# Tennis Results Scraper - ATP, WTA & Challenger Scores with Odds (`poetsc/tennis-results`) Actor

Daily tennis match results from TennisExplorer: ATP, WTA, Challenger and doubles. Set-by-set scores with tiebreaks, winner, seeds, retirements and closing betting odds, for any date range.

- **URL**: https://apify.com/poetsc/tennis-results.md
- **Developed by:** [Poetsc Data](https://apify.com/poetsc) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 match scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

### What does Tennis Results Scraper do?

Tennis Results Scraper collects finished professional tennis matches from [TennisExplorer](https://www.tennisexplorer.com) for any date or date range: **ATP, WTA, Challenger, ITF/UTR events, singles and doubles**. Every match comes with the set-by-set score (including tiebreaks), winner, seeds, retirement and walkover flags, and the **closing betting odds** shown on TennisExplorer.

A full day of men's singles is typically 150–250 matches. A whole season is a few runs away.

### What data do you get?

| Field | Example |
|---|---|
| date, time | 2026-09-24, 13:05 |
| tour, tournament, tournamentCountry, isChallenger | atp-single, Chengdu, CN, false |
| player1, player2 (+ seeds and profile URLs) | Hurkacz H. (5), Shevchenko A. |
| winner | Hurkacz H. |
| score, sets\[] | 6-3 7-6(10) |
| player1Sets, player2Sets | 2, 0 |
| retired, walkover, finished | false, false, true |
| oddsPlayer1, oddsPlayer2 | 1.19, 4.55 |
| matchId, matchUrl | 3329353 |

### Use cases

- **Sports betting models**: historical results with closing odds for backtesting and ELO/rating systems
- **Tennis analytics and journalism**: form, upsets, head-to-heads across Tour, Challenger and ITF levels
- **Fantasy and prediction apps**: feed yesterday's results into your app every morning with a schedule
- **Datasets for machine learning**: thousands of labelled matches with pre-match market prices

### How to use it

1. Set **Start date** (and optionally **End date**). Leave both empty to get yesterday's results.
2. Pick **Tours**: men's/women's singles and doubles.
3. Optionally filter by tournament name, e.g. `challenger` or `Wimbledon`.
4. Run it, then export JSON, CSV or Excel, or call it via API. Use Apify Schedules to collect results every day automatically.

### Input example

```json
{
  "startDate": "2026-09-01",
  "endDate": "2026-09-07",
  "tours": ["atp-single", "wta-single"],
  "tournamentFilter": ""
}
```

### Output example

```json
{
  "date": "2026-09-24",
  "time": "13:05",
  "tour": "atp-single",
  "tournament": "Chengdu",
  "tournamentCountry": "CN",
  "isChallenger": false,
  "player1": "Hurkacz H.",
  "player1Seed": "5",
  "player2": "Shevchenko A.",
  "player2Seed": null,
  "winner": "Hurkacz H.",
  "player1Sets": 2,
  "player2Sets": 0,
  "score": "6-3 7-6(10)",
  "sets": [
    { "player1": 6, "player2": 3, "tiebreak": null },
    { "player1": 7, "player2": 6, "tiebreak": 10 }
  ],
  "retired": false,
  "walkover": false,
  "finished": true,
  "oddsPlayer1": 1.19,
  "oddsPlayer2": 4.55,
  "matchId": "3329353",
  "matchUrl": "https://www.tennisexplorer.com/match-detail/?id=3329353"
}
```

### How much does it cost?

You pay per match saved (see the Pricing tab). A week of ATP + WTA singles results (around 2,500 matches) costs a few dollars, and the Actor runs on the smallest memory setting.

### Notes

- Odds are the closing prices displayed on TennisExplorer's results pages, when available.
- Only finished matches are saved by default. Turn on **Include unfinished matches** to also keep scheduled or in-progress rows.
- The Actor paces its requests politely. Very long date ranges take a while; split them across runs if you are in a hurry.

### Feedback

Missing a field or found a parsing issue? Open an issue on the Issues tab with the date and match.

# Actor input Schema

## `startDate` (type: `string`):

First day to scrape (YYYY-MM-DD). Defaults to yesterday.

## `endDate` (type: `string`):

Last day to scrape (YYYY-MM-DD). Leave empty to scrape only the start date.

## `tours` (type: `array`):

Which result lists to scrape. Men's lists include ATP Tour, Challenger and ITF/UTR events; women's include WTA, WTA 125 and ITF.

## `tournamentFilter` (type: `string`):

Optional. Only keep matches whose tournament name contains this text, e.g. "challenger" or "Chengdu".

## `includeUnfinished` (type: `boolean`):

Also save scheduled or in-progress matches found on the results page.

## `maxMatches` (type: `integer`):

Stop after this many matches.

## `requestDelayMs` (type: `integer`):

Politeness delay between page requests.

## Actor input object example

```json
{
  "tours": [
    "atp-single",
    "wta-single"
  ],
  "includeUnfinished": false,
  "maxMatches": 5000,
  "requestDelayMs": 1500
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("poetsc/tennis-results").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("poetsc/tennis-results").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call poetsc/tennis-results --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,poetsc/tennis-results"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/4eJGwwGhjtRABCHnS/builds/rUVqBUzBtTWYLWb08/openapi.json