Unified Platform for Football Operations and Recruitment

Football has a coordination problem. Players, coaches, and clubs constantly move between teams, but the tools connecting them—training schedules, match history, recruitment visibility—are fragmented across WhatsApp, spreadsheets, and federation websites.

I designed and built Le Club, a unified platform that centralizes team management, player performance, and recruitment into a single system.

A shared data model powers multiple experiences: coaches manage trainings and squads, players track performance, clubs organize across teams, and recruiters discover talent with verified data.

Core Capabilities

• Multi-role platform (players, coaches, clubs, recruiters) with unified access
• GraphQL API covering teams, players, matches, trainings, and competitions
• Identity and authorization system based on OpenID Connect (OIDC)
• Real-time notification system for events and user interactions
• Data ingestion pipeline aggregating verified football data from external sources

Key Results

• Replaced fragmented workflows with a single, coherent multi-role platform
• Unified identity model across backend and clients, avoiding duplicated access logic
• Secure data access via role-based authorization and row-level security
• Continuous enrichment of platform data through large-scale ingestion pipelines

Architecture Overview

Le Club is a polyglot TypeScript/Python monorepo composed of distributed services:

• API (Node.js + Koa + Apollo GraphQL)
  Exposes a unified domain model for clubs, teams, players, and events, backed by MongoDB
• Identity Layer (OIDC Provider)
  Handles authentication and authorization with role management and Hasura integration
• Notifications (RabbitMQ + Server-Sent Events)
  Decoupled real-time event delivery system
• Data Pipeline (Python + Celery + Redis)
  Scrapes and normalizes football data (FFF, RBFA, Soccerway, etc.)

Technical Highlights

• Built a full OpenID Connect provider with PKCE flows and email/phone authentication
• Modelled event hierarchy using Mongoose discriminators (trainings, matches, tournaments)
• Implemented real-time notifications via SSE backed by RabbitMQ
• Designed a distributed ETL pipeline with proxy rotation (Scrapoxy) for large-scale scraping
• Shared TypeScript types and configuration across a multi-service monorepo

My Role

Owned the system end-to-end:

• Designed architecture and data model
• Built the GraphQL API and identity layer
• Implemented real-time notification infrastructure
• Developed the data ingestion pipeline
• Contributed to frontend applications (React, video upload, match annotation)