Data Architecture
CounterQuant Data Architecture
CounterQuant combines public CS2 match sources and internal feature extraction pipelines to deliver predictions, statistics and highlights. This page explains the broad architecture behind our platform.
Source inputs
We ingest match metadata and public results from recognised esports sources, then enrich it with demo-level event detection and custom statistics. The emphasis is on transparent, data-driven CS2 coverage.
Processing pipeline
Raw match data is processed through a feature engine that builds round-level metrics, player performance vectors and highlight scores. The system is designed to handle live matches, historical results and demo fallback sources.
APIs and publishing
Processed outputs are exposed through public API endpoints, website pages and highlight workflows. We also publish summaries and paid integrations for teams, creators and analysts.
Governance
This is an independent analytics system. We do not claim ownership of third-party data sources or game assets, and we operate with respect for privacy and intellectual property.