Bitcoin stock-to-flow model on CoinGlass – latest data overview

Bitcoin’s stock‑to‑flow (S2F) ratio on CoinGlass sits at ≈ 56 as of the latest update, a level that historically aligns with a price target near $70,000 according to the model’s own curve [1]. This matters because the S2F metric is a widely watched proxy for Bitcoin’s scarcity‑driven price outlook, and a shift in the ratio can signal a potential move in market sentiment.

Model reading and price context

CoinGlass’s S2F chart plots Bitcoin’s circulating supply against its annual new issuance, producing a ratio that has hovered around the mid‑50s in recent weeks. With the current ratio of roughly 56, the model’s logarithmic curve points to an implied price close to $70,000 — a modest premium over Bitcoin’s trading level of about $65,900 reported in broader market coverage [2]. The gap between the implied and actual price suggests that, if the S2F relationship holds, Bitcoin could face upward pressure as market participants compare the two figures.

Market dynamics behind the ratio

The S2F ratio rises when new supply growth slows relative to the existing stock, which occurs after each halving event. Bitcoin’s most recent halving in 2024 reduced the block reward from 6.25 to 3.125 BTC, tightening fresh issuance and nudging the ratio upward. On‑chain data shows the circulating supply now exceeds 19 million BTC, while annual new supply is under 1 million BTC, reinforcing the high S2F figure [1]. These supply dynamics, combined with a relatively stable demand environment, keep the S2F model relevant for price expectations.

What to watch

• Price at $70,000 – a breach could validate the model’s implied target.
• Next halving impact – the 2028 halving will further lift the S2F ratio, potentially moving the implied price higher.
• On‑chain supply shifts – any significant change in the rate of new BTC issuance (e.g., large‑scale miner exits) would alter the ratio and merit close monitoring.

The S2F metric remains a focal point for analysts who view Bitcoin’s scarcity as a core price driver, but its predictive power hinges on whether market participants continue to align price movements with the model’s long‑term trajectory.