# Export Match Player xG and Roster Data

**Use case:** 

Export one match roster with player positions, minutes, goals, cards, xG, xA, xGChain, and xGBuildup for lineup and individual performance analysis.

## Input

```json
{
  "mode": "match",
  "league": "EPL",
  "season": 2024,
  "target": "26602",
  "maxItems": 100,
  "includePlayers": true,
  "includeMatches": true,
  "includeShots": false,
  "includeBreakdowns": true,
  "includeRosters": true
}
```

## Output

```json
{
  "matchId": {
    "label": "Match ID",
    "format": "string"
  },
  "side": {
    "label": "Side",
    "format": "string"
  },
  "teamId": {
    "label": "Team ID",
    "format": "string"
  },
  "playerId": {
    "label": "Player ID",
    "format": "string"
  },
  "playerName": {
    "label": "Player",
    "format": "string"
  },
  "position": {
    "label": "Position",
    "format": "string"
  },
  "minutes": {
    "label": "Minutes",
    "format": "integer"
  },
  "goals": {
    "label": "Goals",
    "format": "integer"
  },
  "ownGoals": {
    "label": "Own goals",
    "format": "integer"
  },
  "shots": {
    "label": "Shots",
    "format": "integer"
  },
  "xG": {
    "label": "Expected goals",
    "format": "number"
  },
  "keyPasses": {
    "label": "Key passes",
    "format": "integer"
  },
  "assists": {
    "label": "Assists",
    "format": "integer"
  },
  "xA": {
    "label": "Expected assists",
    "format": "number"
  },
  "yellowCards": {
    "label": "Yellow cards",
    "format": "integer"
  },
  "redCards": {
    "label": "Red cards",
    "format": "integer"
  },
  "subbedIn": {
    "label": "Subbed in",
    "format": "integer"
  },
  "subbedOut": {
    "label": "Subbed out",
    "format": "integer"
  },
  "xGChain": {
    "label": "xG chain",
    "format": "number"
  },
  "xGBuildup": {
    "label": "xG buildup",
    "format": "number"
  },
  "sourceUrl": {
    "label": "Source URL",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Understat xG Scraper – Football Data & Analytics](https://apify.com/datascraperes/understat-football-data.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/datascraperes/understat-football-data.md) to learn more, explore other use cases, and run it yourself.


## 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.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/datascraperes/understat-football-data.md

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).