2024
Scoutition AI
Role: Fullstack Website Developer
ReactNext.jsTailwind CSSFlaskScikit-Learn
Project Performance Impact
✓
85% Prediction Accuracy✓
ML-driven Recommendations✓
15+ Training Modules
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The Challenge
Amateur and youth players often lack access to professional coaching feedback to identify their optimal field positions and personalized training plans.
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The Approach & Solution
Designed a multi-page Next.js dashboard with a Python/Flask machine learning backend. Collected player performance metrics, processed them via a trained classification model, and displayed interactive career progression paths.
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Technical Architecture
Next.js frontend, Tailwind CSS styling, Flask ML API, and Scikit-learn classification engine.
✓
Results & Outcomes
Achieved 85% accuracy in position recommendation based on test player cohorts, and received positive reviews from amateur academy coaches for its structured module delivery.