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.

Kinetic Adaptation via Wasserstein Heuristics and Identity

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

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

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

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.

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.

Analytics Engineering Project looking at Phoenix Suns player shooting performance data

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.

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.

Classify NBA players into positions using per-game statistics using various classification algorithms, feature selection, and performance evaluation techniques