Charlie Hubbard, Carnegie Mellon University student, outdoors in a navy blazer

CharlieHubbard

Start here

Five good places to begin.

Experience

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Projects

01Product · full-stack

PropD

A betting-line comparison product built from odds ingestion through market scanning, later acquired and integrated into BTA Sports.

NFL aging curves by position group
02Research with Ron Yurko

NFL aging curves

How player value changes across a career, and what those curves mean for roster and contract decisions.

Charlie Hubbard with NFL commissioner Roger Goodell at the NFL Draft
03NFL Draft · machine learning

Predicting the NFL Draft

A model of pick value and prospect outcomes—and a study of where draft markets still know more than the algorithm.

United Nations global humanitarian need funding model
04Datathon · team build

CMU Datathon 2026

A funding-allocation model that turns humanitarian need, delivery capacity, and risk into a transparent plan for scarce aid dollars.

Charlie Hubbard's completed March Madness bracket
05Kaggle · machine learning

March Madness model

An ensemble model combining multiple approaches to predict the NCAA tournament.

Man coverage usage rate from 2020 through 2023
06NFL coverage · research

Two-high safety research

What 33,000 NFL plays reveal about attacking the league’s increasingly common two-high safety shells.

PGA Tour scoring distribution and birdie and bogey rates
07Golf analytics · research

The bounce-back effect

A 130,000-observation PGA Tour study that found mean reversion—not a hot hand.

XGBoost approach for evaluating NBA lineups
08CMU Sports Analytics Club

NBA expansion draft

A player-value framework for deciding who an NBA expansion team should protect, target, and let walk.

Tire life distribution and pit probability by tire age
09Kaggle · predictive modeling

F1 pit-stop predictor

A Kaggle competition model for the hardest strategic question in Formula 1: when to box.

Podcast + Writing

About

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The Rubik’s cube solver I built
The Rubik’s cube solver I built
Charlie Hubbard, Carnegie Mellon University student

Background

The best way to learn is to do.

I’m Charlie, a Carnegie Mellon student doubling in Statistics & Machine Learning and Information Systems (yes, a mouthful).

Right now I’m most interested in technology’s place in the uniquely human parts of our lives.

Tell me what you’re working on
Charlie on a rocky shoreline at sunset, arms folded, looking out to sea
Nothing important lives behind this button.
“I would rather have questions that can’t be answered than answers that can’t be questioned.”

— Richard Feynman

You don’t need a reason, or an introduction. The best emails I get are from strangers.

Send one.