GHIN Golf Tracker

Analyzes local GHIN golf JSON data to report handicap trends, scoring patterns, course stats, and yearly performance without external connections.

OpenClaw skill for analyzing GHIN (Golf Handicap and Information Network) golf statistics and handicap tracking.

Description

This skill provides comprehensive analysis of golf statistics from GHIN data including handicap trends, scoring patterns, course performance, and historical breakdowns. The skill reads pre-collected GHIN data from a JSON file and computes detailed statistics in both human-readable and machine-readable formats.

Key Features:

• Current handicap index with trend analysis (improving/declining/stable)
• Lifetime totals including round counts and scoring extremes
• Best 5 differentials with course and date information
• Most played courses with round counts and average scores
• Year-by-year performance breakdown
• Scoring averages by par (3/4/5) when available
• Performance statistics (GIR%, fairways%, putts) when available
• Handicap range analysis with dates

System Access

File System:

• READ: Single GHIN data JSON file (path provided as command-line argument)

Network Access: None

Subprocess/Shell: None

What It Does NOT Do

This skill is designed for data analysis only and explicitly does NOT:

• No network access: Does not connect to GHIN.com or any external services
• No web scraping: Does not perform browser automation or web requests
• No subprocess execution: Does not run external commands or shell scripts
• No file writes: Does not create, modify, or delete any files
• No credential handling: Does not store, read, or manage login credentials
• No data collection: Does not gather GHIN data from external sources

Data Collection: GHIN does not offer a public API for score history. Data collection requires separate browser automation tooling (not included in this skill). See the README for guidance on how to populate the data file.

Resources

Scripts

• scripts/ghin_stats.py - Main analysis script (Python 3.8+ required)

Usage

Basic Analysis

python3 scripts/ghin_stats.py /path/to/ghin-data.json

JSON Output

python3 scripts/ghin_stats.py /path/to/ghin-data.json --format json

Expected Data Format

The script expects a JSON file with the following structure:

{
  "handicap_index": 18.0,
  "lifetime_rounds": 83,
  "handicap_history": [
    {"date": "2026-02-02", "index": 18.0},
    {"date": "2026-01-15", "index": 17.8}
  ],
  "stats": {
    "par3_avg": 4.06,
    "par4_avg": 4.94,
    "par5_avg": 5.73,
    "gir_pct": 50,
    "fairways_pct": 65,
    "putts_avg": 31.2
  },
  "scores": [
    {
      "date": "2026-02-01",
      "score": "82A",
      "course": "Las Vegas Golf Club",
      "cr_slope": "68.0/117",
      "differential": 13.5
    }
  ]
}

Example Output (Text Format)

GHIN Golf Statistics Report
==============================

Current Handicap: 18.0
Trend (last 5): ↗️  Improving

LIFETIME TOTALS
---------------
Total Rounds: 83
Best Score: 72
Worst Score: 95

BEST DIFFERENTIALS
-----------------
1. 8.2 - Pebble Beach Golf Links (2025-08-15)
2. 9.1 - Augusta National Golf Club (2025-09-22)
3. 10.4 - St. Andrews Old Course (2025-07-10)

MOST PLAYED COURSES
-------------------
Las Vegas Golf Club: 12 rounds (avg 84.2)
Phoenix Country Club: 8 rounds (avg 86.1)
Scottsdale National: 6 rounds (avg 82.9)

YEARLY BREAKDOWN
----------------
2026: 8 rounds (avg 83.4)
2025: 42 rounds (avg 84.7)
2024: 33 rounds (avg 87.2)

Dependencies

• Python 3.8+
• Standard library only (json, sys, argparse, statistics, datetime, pathlib, collections, re)

Installation

This skill can be installed via ClawHub:

clawhub install ghin-golf-tracker

Or manually by cloning the repository and placing it in your OpenClaw skills directory.

Error Handling

The script provides specific error handling for:

• FileNotFoundError: When the specified JSON file doesn't exist
• json.JSONDecodeError: When the JSON file is malformed
• Graceful handling of missing or malformed data fields

Output Formats

• Text (default): Human-readable formatted report
• JSON: Machine-readable structured data for further processing

Privacy & Security

• All processing is done locally on the provided data file
• No external network connections are made
• No credentials or sensitive data are stored or transmitted
• Data is processed in memory only with no persistent storage