Kinetic Adaptation via Wasserstein Heuristics and Identity

Coaching Experience's Effect on Winning

Competition-winning Rebound Prediction Notebook

Dunk Vision is a desktop basketball shot tracker and data capture tool built using Python and tkinter. Designed for youth coaches, players, and parents, it lets users track, visualize, and analyze shot data to improve individual and team performance as well as direct training efforts. For courtside users, data can be exported for later analysis.

Multi-scenario analysis of how NBA trash talk and conflicts affect player performance

A professional NBA scouting application that combines live player data from the official NBA Stats API with a two-stage AI agent architecture. The system researches player tendencies, identifies comparable players, fetches their live stats, and synthesizes everything into an executive scouting memo.

A full CV basketball analytics system powered by YOLOv12, ByteTrack, SuperPoint/LightGlue, FastAPI, MongoDB, minIO, Prometheus and Grafana to turn raw basketball broadcast footage into rich spatial analytics and visualized insights.

Player Development Report: Lulu Twidale (Cal). College Career Growth & Dev Analysis Year 1 - Year 3, 2024-2026

Landing website of the ultimate coach assistant for collecting and analyzing basketball statistics. Code was generated with no-code editor Teleporthq.io

Aplicación para recomendar pares de jugadores NBA complementarios para la temporada 2020-2021, utilizando datos de 2015 a 2020.

Files used in code to generate findings, code, and associated visuals and research report

Files used in code to generate findings, code, and associated visuals and research report

A React web app that helps NBA bettors make more informed decisions by visualizing player performance against betting lines with interactive charts and filtering options.

Objective basketball shot recognition using wearable sensors and biomechanical machine learning. Classifies court zones (Paint, FT, 3-Point) with 94.5% accuracy using quaternion-based earth-frame transformations and optimized SVC.

Files used in code to generate findings, code, and associated visuals and research report

WNBA salary-value retrospective using 2023–2025 production, 2026 salary context, comparable-player pricing, and scalability signals.

Codebase for my submission to Kaggle's yearly March Machine Learning Mania competition

Basketball analytics platform — AI-driven game analysis and strategic insights.