DexScreener

    Public forecast documentation

    SOL price forecast availability

    Current forecast values belong to the external live product. This page does not present an old observation as today's SOL forecast.

    Historical audit snapshot created 2026-09-10 — not a live/current forecast

    Where to find the current SOL forecast

    Visit the external live product for its presently published SOL value, issue time, target time, probability, and interval. Availability there is independent of this historical explanation page.

    View current SOL forecast

    Observed setup

    The audit observed four horizons: 6h, 12h, 24h, and 48h, generated on a sixth-hour cadence.

    Overlapping samples

    Because longer horizons exceed the six-hour issue cadence, their evaluation windows overlap. Adjacent errors are therefore not independent observations.

    Direction Brier score

    For n resolved forecasts: (1/n) Σ(pᵢ − yᵢ)². Here pᵢ is probability of up and yᵢ is 1 for up, otherwise 0. A constant p = 0.5 scores 0.25.

    Normalized absolute error

    For each resolved forecast: |predicted price − observed price| / |observed price|. An aggregate must state whether and how these ratios are averaged. It is not raw-price MAE.

    80% confidence band

    A lower and upper forecast interval with nominal 80% coverage. The label describes a long-run calibration target, not certainty for an individual outcome.

    Resolved forecast

    A forecast whose target timestamp has passed and whose outcome price, scoring source, and scoring rule have been recorded.

    Data provenance and recommended public export

    The statistics shown here come only from the forecast audit snapshot created 2026-09-10. Current values remain on the external live product. The local scheduled-worker forecast table is a distinct implementation and is not represented as that external production feed.

    Recommended source: a versioned, downloadable JSON and CSV dataset at the live product, with immutable issued and resolved rows, UTC timestamps, source venue, sample count n, scoring formulas, model version, and a content hash. The Dataset JSON-LD on this page preserves the audit date rather than implying freshness.