# Every ATP tour match of a season with closing odds

**Use case:** 

All ATP tournaments of the year in one run — from the Grand Slams to ATP 250s — with opening and closing odds from up to 42 bookmakers, the no-vig consensus, line movement and scores. The dataset tennis models are trained on.

## Input

```json
{
  "mode": "tournaments",
  "statuses": [
    "finished",
    "scheduled"
  ],
  "daysBack": 1,
  "daysAhead": 1,
  "tours": [
    "ATP",
    "WTA",
    "CHALLENGER",
    "ITF",
    "TEAMS",
    "OTHER"
  ],
  "formats": [
    "SINGLES"
  ],
  "tournaments": [
    "ATP: all"
  ],
  "years": [
    "2024"
  ],
  "lastYears": 1,
  "includeQualifying": false,
  "includeOdds": true,
  "onlyWithOdds": false,
  "includeStats": false,
  "includePointByPoint": false,
  "includeRankings": true,
  "maxMatches": 30
}
```

## Output

```json
{
  "startTime": {
    "label": "Start (UTC)",
    "format": "date"
  },
  "tour": {
    "label": "Tour"
  },
  "tournament": {
    "label": "Tournament"
  },
  "surface": {
    "label": "Surface"
  },
  "player1": {
    "label": "Player 1"
  },
  "player2": {
    "label": "Player 2"
  },
  "player1Rank": {
    "label": "Rank P1",
    "format": "number"
  },
  "player2Rank": {
    "label": "Rank P2",
    "format": "number"
  },
  "status": {
    "label": "Status"
  },
  "score": {
    "label": "Score"
  },
  "winner": {
    "label": "Winner",
    "format": "number"
  },
  "consensus": {
    "label": "Consensus"
  }
}
```

## About this Actor

This example demonstrates how to use [Tennis Scraper: Live Scores, Results & Odds from 40+ Books](https://apify.com/sports-odds-lab/tennis-odds-results.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/sports-odds-lab/tennis-odds-results.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/sports-odds-lab/tennis-odds-results.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`).