# TennisExplorer Scraper - Matches, Players, H2H & Odds (`kmscrape/tennisexplorer-scraper`) Actor

Scrape TennisExplorer: daily ATP/WTA/ITF match results and fixtures, player profiles, tournament draws and head-to-head records. Clean JSON rows, no login. Pay only $1.50 per 1,000 results.

- **URL**: https://apify.com/kmscrape/tennisexplorer-scraper.md
- **Developed by:** [kfir messika](https://apify.com/kmscrape) (community)
- **Categories:** Sports
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.50 / 1,000 results

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

## TennisExplorer Scraper

Collect public TennisExplorer schedules and results, player profiles, tournament pages and match-detail head-to-head comparisons. Match rows include player names and profile URLs, set scores, tournament, round and surface when shown, odds when present, and the source match URL. Profiles include country, birth date, rankings, playing hand, surface records and recent match links when the page exposes them.

The actor uses public TennisExplorer HTML pages and does not require an account. Site fields can change, some list rows omit round or surface, and odds may be absent. ATP/WTA list filters and all-event pages are supported. Challenger and ITF categories are included when present in the returned page; the site does not present all event categories as stable dedicated date filters.

### Inputs

- `dates`: dates in `YYYY-MM-DD` format. The prefilled date is 2026-10-09.
- `matchTypes`: all, ATP/WTA singles or doubles, Challenger, or ITF.
- `playerUrls`: player profile URLs or profile slugs.
- `tournamentUrls`: tournament page URLs.
- `matchUrls`: match-detail URLs or match IDs for H2H comparison.
- `maxItems`: maximum charged rows, default 500; prefilled to 30.

Rows have `type` `match`, `player`, or `tournament`. Match and profile/tournament outputs are charged under event `result`; summary and error rows are free.

### Example output

Trimmed live fields observed on the results page:

```json
{
  "type": "match",
  "date": "2026-10-09",
  "status": "result",
  "tournament": "Shanghai",
  "surface": "hard",
  "player1": "Mannarino A.",
  "player2": "Cobolli F.",
  "score": { "player1": ["6", "4", "6"], "player2": ["1", "6", "3"], "setsWon": { "player1": 2, "player2": 1 } },
  "odds": { "home": 2.58, "away": 1.49 },
  "url": "https://www.tennisexplorer.com/match-detail/?id=3343965"
}
```

Player profile example fields observed: `Seyboth Wild Thiago`, country `Brazil`, birth date `10. 3. 2000`, singles current/high rank `136. / 58.`, playing hand `right`, and surface W/L rows such as clay `252/173` career and `35/14` in 2026.

### Use cases

- Build match calendars and historical results for tennis dashboards.
- Join profile and surface form data to scouting or tournament analysis.
- Feed match and player records to AI agents / MCP workflows that need public tennis context.
- Track event draw pages and compare player head-to-head records.

### Pricing

**$1.50 per 1,000 results**

### FAQ

**Can I request old or future dates?** Yes. Results depend on the date and coverage available on TennisExplorer.

**Are scores and odds always present?** No. Upcoming matches may have no score, and bookmakers may not publish odds for every match.

**Does the actor return full draw brackets?** It returns available draw navigation and match rows from the requested tournament page. Bracket details depend on the page markup.

**Does it include doubles?** The source exposes ATP and WTA singles and doubles tabs. Use the relevant match type where the page provides those rows.

**Are account-only features included?** No. Only pages accessible without signing in are scraped.

# Actor input Schema

## `dates` (type: `array`):

Dates to scrape as YYYY-MM-DD. Each date fetches the site's results and match schedule pages.

## `matchTypes` (type: `string`):

Tour and format filter. The site exposes ATP/WTA singles and doubles selectors; all includes Challenger and ITF rows present in the date page.

## `playerUrls` (type: `array`):

TennisExplorer player profile URLs or player slugs to scrape.

## `tournamentUrls` (type: `array`):

TennisExplorer tournament page URLs to scrape, including match schedule and draw links.

## `matchUrls` (type: `array`):

Match detail URLs (or match URLs) to retrieve player comparison and head-to-head data.

## `maxItems` (type: `integer`):

Maximum charged match, player, and tournament rows to output across this run.

## Actor input object example

```json
{
  "dates": [
    "2026-10-09"
  ],
  "matchTypes": "all",
  "maxItems": 30
}
```

# 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 = {
    "dates": [
        "2026-10-09"
    ],
    "maxItems": 30
};

// Run the Actor and wait for it to finish
const run = await client.actor("kmscrape/tennisexplorer-scraper").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 = {
    "dates": ["2026-10-09"],
    "maxItems": 30,
}

# Run the Actor and wait for it to finish
run = client.actor("kmscrape/tennisexplorer-scraper").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 '{
  "dates": [
    "2026-10-09"
  ],
  "maxItems": 30
}' |
apify call kmscrape/tennisexplorer-scraper --silent --output-dataset

```

## MCP server setup

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

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/0GRT2Tdn1NP5Xcfiv/builds/DKRS4XnI1gZV5IilK/openapi.json