# Tennis Results & Odds Scraper - ATP, WTA, Challenger, ITF (`dariandanciu/tennis-results-scraper`) Actor

Get tennis match results and upcoming matches from TennisExplorer for ATP, WTA, Challenger, ITF and UTR events: players, seeds, set-by-set scores with tiebreaks, winner, match odds and tournament. Singles and doubles, any date range.

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

## Pricing

from $0.80 / 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.
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, Challenger, ITF

Get **tennis results and upcoming matches** for **ATP, WTA, Challenger, ITF and UTR** events: players and seeds, **set-by-set scores with tiebreaks**, winner, **match odds**, tournament, level and country. Singles and doubles, any date range.

### Why this one

- **Every level.** Tour, Challenger, ITF and UTR matches, with a `tournamentLevel` field to filter on.
- **Scores ready to use.** `"7-6(3) 3-6 7-6(9)"` plus `setScores` and sets won per player.
- **Match odds** for both players as TennisExplorer shows them.
- **Upcoming matches too**, with pre-match odds.
- **You only pay for matches.** Failed days are listed in `RUN_SUMMARY` and cost nothing.

### Input

| Field | Example |
|---|---|
| Tours | `atp-single`, `wta-single` |
| Matches | Results or upcoming |
| Date from / to | `2026-11-01` / `2026-11-02` |
| Levels | Tour, Challenger, ITF, UTR |

Every field is optional except **Tours**.

### Output

One row per matche. Example:

```json
{
    "source": "tennisexplorer",
    "id": "te:3365455",
    "tour": "ATP singles",
    "date": "2026-11-01",
    "time": "14:10",
    "tournament": "Vienna",
    "tournamentLevel": "Tour",
    "tournamentCountry": "AT",
    "player1": "Alcaraz C.",
    "player1Seed": "2",
    "player2": "De Minaur A.",
    "player2Seed": "5",
    "winner": "Alcaraz C.",
    "sets1": 2,
    "sets2": 0,
    "score": "6-1 6-4",
    "setScores": [
        "6-1",
        "6-4"
    ],
    "status": "finished",
    "odds1": 1.2,
    "odds2": 4.47,
    "player1Url": "https://www.tennisexplorer.com/player/alcaraz-5ab70/",
    "player2Url": "https://www.tennisexplorer.com/player/de-minaur/",
    "tournamentUrl": "https://www.tennisexplorer.com/vienna/2026/atp-men/",
    "url": "https://www.tennisexplorer.com/match-detail/?id=3365455",
    "searchQuery": "atp-single"
}
```

Each row also has `searchQuery`: the search that found it. A summary of the run (matches per search, the site's total
for each search, and any searches that failed) is saved as `RUN_SUMMARY` in the key-value store.

Export to JSON, CSV, Excel or HTML from the Output tab, or use the API.

### Use cases

- **Tennis analytics and models:** results with odds across every level.
- **Sports apps:** daily results and schedules.
- **Player tracking** from Challenger to Grand Slam.

### Pricing

Pay per matche. See the Pricing tab. Searches that fail are free.

### Good to know

- Times are TennisExplorer's (Central European Time).
- Doubles team names are shortened by TennisExplorer ("Miedler L / Oberleitn").
- Odds appear only for matches TennisExplorer has odds for.
- This Actor reads public match results only (player names as published in results). It does not collect other personal data.

### Feedback

Missing a field or a filter? Open an issue on the Issues tab.

### Related Actors

More sports and markets scrapers by the same developer, with the same pay-per-result pricing:

| Actor | What it gets |
|---|---|
| [ESPN Scores & Standings Scraper](https://apify.com/dariandanciu/espn-scores-standings-scraper) | Scores, schedules and standings for 15 leagues |
| [Prediction Markets Scraper](https://apify.com/dariandanciu/prediction-markets-scraper) | Polymarket and Kalshi odds, volume and liquidity |

# Actor input Schema

## `searches` (type: `array`):

Tour types, one per line: atp-single, wta-single, atp-double, wta-double. ATP and WTA include Challenger, ITF and UTR events.

## `maxResultsPerSearch` (type: `integer`):

Stop each tour after this many matches.

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

Finished results or upcoming matches.

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

First day (YYYY-MM-DD). Empty = yesterday for results, today for upcoming.

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

Last day (YYYY-MM-DD). Empty = today for results, tomorrow for upcoming.

## `levels` (type: `array`):

Only these event levels. Empty = all.

## `proxyConfiguration` (type: `object`):

Apify Proxy is recommended. If the site starts blocking, requests switch to residential proxies automatically.

## Actor input object example

```json
{
  "searches": [
    "atp-single",
    "wta-single"
  ],
  "maxResultsPerSearch": 2000,
  "mode": "results",
  "levels": [],
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

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

One row per matche.

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

Matches per search, and any searches that failed (not charged).

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

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

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

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,dariandanciu/tennis-results-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/sz8MicPHb0ccqXCx2/builds/gNDubfsFj6wsn9DAl/openapi.json