# Collect the posted betting lines for this week's NFL games

**Use case:** 

Returns one row per bookmaker line on upcoming NFL games: spread, over under, both money lines and the favourite, with the matchup and kick-off time. Sports data, not betting advice.

## Input

```json
{
  "dataType": "odds",
  "leagues": [
    "football/nfl"
  ],
  "customLeagues": [],
  "lastNDays": 0,
  "nextNDays": 7,
  "gameState": "scheduled",
  "teamIds": [],
  "eventIds": [],
  "maxItems": 20,
  "includePlayerStats": true,
  "includeRawJson": false,
  "resetDedupMemory": false,
  "emitDuplicates": false,
  "maxRequestsPerSecond": 5,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "BUYPROXIES94952"
    ]
  }
}
```

## Output

```json
{
  "date": {
    "label": "Start time",
    "format": "date"
  },
  "league": {
    "label": "League code"
  },
  "name": {
    "label": "Matchup"
  },
  "state": {
    "label": "State"
  },
  "provider": {
    "label": "Odds provider"
  },
  "details": {
    "label": "Line"
  },
  "spread": {
    "label": "Spread"
  },
  "overUnder": {
    "label": "Over/under"
  },
  "homeMoneyline": {
    "label": "Home ML"
  },
  "awayMoneyline": {
    "label": "Away ML"
  },
  "favourite": {
    "label": "Favourite"
  },
  "homeTeam": {
    "label": "Home team"
  },
  "awayTeam": {
    "label": "Away team"
  },
  "gameUrl": {
    "label": "ESPN link"
  }
}
```

## About this Actor

This example demonstrates how to use [ESPN Scraper: Scores, Standings, Stats, Odds](https://apify.com/automation_craft/espn-sports-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/automation_craft/espn-sports-scraper.md) to learn more, explore other use cases, and run it yourself.


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

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/automation_craft/espn-sports-scraper.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).
