Crypto Signals Methodology: How Metrics in the Table Are Generated

Data Flow and Snapshot Logic

The dashboard reads a generated snapshot from data/dashboard.json via /api/dashboard_file.php. This endpoint is intentionally snapshot-based: it avoids expensive or unstable runtime queries on shared hosting while still returning the same data structure expected by the frontend.

How the Scanner Computes Signal Quality

On the local scanner side, quality is assembled from multiple components (not from a single indicator): volume-to-market-cap participation, 24h volume momentum, daily price sweet-spot behavior, short-term alignment, rank stability, and longer-timeframe context. Penalties reduce score for overheating, weak market structure, dilution risk, and low pair depth.

How Dashboard Stats Are Aggregated

The API computes summary values across all snapshot rows: average 24h change, average risk score, average quality score, average market cap, BTC context means, TP hit count, and active risk count. These values are context indicators, not execution guarantees.

Frontend formatting applies adaptive precision for low-price assets, directional coloring for momentum, and badges for new/risk/TP/pump conditions. For label semantics, continue with Status Guide. For constraints and safe usage, read Risk Policy.

Plain English Signal Legend

Example line: Momentum 67/100 · Conf. 0.0/10 · BTC +0.9% (24h) · Risk 7/10 · 56% (B)

Simple interpretation: this setup shows moderate momentum and medium quality, but risk is high, so it should be treated conservatively.

Risk Warning

Methodology descriptions do not guarantee performance. High volatility can invalidate expected setups fast. Use strict risk controls and never treat scanner output as investment advice.