Product Manager, GameRun

GameRun is an AI-driven sports analytics tool for elite athletes, helping them track progress, analyze performance, and convert complex metrics into clear, actionable insights. The company’s existing GameRunIQ reports were dense and text-heavy, making it hard for athletes and coaches to quickly understand what mattered.

As lead product manager, I guided the redesign into a “Player Development” platform that paired AI-driven qualitative feedback with quantitative baseball metrics in a format athletes could actually use to improve.

Through user discovery interviews with collegiate athletes at all levels, we heard a consistent message: players wanted to see progress over time, understand what their numbers meant, and get simple direction on what to work on next. Those insights shaped our problem framing and early dashboard concepts.

I then led multiple prototype iterations in Figma and Lovable, translating user needs into high-impact user experience refinements. By the high-fidelity stage, athletes could interpret their velocities, spin-rates, pitch metrics, and qualitative feedback at a glance instead of reading paragraphs of text.

To guide development, I defined four core MVP success metrics: user retention, session completion rate, actionable feedback rate, and player development index. Retention was our north star for building a "development" tool athletes would return to.

GameRun was my first experience in sports tech, an industry I care deeply about, and a rewarding opportunity to build a product that genuinely helps athletes improve!