ArcaThread desktop app is still in development and coming soon.
From Data to Decision Support
ArcaThread combines LCU game-state capture, patch-aware logic, and ML-assisted scoring to surface actionable suggestions.
Data Sources
Claims on this page map to active code paths in the desktop app and runtime services.
Official Client Data
Runtime state is read from official League Client (LCU) endpoints and related aggregation services.
Patch-Aware Routing
Recommendation logic is patch-aware and includes fallback paths when coverage is sparse.
Role and Rank Context
Draft/live scoring can include role assumptions and rank-aware model routing.
Region-Aware Inputs
Current runtime focuses on supported regions in your configured environment.
Recommendation Pipeline
The runtime flow below reflects active application architecture.
Game Detection
ArcaThread detects champion select and live games through LCU events and polling.
- LCU event-driven updates
- Draft/live phase recognition
- No game process memory access
Context Extraction
The app builds a normalized state payload from champions, items, objectives, and timing context.
- Patch and queue context
- Team composition extraction
- Gold, level, and item state features
Scoring and Retrieval
Context is routed through stats-backed and ML-assisted scoring paths with deterministic fallback behavior.
- Counter-item analysis categories
- Rank-aware model lookup
- Fallback chain when data/model is unavailable
ML Inference Layer
ONNX runtime support is used for local inference paths, alongside fallback logic to keep outputs available.
- ONNX runner integration
- Model service caching
- Graceful fallback to non-ML recommendation paths
Suggestion Output
Recommendations are presented as options with rationale. The player always makes the final decision.
- Suggestion-only UX
- Build path and alternative options
- Configurable interval (30s default)
Live Context Signals
Live recommendations can react to multiple state signals, not only static matchup tables.
Game Phase
Recommendations can differ between lane, mid game, and late game context.
Enemy Itemization
Counter-item categories include anti-heal, defenses, penetration, and utility responses.
Timing and Tempo
Recommendation refresh follows runtime intervals with a 30-second default setting.
Embedding Layer
Champion features include 20-dimensional embeddings used in multiple recommendation paths.