GoalGorithm MCP Server

GoalGorithm MCP Server

Provides soccer match predictions and league statistics using xG data and Poisson distribution models. It enables users to forecast outcomes, analyze team performance, and view league tables across major European football leagues.

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GoalGorithm MCP Server

Soccer match predictions using xG data and Poisson distribution, exposed as MCP tools for Claude Desktop/Code.

Proven in production — This prediction model is actively used on BongdaNET, a football analytics platform that combines expert analysis with data science to deliver accurate match predictions. BongdaNET also serves as a comprehensive football data hub — offering odds from top bookmakers, live results, fixtures, and standings for leagues worldwide — providing a smart betting experience for punters and football enthusiasts alike.

Install

pip install goalgorithm-mcp

Or run directly:

uvx goalgorithm-mcp

Claude Desktop Config

Add to your Claude Desktop config (claude_desktop_config.json):

{
  "mcpServers": {
    "goalgorithm": {
      "command": "goalgorithm-mcp"
    }
  }
}

Example Usage

Once configured, just ask Claude naturally:

You: "Predict Arsenal vs Chelsea this weekend"

Claude will call the predict_match tool and respond with something like:

Claude: Here's the prediction for Arsenal vs Chelsea (Premier League):

Outcome Probability
Arsenal Win 52.4%
Draw 22.7%
Chelsea Win 24.9%
  • Expected Goals: Arsenal 1.85 — Chelsea 1.23
  • Over 2.5 Goals: 58.3% | Under 2.5: 41.7%
  • Both Teams to Score: Yes 52.1% | No 47.9%
  • Most Likely Scores: 1-0 (12.8%), 1-1 (11.2%), 2-1 (10.5%)

Arsenal are clear favorites at home with stronger attacking xG.

Other things you can ask:

  • "Show me the La Liga xG table" — calls get_league_table
  • "Which leagues are available?" — calls list_leagues
  • "Who's more likely to win, Bayern or Dortmund?" — calls predict_match

Tools

predict_match

Predict soccer match outcome using xG-based Poisson model.

predict_match(home_team="Arsenal", away_team="Chelsea", league="EPL")

Returns: win/draw/loss %, over/under 2.5, BTTS, top 3 scores, expected goals, score matrix.

list_leagues

List all supported soccer leagues with IDs and slugs.

get_league_table

Get all teams in a league with their xG statistics, sorted by attacking strength.

get_league_table(league="EPL")

Supported Leagues

ID League Slug
9 Premier League EPL
12 La Liga LaLiga
11 Serie A SerieA
20 Bundesliga Bundesliga
13 Ligue 1 Ligue1

How It Works

  1. Fetches team xG/xGA stats from Understat.com
  2. Computes attack/defense strength relative to league average
  3. Applies Poisson distribution to calculate goal probabilities
  4. Builds 6x6 score matrix for all possible scorelines (0-5 goals each)
  5. Derives match outcomes: W/D/L, Over/Under 2.5, BTTS

Data Source

All data from Understat.com public JSON API. Results cached locally for 12 hours.

License

GPL v2 or later

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