# Tennis Scraper (`piotrv1001/tennis-scraper`) Actor

The Tennis Scraper extracts ATP, WTA, Challenger and ITF matches — results, live scores and fixtures — with players, tournaments, surfaces and set scores, plus optional match stats, point-by-point, durations, tiebreaks and head-to-head for betting and analytics.

- **URL**: https://apify.com/piotrv1001/tennis-scraper.md
- **Developed by:** [FalconScrape](https://apify.com/piotrv1001) (community)
- **Categories:** Sports, Automation, Developer tools
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 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 Scraper

Get tennis match data for every tour as clean, structured JSON. The **Tennis Scraper** returns ATP, WTA, Challenger and ITF matches — finished results, live scores and upcoming fixtures — with **players, tournaments, surfaces, set-by-set scores and winners**, and optionally **match statistics, point-by-point, set durations, tiebreak scores and head-to-head history**. Built for betting models, sports analytics, fantasy tools and live-score apps.

### ✨ Features

- 🌍 **Every level of the game**: ATP, WTA, Challenger, ITF, juniors and exhibitions, singles and doubles — typically 100–400 matches a day.
- 📅 **Results, live and upcoming**: Up to 7 days back for finished results and 7 days ahead for the schedule, with live scores (current game points and who is serving) for matches in play.
- 📊 **Match statistics**: Aces, double faults, first-serve %, points won on serve and return, break points saved and converted, games won — for the whole match and for every set.
- 🎯 **Point-by-point**: Every game with its server, winner, breaks of serve and the full point sequence, with break points, set points and match points flagged.
- ⏱️ **Durations and tiebreaks**: Match and set durations, tiebreak scores and the chair umpire.
- 🤝 **Head-to-head**: Previous meetings of the two players with date, tournament, surface, winner and score.
- 🔎 **Simple filters**: Tour, singles or doubles, match status and player names.
- 💸 **Fair billing**: Pay per match saved. Runs with no matching matches are free.

### 🛠️ How It Works

1. **Pick the days** – `daysBack` (results) and `daysAhead` (schedule), 0–7 each. `0` and `0` means today only.
2. **Filter** – Choose `tours` (empty = all), `matchType` (singles by default), `status` (finished, live, scheduled or all) and, optionally, `players` (part of a name is enough).
3. **Add details (optional)** – Turn on `includeMatchDetails` for statistics, point-by-point, durations, tiebreaks and head-to-head.
4. **Run it** – Matches stream into the dataset; export as JSON, CSV or Excel, or schedule runs for a live feed.

### 💰 Pricing

| Event           | Price  | What you get                                                                                                           |
| --------------- | ------ | ---------------------------------------------------------------------------------------------------------------------- |
| `match`         | $0.003 | One match: tournament, tour, surface, players, status, winner, set scores and live score                               |
| `match-details` | $0.006 | Charged instead of `match` when details are on: adds statistics, point-by-point, durations, tiebreaks and head-to-head |

Example: yesterday's ATP and WTA singles results (about 50 matches) cost **$0.15**, or **$0.30** with full match details. A run that finds no matching matches is not charged.

### ⚠️ Good to know

- The schedule covers 7 days back and 7 days ahead of today. Older results are not available.
- Statistics and point-by-point exist for matches that have been played; for scheduled matches, details contain the head-to-head only. Lower-level ITF matches often have no statistics.
- `player1` / `player2` follow the order the match is listed in; `winner` and every per-player value use the same sides.
- `country` is `World` for players competing under a neutral flag.
- Times are UTC.

### 📊 Sample Output Data

```json
{
    "matchId": "G2W1cGK6",
    "url": "https://www.flashscore.com/match/G2W1cGK6/#/match-summary",
    "startsAt": "2026-10-02T05:10:00.000Z",
    "status": "finished",
    "statusDetail": "finished",
    "tour": "atp",
    "category": "ATP - SINGLES",
    "matchType": "singles",
    "tournament": {
        "id": "3473162",
        "name": "Beijing (China)",
        "surface": "hard",
        "indoor": false,
        "url": "https://www.flashscore.com/tennis/atp-singles/beijing/"
    },
    "player1": {
        "id": "drgiRTl7",
        "name": "Molcan A.",
        "country": "Slovakia",
        "slug": "molcan-alex",
        "partner": null
    },
    "player2": {
        "id": "4bNPtZT5",
        "name": "Khachanov K.",
        "country": "World",
        "slug": "khachanov-karen",
        "partner": null
    },
    "winner": "player2",
    "setsWon": {
        "player1": 0,
        "player2": 2
    },
    "sets": [
        {
            "player1": 5,
            "player2": 7,
            "tiebreak": null,
            "durationMinutes": 41
        },
        {
            "player1": 3,
            "player2": 6,
            "tiebreak": null,
            "durationMinutes": 34
        }
    ],
    "live": null,
    "updatedAt": "2026-10-02T06:25:16.000Z",
    "scrapedAt": "2026-10-03T13:03:16.781Z",
    "durationMinutes": 75,
    "umpire": "Lahyani M.",
    "statistics": [
        {
            "period": "Match",
            "group": "Service",
            "name": "Aces",
            "player1": "1",
            "player2": "7"
        },
        {
            "period": "Match",
            "group": "Service",
            "name": "Double Faults",
            "player1": "1",
            "player2": "0"
        },
        {
            "period": "Match",
            "group": "Service",
            "name": "1st serve percentage",
            "player1": "59%",
            "player2": "77%"
        },
        {
            "period": "Match",
            "group": "Service",
            "name": "1st serve points won",
            "player1": "83% (25/30)",
            "player2": "85% (34/40)"
        }
    ],
    "pointByPoint": [
        {
            "set": 1,
            "gamesScore": {
                "player1": 0,
                "player2": 1
            },
            "server": "player2",
            "winner": "player2",
            "brokenServe": false,
            "points": [
                {
                    "score": "0:15",
                    "breakPoint": false,
                    "setPoint": false,
                    "matchPoint": false
                },
                {
                    "score": "0:30",
                    "breakPoint": false,
                    "setPoint": false,
                    "matchPoint": false
                },
                {
                    "score": "0:40",
                    "breakPoint": false,
                    "setPoint": false,
                    "matchPoint": false
                }
            ]
        }
    ],
    "headToHead": [
        {
            "matchId": "j5TAU6tU",
            "date": "2022-05-18",
            "tournament": "Lyon 2",
            "surface": "clay",
            "winner": "player1",
            "score": "0:2"
        }
    ]
}
```

Start building your tennis dataset with the **Tennis Scraper**! 🎾

# Actor input Schema

## `daysBack` (type: `integer`):

Include matches from this many past days (0 = today only, up to 7). Use it to collect finished results.

## `daysAhead` (type: `integer`):

Include scheduled matches for this many upcoming days (0 = today only, up to 7).

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

Which tours to include. Leave empty for all, including ITF, Challenger, juniors and exhibitions.

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

Which draws to include.

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

Only finished results, only live matches, only scheduled matches, or everything.

## `players` (type: `array`):

Only matches involving these players. Part of the name is enough (e.g. `Sinner`, `Swiatek`).

## `includeMatchDetails` (type: `boolean`):

Add match statistics (overall and per set), point-by-point, set durations and tiebreak scores, and head-to-head history for every match. Billed at the detailed-match price.

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

Maximum number of matches to return.

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

Proxy settings. The default works.

## Actor input object example

```json
{
  "daysBack": 1,
  "daysAhead": 0,
  "tours": [
    "atp",
    "wta"
  ],
  "matchType": "singles",
  "status": "all",
  "players": [],
  "includeMatchDetails": false,
  "maxItems": 50,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# 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 = {
    "daysBack": 1,
    "tours": [
        "atp",
        "wta"
    ],
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("piotrv1001/tennis-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 = {
    "daysBack": 1,
    "tours": [
        "atp",
        "wta",
    ],
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("piotrv1001/tennis-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 '{
  "daysBack": 1,
  "tours": [
    "atp",
    "wta"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call piotrv1001/tennis-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,piotrv1001/tennis-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/MFvc7aKSqBv0rImzo/builds/ARvydgzm5Shtledzz/openapi.json