# Tennis Explorer Scraper · Matches & Odds (`bibian/tennisexplorer-scraper`) Actor

Extract ATP and WTA tennis match results, upcoming matches and pre-match odds from Tennis Explorer: tournament, round players, set scores and betting odds for singles and doubles.

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

## Pricing

from $4.50 / 1,000 matches

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

## Tennis Explorer Scraper · Matches & Odds

Scrape ATP and WTA tennis match results, upcoming matches and pre-match odds from [Tennis Explorer](https://www.tennisexplorer.com), and get clean structured data: tournament, players, set scores and betting odds for singles and doubles.

### What you can do with it

- **Track results daily**: pull finished matches for the last few days, with full set scores and the winner.
- **Watch upcoming matches and odds**: get scheduled and live matches with their pre-match odds before they start.
- **Feed a betting or stats model**: odds plus set-by-set scores in one normalized record, for ATP and WTA, singles and doubles.
- **Follow a tour level**: Futures, Challengers and main tour are all covered, so you can track a player's whole season.

### Input

| Field | What it does |
|---|---|
| Tour and draw | `atp-single`, `atp-double`, `wta-single` or `wta-double`. |
| Mode | `results` reads finished matches going backward from today. `upcoming` reads scheduled and live matches with pre-match odds, going forward from today. |
| Number of days | How many calendar days to read (default 3). |
| Maximum number of matches | The run stops once this many matches are saved. |

### Output

One record per match:

```json
{
  "tour": "ATP",
  "matchType": "singles",
  "date": "2026-09-28",
  "mode": "results",
  "id": "3334240",
  "url": "https://www.tennisexplorer.com/match-detail/?id=3334240",
  "tournament": "Chengdu",
  "tournamentUrl": "https://www.tennisexplorer.com/chengdu/2026/atp-men/",
  "time": "13:25",
  "status": "finished",
  "player1": "Hurkacz H.",
  "player1Url": "https://www.tennisexplorer.com/player/hurkacz/",
  "player1Seed": 5,
  "player2": "Shapovalov D.",
  "player2Url": "https://www.tennisexplorer.com/player/shapovalov/",
  "player2Seed": 7,
  "winner": 1,
  "setsPlayer1": [6, 6, 6, null, null],
  "setsPlayer2": [7, 3, 3, null, null],
  "resultPlayer1": 2,
  "resultPlayer2": 1,
  "oddsPlayer1": 1.61,
  "oddsPlayer2": 2.29
}
```

Export the dataset as JSON, CSV or Excel, or read it through the Apify API.

### Why this one

- **Cheaper than the installed leader.** $4.50 per 1,000 matches against $7.50 for the only other Tennis Explorer actor on the Store.
- **Results, upcoming matches and odds in one actor.** No need to run a separate tool for pre-match odds.
- **Singles and doubles, ATP and WTA.** One input field switches between all four draws instead of four separate actors.

### Good to know

- `time` is the kickoff time as Tennis Explorer displays it; the site does not publish a timezone, so treat it as local to the tournament unless you already know it.
- `oddsPlayer1` and `oddsPlayer2` are only published for matches the site has odds for (mostly main tour and upcoming matches); they are `null` otherwise.
- A retired or walkover match is flagged in `status`; its remaining sets are `null`.
- Only players' public match results and seedings are collected: no contact details of any kind.

# Actor input Schema

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

Which tour and draw to scrape.

## `mode` (type: `string`):

"Results" reads finished matches going backward from today. "Upcoming" reads scheduled and live matches with pre-match odds, going forward from today.

## `days` (type: `integer`):

How many calendar days to read (today plus this many days back for results, or forward for upcoming matches).

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

The run stops once this many matches are saved.

## Actor input object example

```json
{
  "type": "atp-single",
  "mode": "results",
  "days": 3,
  "maxItems": 50
}
```

# Actor output Schema

## `matches` (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("bibian/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 = {}

# Run the Actor and wait for it to finish
run = client.actor("bibian/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 '{}' |
apify call bibian/tennisexplorer-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,bibian/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/ROUNdXuUyj5CaI7Yd/builds/pb2cb7iGBKieY9kg6/openapi.json