# Nfl This Week Kalshi Vs Polymarket Odds

**Use case:** 

NFL games priced on both Kalshi and Polymarket with the cross-venue odds gap. Free first 50 rows.

## Input

```json
{
  "leagues": [
    "nfl"
  ],
  "onlyBothVenues": true,
  "maxResults": 50
}
```

## Output

```json
{
  "league": {
    "label": "League"
  },
  "game_date": {
    "label": "Date"
  },
  "team": {
    "label": "Team"
  },
  "opponent": {
    "label": "Opponent"
  },
  "kalshi_implied_prob": {
    "label": "Kalshi prob"
  },
  "polymarket_implied_prob": {
    "label": "Polymarket prob"
  },
  "cross_venue_gap_after_fees": {
    "label": "Gap after fees"
  },
  "venues": {
    "label": "Venues"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Kalshi vs Polymarket Odds Gap - NFL NBA NHL MLB NCAAF Actor is ready to run with the inputs already set for "Nfl This Week Kalshi Vs Polymarket Odds". [Sign up or log in](https://console.apify.com/create-task-from-example/Yg4cp2RM1vVJnIi7u) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Nfl This Week Kalshi Vs Polymarket Odds" task

The Kalshi vs Polymarket Odds Gap - NFL NBA NHL MLB NCAAF Actor will start running based on the input automatically. You can also change all the input fields, like leagues (blank = all), only games on both venues, and more, to match your specific use case.

### 3. Receive the "Nfl This Week Kalshi Vs Polymarket Odds" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as league, date, team, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Nfl This Week Kalshi Vs Polymarket Odds" task via API](https://apify.com/exemplary_mezzo/sports-odds-api-kalshi-polymarket.md).

## About this Actor

This example demonstrates how to use [Kalshi vs Polymarket Odds Gap - NFL NBA NHL MLB NCAAF](https://apify.com/exemplary_mezzo/sports-odds-api-kalshi-polymarket.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/exemplary_mezzo/sports-odds-api-kalshi-polymarket.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/exemplary_mezzo/sports-odds-api-kalshi-polymarket.md

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`).