How It Works

From Data to Decisions

ArcaThread combines patch-aware statistics, machine learning, and real-time game state to provide recommendations that actually make sense.

Data Sources

We don't guess. Every recommendation is backed by real match data, segmented by the factors that actually matter.

Riot API Data

Millions of ranked matches from Riot's official API, continuously ingested and processed.

Patch Versioning

Every recommendation is tied to a specific patch. No stale data from pre-rework champions.

Role & Rank Context

Diamond support builds differ from Silver. We segment data by role and rank for precise recommendations.

Regional Meta

Currently supporting EUW, with more regions planned. Our models will account for regional differences as we expand.

The Recommendation Pipeline

From the moment you enter a game to your final item purchase, here's what happens behind the scenes.

01

Game Detection

ArcaThread detects when you enter champion select or an active game via the League Client API (LCU). No manual input required.

  • LCU WebSocket connection for real-time events
  • Automatic draft phase recognition
  • Live game state monitoring
02

Context Extraction

We gather all relevant context: your champion, role, enemies picked, current patch, and your rank/region.

  • Champion select anonymity preserved (ally 1-5)
  • Enemy team composition analysis
  • Patch-aware feature derivation
03

Data Retrieval

Query our aggregated statistics for the exact matchup context: win rates, item efficiencies, rune synergies.

  • Sub-100ms query response time
  • Fallback chain: exact → rank backoff → patch backoff
  • Global safety net for new patches
04

ML Inference

Our ONNX models rank options based on millions of match outcomes in similar contexts.

  • Local inference for speed (<50ms)
  • Server-side for complex models when needed
  • Deterministic fallback if models unavailable
05

Recommendation

Present 2-3 viable options with clear rationale. You decide—not an autopilot.

  • Build path visualization
  • Situational reasoning included
  • Updates every ~30 seconds in-game
Adaptive Logic

Recommendations That Adapt to the Game

Static build guides fail because they don't account for the dynamic nature of League matches. ArcaThread reads game state and adjusts in real time.

Game Phase

Early game priorities differ from late game needs

Enemy Builds

Detects enemy itemization and suggests counter-builds

Gold Differential

Behind? Safer items. Ahead? Push your advantage.

Team Composition

Considers your team's damage types and gaps

Live adaptive recommendations view

Real screenshot coming soon

Technical

Built for Performance

<100ms

Query Latency

P95 response time

<50ms

Model Inference

Local ONNX runtime

~30s

Update Interval

In-game recommendations

Low

Memory Usage

Lightweight footprint

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