In professional esports, coaches spend hours analyzing match data, identifying player tendencies, and developing counter-strategies. Manual analysis is slow, error-prone, and often misses hidden patterns.
Scout9 Pro is an AI-powered system designed to automate scouting for esports coaches. It analyzes historical match data from VALORANT and League of Legends to generate coach-ready scouting reports highlighting team strategies, key player tendencies, and exploitable weaknesses — all in minutes.
The system is built with Python, FastAPI, React, Pandas, NumPy, scikit-learn, and uses JetBrains IDEs + Junie AI Coding Agent to accelerate development. Junie helped refactor pipelines, validate logic, and generate human-readable insights from complex esports datasets.
Scout9 Pro produces HTML and PDF reports, visualizes player and team metrics, and is structured with a modular architecture ready for expansion. It saves hours of preparation time, reduces analyst workload, and gives smaller teams access to insights previously available only to top-tier organizations.
Check out the code and sample reports here: Scout9 Pro GitHub
With Scout9 Pro, AI becomes a coach’s best assistant — transforming esports scouting into a fast, accurate, and actionable process.
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