Local-first fantasy football draft assistant with custom scoring profiles, projection analytics, multi-source ADP/ECR rankings, and Yahoo sync. FastAPI + React + SQLite.
GCI World 2026 April - NFL Draft Prediction. Binary classification (AUC) solution using a LightGBM/XGBoost/CatBoost stacking ensemble with Optuna tuning. Matsuo-Iwasawa Lab, University of Tokyo.
NFL Draft Tracker using Python, Flask, and Bootstrap
7-round mock draft simulator based on position and prospect grade
NFL Draft Simulator For 2026 NFL Draft, Programmed in React/ Google AI Studio
Completed an analysis on the relationship between the combine performance and future league performance of 941 NFL players drafted between 2015 and 2017 using R. Proved that the combine performance of NFL players has little to no correlation on future player performance using linear regression. My goal was to show that the NFL Combine should not…
Predicting NFL Draft selection probability from Combine metrics using a tuned LightGBM + XGBoost ensemble. Features position-normalised z-scores, smoothed school target encoding, and Optuna hyperparameter tuning. Built for GCI World 2026 April In-Class Competition. Public AUC: 0.82983.
Analysis of successful NFL players as prospects
Scraped data via BeautifulSoup to create a Linear Regression Model to Predict Total Yards Rushing and Receiving of Rookie NFL Running Backs
Drafting characters from Key & Peele's East/West Bowl in Go
NFL Fantasy app (by https://brffootball.com.br/) with customized podcast
A place to store data about historical NFL draft classes
Scraping information on consensus big boards.
Can we predict an NFL rookie's success using only raw Combine traits? This project evolves my academic coursework into a fully modular, object-oriented ML pipeline. This model mathematically grades the 2026 draft class - leveling up my enterprise architecture skills while giving me an excuse to over-analyze the Chicago Bears' draft picks.
Random forest models using TDA to predict drafted round for WRs
Python analysis using draft position and NFL performance data to identify undervalued and overvalued draft prospects.
Predictive model and code used to determine the relationship between variables collected from each game and the number of wins for a given team in 2020.
Current Raiders draft-room tool for depth fragility scoring, prospect fit, and Mintlify documentation.
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