ROBLOX Stats Tracker

A Node.js application that automatically tracks and logs various statistics for ROBLOX games and groups over time. It collects data such as:

• Game visits
• Favorite count
• Current active players
• Group member count
• Up/down votes

Features

• Automatic data collection at configurable intervals
• CSV file output organized by date
• Detailed logging system
• Error handling and recovery
• Clean shutdown and log rotation
• Rate limiting to respect ROBLOX's API limits
• Automatic retry on server errors

Getting Started and Installation

1. Clone this repository: git clone https://github.com/yourusername/roblox-stats-tracker.git cd roblox-stats-tracker

2. Install dependencies: npm install

3. Configure your settings in config.js:

   • Set your ROBLOX universe ID (currently set to 1931573465)
   • Set your group ID (currently set to 2880815)
   • Adjust the save interval if needed (default is 5 minutes)

Finding your ROBLOX universe ID and group ID

1. Find your ROBLOX universe ID:

   • Go to your game's configuration page
   • The universe ID is in the URL: https://create.roblox.com/dashboard/creations/experiences/[universeId]/...

2. Find your group ID:

   • Go to your group's page
   • The group ID is in the URL: https://www.roblox.com/groups/[groupId]/...

3. Update these values in config.js

Usage

Start the tracker: npm start

Using Screen (recommended for servers):

1. Install screen if not already installed:

   • Ubuntu/Debian: sudo apt-get install screen
   • CentOS/RHEL: sudo yum install screen

2. Start the tracker in a screen session: ./start.sh

3. Detach from the screen session: Press Ctrl+A then D

4. Reattach to the session later: screen -r tracker

5. List all screen sessions: screen -ls

Data Format

The tracker creates daily CSV files in the saves directory with the following format:

Column	Description
Timestamp	ISO 8601 timestamp
Visits	Total game visits
Favorites	Total favorites
Players	Current active players
Members	Group member count
UpVotes	Total up votes
DownVotes	Total down votes

Example: 2024-03-20T12:00:00.000Z,1000000,50000,150,5000,75000,2500

Viewing the Data

While you can open the CSV files in any spreadsheet application, I recommend using CSViewer for analyzing the data. CSViewer is:

• Fast and lightweight
• Free for commercial use
• Great for large CSV files
• Includes filtering and basic visualization features

The data format is also compatible with other tools like Excel, Google Sheets, or any CSV viewer of your choice.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.