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.
README
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
- Fetches team xG/xGA stats from Understat.com
- Computes attack/defense strength relative to league average
- Applies Poisson distribution to calculate goal probabilities
- Builds 6x6 score matrix for all possible scorelines (0-5 goals each)
- 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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