# Tennis matches tomorrow with Elo and win probability

**Use case:** 

Today's and tomorrow's scheduled ATP and WTA singles in Jeff Sackmann's columns, with both players' rank, seed, Elo and the Elo win probability of each match. The example returns up to 300 matches; set Max items higher if the draw is bigger.

## Input

```json
{
  "sackmannFile": "upcoming",
  "years": [
    2025
  ],
  "tours": [
    "atp",
    "wta"
  ],
  "maxItems": 300
}
```

## Output

```json
{
  "tourney_date": {
    "label": "Week",
    "format": "number"
  },
  "tourney_name": {
    "label": "Tournament",
    "format": "text"
  },
  "surface": {
    "label": "Surface",
    "format": "text"
  },
  "round": {
    "label": "Round",
    "format": "text"
  },
  "start_time": {
    "label": "Start (UTC)",
    "format": "text"
  },
  "p1_name": {
    "label": "Player 1",
    "format": "text"
  },
  "p1_rank": {
    "label": "Rank",
    "format": "number"
  },
  "p1_elo": {
    "label": "Elo",
    "format": "number"
  },
  "p2_name": {
    "label": "Player 2",
    "format": "text"
  },
  "p2_rank": {
    "label": "Rank",
    "format": "number"
  },
  "p2_elo": {
    "label": "Elo",
    "format": "number"
  },
  "p1_win_probability": {
    "label": "Player 1 win probability",
    "format": "number"
  }
}
```

## How it works

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

The ATP & WTA Tennis Match Dataset - Sackmann CSV Format Actor is ready to run with the inputs already set for "Tennis matches tomorrow with Elo and win probability". [Sign up or log in](https://console.apify.com/create-task-from-example/rhSbYY03BMgMzb1rQ) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Tennis matches tomorrow with Elo and win probability" task

The ATP & WTA Tennis Match Dataset - Sackmann CSV Format Actor will start running based on the input automatically. You can also change all the input fields, like file, years, and more, to match your specific use case.

### 3. Receive the "Tennis matches tomorrow with Elo and win probability" 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 week, tournament, surface, 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 "Tennis matches tomorrow with Elo and win probability" task via API](https://apify.com/crawlplant/tennis-match-dataset.md).

## About this Actor

This example demonstrates how to use [ATP & WTA Tennis Match Dataset - Sackmann CSV Format](https://apify.com/crawlplant/tennis-match-dataset.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/crawlplant/tennis-match-dataset.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/crawlplant/tennis-match-dataset.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`).