SYSTEMS · ESPORTS ANALYTICS
An AI analyst and coach that turns official GRID match data into advanced metrics, what-if simulations, and live strategic guidance for League of Legends and VALORANT.
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Esports teams review matches from raw stat lines that miss context. A KDA tells you who died, not why a round was lost or what a team should have done differently. Coaches need deeper competitive metrics and in-match guidance, not just box scores. Team Intuition Engine pulls official match data from the GRID Esports API and turns it into Moneyball-style analysis for League of Legends and VALORANT.
A FastAPI backend ingests match data through GRIDClient, then runs it through title-specific processors that compute advanced metrics beyond basic statistics. The structured output is handed to an LLM layer that writes narrative analysis and coaching recommendations, so numbers become readable strategy. A Next.js dashboard called Junie surfaces the metrics and insights and can simulate alternative outcomes from live game state.
GRIDClient authenticates with a GRID API key and fetches official match data for League of Legends and VALORANT.
ValorantStatsProcessor and ValorantAnalyzer calculate metrics like ACS, KAST %, and Economy Impact that go beyond basic KDA and Combat Score.
The structured stats are passed to the LLM layer, which produces readable analysis and strategic recommendations.
What-if modeling replays alternative match outcomes from live game state to test hypothetical decisions.
The Next.js dashboard renders metrics, insights, and contextual coaching during active matches.
Calculates ACS, KAST %, Economy Impact, and other metrics that basic stat lines leave out.
Models hypothetical what-if outcomes by replaying alternative match states from live game data.
The Junie Dashboard delivers contextual strategic recommendations during active matches.
Works across both League of Legends and VALORANT from a single platform.
An LLM turns raw statistics into plain-language analysis a coach can act on.