{"repo":"IanDublew/QuantIntelli","free":true,"listed":false,"github":"https://github.com/IanDublew/QuantIntelli","clone":"git clone https://github.com/IanDublew/QuantIntelli.git","description":"A Hybrid AI Agent for Quantitative Football Prediction Analysis","language":"Python","stars":12,"topics":["rag","sports-analytics","ai-agent","data-science","decision-support-system","educational-project","football","google-gemini-ai","gradio","hybrid-ai"],"license":null,"category":"ai-agents","readme_excerpt":"QuantIntelli+ ⚽️ A Hybrid AI Agent for Quantitative Football Prediction Analysis QuantIntelli+ is not just another prediction bot. It's a sophisticated, two-stage analytical agent that fuses a battle-tested statistical model with a powerful, context-aware RAG-LLM pipeline. 🔗 Quick Links - Try QuantIntelli+ Live - View Prediction Analysis --- ✨ Core Features 🧠 Dual-Engine Analysis: Combines a fast XGBoost model for baseline statistical predictions with a deep Google Gemini LLM for contextual analysis. 🌐 Advanced RAG Pipeline: Dynamically searches the web using Tavily, Google, and DuckDuckGo to gather real-time, relevant information like team news, injuries, form, and H2H stats. 📄 Content Enrichment: Goes beyond snippets by fetching and parsing full-text articles from top-ranking search results to provide deeper context to the LLM. 📊 Structured Analytical Output: Generates a detailed, professional-grade report with sections for Dual Recommendation , Conflict Resolution , Market Efficiency , and Risk Analysis . 💾 Persistent Session Logging: Uses Supabase to log every prediction and its subsequent analysis, creating a traceable record of the agent's reasoning. 🕹️ Interactive UI: Built with Gradio for an intuitive, easy-to-use interface that guides the user through the two-stage analysis process. --- 🚀 How It Works: The Analysis Pipeline QuantIntelli+ operates a unique two-stage workflow to deliver its insights. 1. 🎯 Stage 1: The Statistical Prediction A user inputs match","default_branch":null,"files":null,"tree":[],"storefront":"/r/IanDublew","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/IanDublew/QuantIntelli/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}