Candidate",
    "format": "boolean"
  },
  "estimatedNetSpreadPercent": {
    "label": "Net spread %",
    "format": "number"
  },
  "combinedCost": {
    "label": "Combined cost",
    "format": "number"
  },
  "matchConfidence": {
    "label": "Confidence",
    "format": "number"
  },
  "strategy": {
    "label": "Strategy",
    "format": "string"
  },
  "expiryDifferenceHours": {
    "label": "Expiry difference h",
    "format": "number"
  },
  "observedAt": {
    "label": "Observed",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Polymarket & Kalshi Arbitrage Monitor](https://apify.com/automation-lab/polymarket-kalshi-arbitrage-monitor) with a specific input configuration. Visit the [Actor detail page](https://apify.com/automation-lab/polymarket-kalshi-arbitrage-monitor) to learn more, explore other use cases, and run it yourself.


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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/automation-lab/polymarket-kalshi-arbitrage-monitor.md

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).