# Tennis Scraper: Live Scores, Results, Odds & Stats (`scrapemint/tennis-scraper`) Actor

Tennis matches for any date: live scores, results with set and tiebreak scores, fixtures, closing odds with implied probability, head-to-head and serve stats. ATP, WTA, Challenger, ITF, singles and doubles. History back to 2005. $0.002 per match.

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

## Pricing

from $2.00 / 1,000 tennis 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: Live Scores, Results, Odds & Stats

Every tennis match for the dates you pick, as clean rows: **live scores**, **results** with set and tiebreak scores, **fixtures**, **average bookmaker odds** with implied probability, **head-to-head** counts, and optional **match stats** (aces, double faults, serve and return points won, break points, winners, unforced errors). ATP, WTA, Challenger and ITF, singles and doubles.

Results and closing odds go back to 2005, so you can backtest a model on years of matches in one run.

No API key, no login, no proxy. $0.002 per match, no start fee.

### What you get per match

- `tournament`, `category` ("ATP - SINGLES"), `tour` (`atp`, `wta`, `challenger-men`, `itf-women`...), `surface` (hard, clay, grass), `doubles`
- `status`: `scheduled`, `live`, `finished`, `retired`, `walkover`, `cancelled`, `postponed`, `interrupted`, `awarded`
- `player1` / `player2`: name, country, slug
- `winner` (1 or 2), `setsWon1`, `setsWon2`
- `sets`: games per set, with `tiebreak1`/`tiebreak2` when the set went to a tiebreak
- `score`: the usual string, e.g. `6-7(3) 6-1 6-2`
- `odds`: `player1`, `player2` (decimal), `impliedPct1`, `impliedPct2`, `favourite`, and `h2hMatches` for fixtures
- `stats` (with Match stats on): per match and per set, each stat for both players. Percentages come split into `pct`, `won` and `total`
- `startTime` (UTC), `matchUrl`, `tournamentUrl`

### Example input

Today's ATP and WTA matches, live and finished, with odds:

```json
{
  "dateFrom": "today"
}
```

Yesterday's results with full serve stats:

```json
{
  "dateFrom": "yesterday",
  "status": "finished",
  "includeStats": true
}
```

Every match a few players played at Roland Garros 2015, with closing odds:

```json
{
  "dateFrom": "2015-05-24",
  "dateTo": "2015-06-07",
  "players": ["Djokovic", "Wawrinka", "Nadal"]
}
```

Tomorrow's Challenger and ITF fixtures:

```json
{
  "dateFrom": "tomorrow",
  "tours": ["challenger-men", "challenger-women", "itf-men", "itf-women"],
  "status": "scheduled"
}
```

### Example output

```json
{
  "matchId": "8v653Rz9",
  "startTime": "2026-10-06T11:15:00.000Z",
  "tour": "atp",
  "category": "ATP - SINGLES",
  "tournament": "Beijing (China)",
  "surface": "hard",
  "status": "retired",
  "player1": { "name": "Djokovic N.", "country": "Serbia", "slug": "djokovic-novak" },
  "player2": { "name": "De Minaur A.", "country": "Australia", "slug": "de-minaur-alex" },
  "winner": 1,
  "setsWon1": 1,
  "setsWon2": 0,
  "sets": [
    { "player1": 7, "player2": 6, "tiebreak1": 7, "tiebreak2": 3 },
    { "player1": 0, "player2": 1 }
  ],
  "score": "7-6(3) 0-1",
  "odds": { "player1": 1.52, "player2": 2.5, "impliedPct1": 65.8, "impliedPct2": 40, "favourite": 1 },
  "stats": {
    "match": {
      "aces": { "player1": 0, "player2": 4 },
      "1stServePointsWon": { "player1": { "pct": 90, "won": 18, "total": 20 }, "player2": { "pct": 74, "won": 25, "total": 34 } }
    }
  },
  "matchUrl": "https://www.flashscore.com/match/8v653Rz9/#/match-summary"
}
```

### Uses

- **Betting models and backtests:** years of results with closing odds, and implied probability ready to compare against your own
- **Daily fixtures with prices:** schedule the run every morning for the day's matches, favourites and head-to-head
- **Live score feeds:** run every few minutes with status Live for in-play set scores
- **Player and serve analysis:** serve and return stats per match and per set for every player on tour

### Pricing

- **$0.002** per match, odds and head-to-head included
- **+$0.002** for the stats block, only on matches that have one, and only with Match stats on
- No start fee. A run that finds no matches is free.

### Notes

- Live scores, statuses and serve stats cover 7 days back to 7 days ahead. Older dates return results, scores and closing odds, without surface or stats.
- Odds are average bookmaker odds. For finished matches they are closing odds. Some small ITF matches have none, and their `odds` is `null`.
- `startTime` is UTC. Older matches carry `localDate` and `localTime` in Central European time instead.

# Actor input Schema

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

YYYY-MM-DD, or today, yesterday, tomorrow, or a day offset like -3 or +2. Live scores and serve stats cover 7 days back to 7 ahead; older dates (back to 2005) return results and closing odds.

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

Same formats. Empty means the same day as From. Up to 366 days per run.

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

Which levels to include.

## `includeDoubles` (type: `boolean`):

Off: singles only.

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

Live works for today only.

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

Only matches with these players, e.g. Sinner, Alcaraz, Swiatek. Surname is enough. Empty for all.

## `includeOdds` (type: `boolean`):

Average bookmaker odds for each player (closing odds for finished matches), implied probability, favourite, and head-to-head count for fixtures. No extra charge.

## `includeStats` (type: `boolean`):

Aces, double faults, 1st serve %, serve and return points won, break points, winners, unforced errors, per match and per set. Finished and live matches within the last 7 days. +$0.002 per match that has stats.

## `maxMatches` (type: `integer`):

Stop after this many match rows.

## Actor input object example

```json
{
  "dateFrom": "today",
  "dateTo": "",
  "tours": [
    "atp",
    "wta"
  ],
  "includeDoubles": false,
  "status": "all",
  "players": [],
  "includeOdds": true,
  "includeStats": false,
  "maxMatches": 1000
}
```

# Actor output Schema

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

Match rows: tournament, surface, players, status, winner, set scores with tiebreaks, odds and stats.

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

Match and stats counts, the date range, and anything that failed.

# 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 = {
    "dateFrom": "today",
    "tours": [
        "atp",
        "wta"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/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 = {
    "dateFrom": "today",
    "tours": [
        "atp",
        "wta",
    ],
}

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

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapemint/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/zztu7VXDNNhZXRJRg/builds/xyEaDeMfetQbpnwFp/openapi.json