Majadu Tools
Glicko-1 Rating Engine & Frameworkless Go API
Overview & Problem
Majadu powers local sports session operations—generating balanced doubles matchups, live court scoring, tournament brackets, and cross-season skill rating tracking.
Casual sports sessions suffer from subjective player seeding, manual paper scorekeeping, and network drops during live matches in sports halls with weak cellular coverage.
Architecture
A monorepo with a React 19 PWA frontend and a zero-dependency Go 1.26 backend API using PostgreSQL 18 with schema-based multi-tenancy.
Engineering Trade-offs
Frameworkless Go backend
Built using Go standard library net/http and pgx/v5. Sub-millisecond response times and instant cold starts inside rootless Podman containers.
Glicko-1 rating with confidence decay
Replaced raw win/loss tallies with a custom Glicko-1 rating engine (Glicko-1-lite) that factors in victory margin and increases rating deviation when players skip seasons.
Schema-isolated multi-tenancy
Community databases use PostgreSQL search paths per seasonal domain rather than row-level tenant IDs, simplifying backup and data isolation.
Key Takeaway
Standard-library Go code paired with a disciplined mathematical rating model delivers high production reliability with near-zero server resource usage.
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