🎯 CSFloat Trades

Advanced CS2 Trading Bot & Market Analysis Dashboard

A sophisticated Python application that automatically identifies profitable arbitrage opportunities on the CSFloat marketplace through real-time market scanning and multi-strategy analysis.

🚀 Features

📊 Real-Time Market Scanning

• Continuous monitoring of CSFloat marketplace API
• Automated detection of underpriced items and trading opportunities
• Rate-limited API interactions with error handling
• Processes hundreds of listings per scan cycle

🧠 Multi-Strategy Trading Analysis

• Price Anomaly Detection - Items listed below market value
• Sticker Value Arbitrage - Conservative & aggressive sticker trading
• Float Tier Upgrades - Low float items with upgrade potential
• High Overpay Potential - Items likely to receive premium offers
• Charm/Keychain Trading - Specialized charm arbitrage opportunities
• Dynamic Profit Targeting - Adaptive profit thresholds by price tier

🖥️ Interactive Web Dashboard

• Clean, dark-themed responsive interface
• Real-time deal updates without page refresh
• Strategy-based organization and sorting
• Detailed profit metrics and item analysis
• Mobile-optimized for on-the-go trading

🛠️ Tech Stack

📁 Project Structure

Csfloat-Trades/
├── app.py              # Flask web application & main entry point
├── scanner.py          # Market scanning & analysis engine
├── config.json         # Configuration parameters
├── templates/
│   └── index.html     # Web dashboard interface
└── .gitignore         # Version control exclusions

⚙️ Installation & Setup

Prerequisites

• Python 3.7+
• CSFloat API access
• Basic knowledge of CS2 trading

Installation Steps

1. Clone the repository

   git clone https://github.com/ernsahin/Csfloat-Trades.git
   cd Csfloat-Trades

2. Install dependencies

   pip install flask requests sqlite3

3. Configure settings

   • Edit config.json with your API credentials
   • Adjust profit thresholds and scanning parameters
   • Set price range filters and weapon type preferences

4. Run the application

   python app.py

5. Access dashboard

   • Open browser to http://127.0.0.1:5000
   • Monitor deals in real-time
   • Analyze profitable opportunities

🔧 Configuration Options

Scanning Parameters

• API scan intervals and page limits
• Rate limiting and timeout settings
• Error handling and retry logic

Trading Strategies

• Individual profit thresholds per strategy
• Float value analysis parameters
• Sticker valuation settings

Risk Management

• Maximum investment amounts
• Minimum profit requirements (USD & percentage)
• Price range filtering by weapon category

📈 Key Metrics Tracked

• Profit Potential: Expected USD profit per deal
• Percentage Gain: ROI calculations
• Float Values: Wear condition analysis
• Sticker Values: Applied sticker worth assessment
• Market Anomalies: Price deviation detection
• Overpay Likelihood: Premium offer probability

🎮 Trading Strategies Explained

1. Price Anomaly Detection

Identifies items priced significantly below market average, indicating potential quick-flip opportunities.

2. Sticker Arbitrage

• Conservative: Safe sticker value calculations with proven market data
• Aggressive: Higher risk/reward sticker trading with premium estimates

3. Float Tier Upgrades

Targets items close to wear tier boundaries that could upgrade with slight float improvements.

4. High Overpay Potential

Analyzes item characteristics likely to attract collector premiums and overpay offers.

🚦 Usage Workflow

1. Setup: Configure API access and trading parameters
2. Launch: Start the application and background scanner
3. Monitor: View real-time deals on the web dashboard
4. Analyze: Review profit potential and strategy recommendations
5. Execute: Use identified opportunities for manual or automated trading
6. Track: Monitor performance and adjust strategies

🔐 Security & Privacy

• Local SQLite database storage
• API credentials stored in local config file
• No external data transmission beyond CSFloat API
• Rate limiting prevents API abuse

⚡ Performance Features

• Concurrent Processing: Multi-threaded scanning and web serving
• Intelligent Caching: Reduces API calls and improves response times
• Database Optimization: Efficient deal storage and retrieval
• Memory Management: Automatic cleanup of outdated opportunities

🎯 Target Users

• Professional CS2 Traders seeking automated opportunity identification
• Market Analysts researching CS2 skin market trends
• Arbitrage Traders looking for cross-platform price differences
• Investment Researchers analyzing gaming asset markets

📊 Dashboard Features

• Strategy Filtering: View deals by specific trading strategy
• Sortable Columns: Organize by profit, price, float, or date
• Deal Management: Clear completed deals and reset database
• Responsive Design: Works on desktop, tablet, and mobile devices

🤝 Contributing

Contributions are welcome! Please feel free to submit pull requests or open issues for bugs and feature requests.

📝 License

This project is for educational purposes. Please ensure compliance with CSFloat's terms of service and applicable trading regulations.

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⚠️ Disclaimer: This tool is for educational and research purposes. Always perform your own analysis before making trading decisions. CS2 trading involves financial risk.