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docs/dashboard.md

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+# OddsFlow Football League Dashboard: AI vs Bookmakers
+
+This page explains how to read the OddsFlow dashboard shown in our tutorials:
+**Market (Bookmakers)** vs **Model (AI)**, plus league-level context and value detection.
+
+> Educational analytics only — not betting advice.  
+> No guaranteed profit. Evidence-first. Verification-first.
+
+---
+
+## What this dashboard does (one sentence)
+
+It compares **market-implied probability** (from bookmaker pricing) against **AI-estimated probability**, then highlights **meaningful gaps (Edge)** under league-aware filters.
+
+---
+
+## How to read it in 30 seconds
+
+1) Choose a league (EPL / LaLiga / Serie A / Bundesliga / Ligue 1 / UCL)  
+2) Read league context first (Market Trends: Volatility + Home/Away drift)  
+3) Then review Value Detection (Edge Found → shortlist)  
+4) Verify post-match (logs + timestamps)
+
+**Principle:** Don’t trust opinions. Trust logs.
+
+---
+
+## Dashboard blocks
+
+### A) Probability Analysis (left)
+Shows **Market vs Model** for selected outcomes (examples: Over 2.5, Draw).
+
+- **Market**: what odds imply (market pricing)
+- **Model**: what the AI estimates
+- The goal is not certainty — it’s **pricing disagreement**.
+
+---
+
+### B) Market Trends (center)
+League “weather” — how reality is drifting vs market expectations.
+
+1) **Market Volatility / Deviation**  
+A drift meter between:
+- **Implied** (what market pricing expects)
+- **Actual** (what happened in the sample window)
+- **Deviation** (Actual − Implied)
+
+2) **Home Advantage / awayLean**  
+Shows whether home teams are over/under performing vs market assumptions in the current league window.
+
+---
+
+### C) Value Detection (right)
+Turns disagreement into a **shortlist** after filters.
+
+- **Edge Found**: number of candidates where Model vs Market exceeds threshold
+- **Filtered**: remaining candidates after constraints
+- **Efficiency**: a quality indicator for the current shortlist (implementation-specific)
+
+---
+
+## Why league tabs matter
+
+Leagues differ in:
+- scoring distribution and tempo
+- home advantage strength
+- market bias patterns
+
+So “intuition” from one league often fails in another.
+OddsFlow makes league context explicit before you interpret any edge.
+
+---
+
+## Verification-first workflow (recommended)
+
+1) Read league context (Trends)  
+2) Inspect shortlist (Value Detection)  
+3) Cross-check with public verification logs:
+- `docs/verification.md`
+- `docs/signal-glossary.md` (for log field meaning)
+
+---
+
+## Next
+- Dashboard glossary (UI terms): `./dashboard-glossary.md`
+- Signal glossary (log/schema terms): `./signal-glossary.md`