This is like having a super-analyst in the back office that watches every play, crunches all the stats, and then hands coaches a few clear, data-backed answers: which recruits to chase, what lineups work best, and what tendencies opponents really have – without the staff needing to be data scientists.
College football staffs are drowning in video, tracking data, and stats but lack time and tools to turn it into clear decisions on recruiting, roster management, game strategy, and player development. Recon-style platforms aim to turn raw data into simple, actionable insights for coaches and front offices.
Domain-specific data (play, tracking, and recruiting datasets), embedded in coaching workflows, plus know-how translating football concepts into usable analytics gives a defensible edge over generic analytics tools.
Hybrid
Vector Search
Medium (Integration logic)
Data integration and quality across game film, tracking, and recruiting sources; plus model re-training as schemes and play styles evolve.
Early Adopters
More focused on college football decision support (recruiting and tactical insights) than generic performance tracking or pro-level analytics; emphasis on packaging insights in coach-friendly, non-technical interfaces.