Sports and Character Knowledge: Lister App
Lister is a minimalist trivia-style game built around a simple challenge: list as many valid names as you can within a time limit, without repeating any entries. Players choose a category (e.g., NFL, NBA, MLB, soccer, movie actors, etc.) and type in names as they come to mind, just like scribbling lists on paper during downtime or on a plane. The timer pauses when you leave the app, and each entry is validated and checked for duplicates in real time.
Beyond basic correctness, Lister scores each answer using a rarity system inspired by games like Immaculate Grid. Rarity is calculated from real-world stats (snaps, minutes played, time in league, etc.) and from how frequently that player or person is named by the Lister community. This lets users see not only how many names they remembered, but how deep their "ball knowledge" really is.
Designed as a free, no-hints, no-pay-to-win experience, Lister focuses on clean gameplay and re-playability. It’s built for sports fans and pop culture nerds who enjoy testing their memory, comparing scores with friends, and discovering which of their favorite obscure players or actors almost no one else remembers.
Currently in Beta development.
Swap Lab
Swap Lab is a player comparison and trade-scenario tool that lets users evaluate two, for example, NBA players side-by-side and simulate “swap” outcomes between teams. It combines traditional and advanced stats with role/context indicators helping users judge roster fit, strengths/weaknesses, and projected impact in a visual, debate-friendly format. The experience is designed to make hypothetical trades feel structured, data-backed, and easy to understand at a glance.
Currently in early stage development.
Instagram Followers vs Following Analyzer
Follower Audit helps users understand their Instagram network by importing Instagram’s official data download (zip), parsing the followers and following lists, and showing clear differences—like who doesn’t follow back, accounts you’ve unfollowed, and changes over time. The product is built with a privacy-first mindset: users analyze their own exported data locally, then filter/search results and export lists for personal tracking. It turns a messy data dump into a clean, useful dashboard.
In pre-launch development
