About VladDog (VLADDOG):
Currently trading at $0.00007672, with a market capitalization of $72.66K and a 24-hour trading volume of $76.24K. Liquidity reads as high-turnover trading conditions (volume/market cap 104.93%) High turnover often keeps markets responsive during high-activity windows..
Market assessment:
Bull score 38/100 suggests weak momentum with limited upside traction with participation that remains subdued..
Windowed performance: -54.42% (24h), 0.00% (7d), 0.00% (30d). Windows are mixed, suggesting a range-bound or transitional structure.
The 24h tape is fast and reactive in this update. Risk is assessed as Low, which implies more stable conditions with tighter volatility behavior Risk metrics are snapshot-based and can evolve with the market..
VladDog (VLADDOG) is positioned in the Late phase,
typically associated with a late phase where downside sensitivity can increase Late-cycle conditions can amplify both rallies and pullbacks..
Supply design details are limited in the current snapshot fields.
Conclusion: From a structure view, the setup currently reflects a defensive structure where capital preservation becomes a priority. Update date: 2026-07-15.
YearBull Rank on this page
Newest YearBull Rank value for vladdog: #6423.
Rank timeline (last 365 days)
Rank movement (nearest daily data).
Reading rule: rank #120 sits higher than rank #200.
- 7d window: no reference point available.
- 30d window: no reference point available.
YearBull Rank is a comparative ordering used on YearBull to place a coin versus others using a consistent set of inputs. Use it as positioning context over time, not as a promise.
Phase read: If both windows align, the direction is clearer. a stable phase often tightens the rank range.
Where it trades: If the line breaks range, confirm it across a longer window. changes can follow how the coin is routed across markets.
Flow context: If the curve improves and holds, it is usually more structural. rank can move when liquidity redistributes across the cohort.
Risk note: If you see repeated snap-backs, assume sensitivity to one factor. big jumps can be data-driven, but also rotation-driven.
Editorial note:
This analysis was prepared by the YearBull research team under the direction of
Alan Zelvin,
Founder and Lead Crypto Researcher.
The assessment follows YearBull’s internal research methodology and editorial standards.
Methodology ·
Editorial Policy
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