# Tennis Abstract Player Match Scraper (`fetch_cat/tennis-abstract-scraper`) Actor

Export public recent match results and match statistics for a Tennis Abstract player.

- **URL**: https://apify.com/fetch\_cat/tennis-abstract-scraper.md
- **Developed by:** [Hanna Nosova](https://apify.com/fetch_cat) (community)
- **Categories:** Sports
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.59 / 1,000 match 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?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Tennis Abstract Player Match Scraper

Export recent public Tennis Abstract match results for one player into structured JSON, CSV, Excel, or an API workflow. Get a clean match-level dataset with opponents, scores, tournament context, rankings, and the statistics displayed for each public result.

### What you get

Every exported row is one recent player match. Use it to:

- Track a player’s latest opponents, scores, and results.
- Build a surface-aware tennis player match history dataset.
- Compare tournament, round, ranking, and tennis match statistics trends.
- Feed match history into spreadsheets, dashboards, or analytical agents.

### Input recipes

Start with a small request:

```json
{
  "playerSlug": "NovakDjokovic",
  "maxItems": 20
}
```

Use the player identifier from the public Tennis Abstract player URL. For example, the slug in a player URL ending in `?p=IgaSwiatek` is `IgaSwiatek`.

### Output example

```json
{
  "playerSlug": "NovakDjokovic",
  "playerName": "Novak Djokovic",
  "date": "2025-01-24",
  "tournament": "Australian Open",
  "surface": "Hard",
  "round": "SF",
  "opponent": "Alexander Zverev",
  "result": "W",
  "score": "7-6(5) 6-3",
  "sourceUrl": "http://www.tennisabstract.com/cgi-bin/player-classic.cgi?p=NovakDjokovic"
}
```

Statistics and rankings are included when displayed by the source for that match; unavailable source values are `null` rather than guessed.

### Input settings

| Input | Description |
|---|---|
| `playerSlug` | Required Tennis Abstract player identifier from the public player URL. |
| `maxItems` | Maximum recent match rows to export, from 1 to 200. Start with 20. |

### Output fields

| Field | Description |
|---|---|
| `playerSlug` / `playerName` | Requested player identifier and public display name. |
| `date` | Match date as displayed by the source. |
| `tournament` / `tournamentUrl` | Tournament name and public tournament link when available. |
| `surface` / `round` | Surface and tournament round. |
| `playerRank` / `opponentRank` | Public ranking values when shown. |
| `opponent` / `opponentSlug` / `opponentCountry` | Opponent identity and source-provided metadata. |
| `result` / `score` | Displayed result marker and match score. |
| `dominanceRatio` | Source-provided dominance ratio when available. |
| `aceRate` / `doubleFaultRate` | Displayed serve rates when available. |
| `firstServeIn` / `firstServeWon` / `secondServeWon` | Displayed first- and second-serve percentages. |
| `breakPointsSaved` | Displayed break-point statistic. |
| `matchDuration` | Displayed match duration when available. |
| `sourceUrl` | Public player page used for the exported row. |

### Who is it for?

This Actor is useful for tennis analysts, sports researchers, journalists, fantasy and scouting workflows, and developers building player-history datasets. It is designed for public recent-match data for a specific player, not live scoring or private account data.

### Tips

- Copy the exact player slug from the public player URL to avoid targeting a similarly named player.
- Begin with a small `maxItems` value when testing a new workflow.
- Use `sourceUrl` to retain a direct public reference alongside every exported row.
- Export to CSV or Excel for spreadsheets, or consume the default dataset from your application.

### Pricing and limits

[View current pricing on the Actor’s Pricing tab](https://apify.com/fetch_cat/tennis-abstract-scraper/pricing). A small run-start fee applies, followed by a charge for each exported match result. The tier shown on the Pricing tab is authoritative.

The Actor exports rows currently available on the public player page. It does not invent missing statistics, historical rows that are no longer present, or live match updates.

### API usage

#### Node.js

```javascript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/tennis-abstract-scraper').call({
  playerSlug: 'NovakDjokovic',
  maxItems: 20,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

#### Python

```python
from apify_client import ApifyClient

client = ApifyClient("<APIFY_TOKEN>")
run = client.actor("fetch_cat/tennis-abstract-scraper").call(
    run_input={"playerSlug": "NovakDjokovic", "maxItems": 20}
)
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)
```

#### cURL

```bash
curl -X POST \
  'https://api.apify.com/v2/acts/fetch_cat~tennis-abstract-scraper/runs?token=<APIFY_TOKEN>' \
  -H 'content-type: application/json' \
  -d '{"playerSlug":"NovakDjokovic","maxItems":20}'
```

### MCP and AI agents

Use this Actor from Apify MCP by enabling `https://mcp.apify.com?tools=fetch_cat/tennis-abstract-scraper`.

For Claude Code, add the MCP server:

```bash
claude mcp add apify -- npx -y @apify/mcp-server --tools=fetch_cat/tennis-abstract-scraper
```

Or add this server configuration:

```json
{
  "mcpServers": {
    "apify": {
      "command": "npx",
      "args": ["-y", "@apify/mcp-server", "--tools=fetch_cat/tennis-abstract-scraper"],
      "env": { "APIFY_TOKEN": "<APIFY_TOKEN>" }
    }
  }
}
```

Example prompts: “Export the latest 20 matches for NovakDjokovic” or “Return IgaSwiatek’s recent hard-court matches as a table.”

### Related Actors

Extend player research with these FetchCat Actors:

- [Google Search Results Scraper](https://apify.com/fetch_cat/google-search-results-scraper) for tournament and news discovery.
- [YouTube Channel Videos Scraper](https://apify.com/fetch_cat/youtube-channel-videos-scraper) for public player-channel video catalogs.
- [YouTube Comments Scraper](https://apify.com/fetch_cat/youtube-comments-scraper) for public audience discussion research.
- [Instagram Profile & Posts Scraper](https://apify.com/fetch_cat/instagram-profile-posts-scraper) for public player social-content exports.
- [Website Content Crawler](https://apify.com/fetch_cat/website-content-crawler-lite) for tournament or federation web pages.

This Actor focuses specifically on recent player match rows from Tennis Abstract.

### FAQ

#### Do I need a Tennis Abstract account?

No. The Actor uses public player information and does not require login credentials.

#### Why can a statistic be null?

A null value means that statistic was not displayed for that public match row. The Actor preserves the source’s availability rather than estimating data.

#### Can I request more than 200 matches?

The current maximum is 200 rows per run. Split research into player-specific runs to keep exports focused and manageable.

#### Is this live match data?

No. It exports recent match rows available on the public player page at run time.

### Support

Open an issue on the [Actor page](https://apify.com/fetch_cat/tennis-abstract-scraper/issues) with the player slug and a non-sensitive example. Include the expected public player page so support can reproduce the request.

# Actor input Schema

## `playerSlug` (type: `string`):

The player identifier in a Tennis Abstract player URL, for example NovakDjokovic or IgaSwiatek.

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

Maximum recent match rows to export. Keep the prefill low for a quick first run.

## Actor input object example

```json
{
  "playerSlug": "NovakDjokovic",
  "maxItems": 20
}
```

# Actor output Schema

## `overview` (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 = {
    "playerSlug": "NovakDjokovic",
    "maxItems": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("fetch_cat/tennis-abstract-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 = {
    "playerSlug": "NovakDjokovic",
    "maxItems": 20,
}

# Run the Actor and wait for it to finish
run = client.actor("fetch_cat/tennis-abstract-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 '{
  "playerSlug": "NovakDjokovic",
  "maxItems": 20
}' |
apify call fetch_cat/tennis-abstract-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,fetch_cat/tennis-abstract-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/IWAPn9W7rCzGcHf6A/builds/HHAqZoWNomRqNgyk4/openapi.json