College compatibility tool for high school athletes who want playing time

A family spends three years and $14K on a recruiting consultant, tournament fees, and showcases. Their kid gets ignored by every coach they wanted to meet. The consultant still gets paid. Roster spots, recruiting class sizes, how many minutes similar players got. All public the whole time. Nobody showed them where to look. FitFinder matches athletes to programs where they'll see the field. Enter sport, position, and stats. It cross-references roster depth, recruiting class size, and how many minutes similar players got in year one. A D2 with a graduating senior at the kid's position ranks higher than a D1 with three upperclassmen blocking the path. Consultants send blast emails to every program on a list. FitFinder checks who's leaving. Start in men's baseball, where 35-man rosters and high transfer portal activity make depth chart logic easiest to prove. Most athletic department websites publish rosters in standard HTML tables with name, position, year, and hometown. A Python crawler can scrape those weekly and cross-reference transfer portal databases to track who's leaving and where gaps are opening. Store everything in Supabase indexed by program, position, and class year. Partner with three club teams as early testers, track where their athletes commit and whether they play, and adjust weights until the model predicts playing time, not just offers. Families spend $5K-10K on consultants who never check the roster. Charge $29/month for matching and outreach tools, $99/month for premium with coach connections and film review. Club teams license the dashboard for $500/month to give their members something consultants can't touch: data that updates every time a player transfers, commits, or walks away. One club partnership seeds 200 families. The transfer portal made roster data volatile. Volatile data rewards whoever tracks it best.

What you get with the full dossier