# Tennis Results & Odds Scraper - ATP, WTA, ITF (TennisExplorer) (`riscrape/tennis-results-odds-scraper`) Actor

Daily tennis match results and upcoming matches from TennisExplorer: tournament, players, seeds, set-by-set scores with tiebreaks, winner and closing odds. ATP, WTA, Challenger and ITF, singles and doubles.

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

## Pricing

from $1.90 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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 Results & Odds Scraper - ATP, WTA, ITF (TennisExplorer)

Daily **tennis match results** and **upcoming matches** from TennisExplorer.

For every match: **date, start time, tournament, country, category, both players with seeds and profile links, set-by-set score with tiebreaks, sets won, winner, odds for each player** and the match link.

Covers **ATP, WTA, Challenger and ITF**, singles and doubles.

### Input

| Field | What to put |
|---|---|
| `dateFrom` / `dateTo` | Range of days for results (empty = yesterday) |
| `categories` | `atp-single`, `wta-single`, `atp-double`, `wta-double`, `challenger-single`, `itf-men-single`, `itf-women-single` or `all` |
| `upcomingDays` | Also list scheduled matches with odds for the next N days |
| `maxItems` | Stop after this many matches |

### Output

```json
{
  "type": "result",
  "date": "2026-10-06",
  "tournament": "Beijing",
  "countryCode": "CN",
  "player1": "Djokovic N.", "player1Seed": "6",
  "player2": "De Minaur A.", "player2Seed": "5",
  "score": "7-6(3) 0-1",
  "sets": [{"p1": 7, "p2": 6, "tiebreak": 3}, {"p1": 0, "p2": 1, "tiebreak": null}],
  "winner": "Djokovic N.",
  "oddsPlayer1": 1.52, "oddsPlayer2": 2.5,
  "matchUrl": "https://www.tennisexplorer.com/match-detail/?id=3342083"
}
```

### Use cases

- Build tennis datasets for betting models and backtests (results + odds)
- Track daily results for a tour or a tournament
- Get tomorrow's schedule with odds

### Pricing

Pay per result: $2.50 per 1,000 matches.

# Actor input Schema

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

First day of results (YYYY-MM-DD). Empty = yesterday.

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

Last day of results (YYYY-MM-DD). Empty = same as 'from'.

## `categories` (type: `array`):

atp-single, wta-single, atp-double, wta-double, challenger-single, itf-men-single, itf-women-single, or all

## `upcomingDays` (type: `integer`):

Also return scheduled matches with odds for today and the next N-1 days (0 = skip).

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

Stop after this many matches (0 = no limit).

## Actor input object example

```json
{
  "categories": [
    "atp-single",
    "wta-single"
  ],
  "upcomingDays": 0,
  "maxItems": 0
}
```

# 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 = {
    "categories": [
        "atp-single",
        "wta-single"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("riscrape/tennis-results-odds-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 = { "categories": [
        "atp-single",
        "wta-single",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("riscrape/tennis-results-odds-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 '{
  "categories": [
    "atp-single",
    "wta-single"
  ]
}' |
apify call riscrape/tennis-results-odds-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,riscrape/tennis-results-odds-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/25tQCsKkTM86CPDR8/builds/ffB07y78JRcmjCXYo/openapi.json