# Live Tennis Match Scores, Rankings, H2H & Odds Scraper (`keenedigitalstudio/tennis-stats-odds-scraper`) Actor

Extract live and completed ATP & WTA tennis matches, set-by-set scores, tiebreaks, tournament draws, official world rankings, and fair decimal odds via public sports JSON APIs. $2.00/1,000 results ($0.002/item) with $0 start fee. Built by Keene Digital Studio.

- **URL**: https://apify.com/keenedigitalstudio/tennis-stats-odds-scraper.md
- **Developed by:** [Keene Digital Studio](https://apify.com/keenedigitalstudio) (community)
- **Categories:** Other, AI, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## 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

## Live Tennis Match Scores, Rankings, H2H & Odds Scraper

Extract **live, completed, and scheduled ATP & WTA tennis matches, set-by-set scores, tiebreaks, tournament draws, official world rankings, and implied fair decimal odds** via public sports JSON APIs with zero proxy costs.

Built by **Keene Digital Studio**.

***

### Why Choose This Scraper Over Legacy Incumbents?

| Feature | **Keene Digital Studio (`tennis-stats-odds-scraper`)** | `crawlstone/tennis-scraper` |
|---|---|---|
| **Pricing** | **$2.00 / 1,000 results** (`$0.002` / item) | $8.00 / 1,000 results |
| **Start Fee** | **$0.00** | Included in high per-1k rate |
| **Reliability** | **100% pass rate** via direct ESPN ATP/WTA public JSON APIs | 10.4% failure rate on Apify Store |
| **Rankings & Odds Enrichment** | Automatically enriches matches with live ATP/WTA world ranks, points, and Bradley-Terry fair decimal odds | Raw scores only |

***

### Key Capabilities

1. **ATP & WTA Tournament Scoreboards (`MATCH` records):**
   - Extracts live (`In Progress`), completed (`Final`), and upcoming (`Scheduled`) matches across ATP Tour, WTA Tour, and Grand Slam tournaments.
   - Includes set-by-set scores with tiebreak points (e.g., `6-4, 3-6, 7-6(4)`), round names (`Round of 32`, `Quarterfinal`, `Final`), court names, and official match notes.
2. **Official World Rankings Enrichment (`RANKING` records):**
   - Pulls official ATP and WTA Top 150+ world rankings, points, previous rank, and ranking movement trends.
   - Automatically cross-references active tournament players with their current world rank and official points.
3. **Implied Win Probabilities & Fair Decimal Odds:**
   - Computes pre-match fair win probabilities (`player1WinProb`, `player2WinProb`) and fair decimal odds (`player1FairOdds`, `player2FairOdds`) from official tour points and rankings.

***

### Input Example

```json
{
  "tour": "BOTH",
  "mode": "ALL",
  "matchStatus": "ALL",
  "dates": [],
  "searchFilter": "",
  "maxItems": 50
}
```

### Output Example

```json
{
  "recordType": "MATCH",
  "tour": "ATP",
  "tournamentId": "10-2026",
  "tournamentName": "Erste Bank Open",
  "isMajor": false,
  "drawName": "Men's Singles",
  "roundName": "Qualifying - 1st Round",
  "matchId": "187149",
  "matchDate": "2026-10-24T09:00Z",
  "matchStatus": "Final",
  "completed": true,
  "venueLocation": "Vienna, Austria",
  "courtName": "Glaubandich Court",
  "player1Name": "Pablo Carreno Busta",
  "player1Country": "Spain",
  "player1Rank": 92,
  "player1Points": 645.0,
  "player1Winner": false,
  "player2Name": "Jacob Fearnley",
  "player2Country": "Great Britain",
  "player2Rank": 88,
  "player2Points": 668.0,
  "player2Winner": true,
  "scoreSummary": "4-6, 6-3, 3-6",
  "setsPlayed": 3,
  "matchNote": "Jacob Fearnley (GBR) bt Pablo Carreno Busta (ESP) 6-4 3-6 6-3",
  "player1WinProb": 0.4943,
  "player2WinProb": 0.5057,
  "player1FairOdds": 2.02,
  "player2FairOdds": 1.98,
  "rankChange": null,
  "playerUrl": "https://www.espn.com/tennis/player/_/id/1590/pablo-carreno-busta",
  "sourceApi": "espn-tennis-atp-scoreboard",
  "elapsedMs": 412,
  "scrapedAt": "2026-10-27T00:05:00+00:00"
}
```

# Actor input Schema

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

Select ATP (Men's), WTA (Women's), or BOTH tours.

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

Extract live/completed tournament matches (MATCHES), official world rankings (RANKINGS), or both (ALL).

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

Filter matches by completion state (ALL, COMPLETED, LIVE, SCHEDULED).

## `dates` (type: `array`):

Optional list of scoreboard dates in YYYYMMDD format (e.g., \['20261026']) or leave empty for current active tournaments.

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

Optional case-insensitive filter for player name (e.g., 'Sinner', 'Alcaraz', 'Sabalenka') or tournament name (e.g., 'Vienna', 'Basel', 'Tokyo'). Leave empty for all.

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

Maximum number of match and ranking records to emit (1 to 500).

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

Optional proxy settings. Not required — public JSON APIs operate at 100% reliability without proxies.

## Actor input object example

```json
{
  "tour": "BOTH",
  "mode": "ALL",
  "matchStatus": "ALL",
  "dates": [],
  "searchFilter": "",
  "maxItems": 50
}
```

# Actor output Schema

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

Full dataset of extracted ATP/WTA tennis matches, scores, rankings, and fair odds.

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

Tabular overview of tournaments, players, set scores, rankings, and implied odds.

# 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 = {
    "tour": "BOTH",
    "mode": "ALL",
    "matchStatus": "ALL",
    "dates": [],
    "searchFilter": "",
    "maxItems": 50
};

// Run the Actor and wait for it to finish
const run = await client.actor("keenedigitalstudio/tennis-stats-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 = {
    "tour": "BOTH",
    "mode": "ALL",
    "matchStatus": "ALL",
    "dates": [],
    "searchFilter": "",
    "maxItems": 50,
}

# Run the Actor and wait for it to finish
run = client.actor("keenedigitalstudio/tennis-stats-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 '{
  "tour": "BOTH",
  "mode": "ALL",
  "matchStatus": "ALL",
  "dates": [],
  "searchFilter": "",
  "maxItems": 50
}' |
apify call keenedigitalstudio/tennis-stats-odds-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,keenedigitalstudio/tennis-stats-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/yff6KTKGolqgGWaqX/builds/eA0VAnubXhdDMO08j/openapi.json