Trading activity:
Reported 24-hour volume equals 0.00% of market capitalization. The local markets snapshot lists Raydium among venues with observed trading activity.
YearBull indicators:
YearBull Rank #6,054. Bull Score 41/100.
YB Market Risk Low. This relative market-volatility label is not an investment-safety assessment.
Cycle Early. Observed price change: 24h -0.56% · 7d -2.92% · 30d -29.42%.
Values are descriptive and should be read together rather than as a price forecast.
Read the YearBull methodology.
Snapshot date: 2026-10-27.Data history: 89 daily observations available in the latest 90-day window.
Methodology responsibility:
YearBull’s analytical methodology and presentation rules are developed and maintained by
Alan Zelvin, Founder & Lead Crypto Researcher.
This note identifies responsibility for the methodology; it does not attribute authorship of this data snapshot.
What is ROVR Network (ROVR)?
Source description
“ROVR is a decentralized global platform designed for high-definition, real-time 3D data collection, processing, and storage across all scenarios. We are driven by the belief that data ownership should rest with individual producers, not large corporations or organizations. By generating vast volumes of ultra-high-definition 3D and 4D data—complete with detailed timelines—ROVR is establishing a robust foundation for the next generation of 3D AI training.”
This source-supplied description may contain old, promotional, or unverified claims and is not YearBull editorial analysis.
Official links and contract records appear in Key Facts. Project details can change, so verify current information with the project.
ROVR Network (ROVR) FAQ
How does ROVR approach ownership of three-dimensional data?
ROVR presents its platform around the principle that ownership of captured data should remain with the individuals who produce it, rather than large corporations or other organizations. Its stated focus is decentralized collection, processing, and storage of high-definition three-dimensional and four-dimensional material across varied scenarios. The project does not specify the legal or technical mechanisms used to enforce those ownership rights.
What type of material does ROVR aim to collect and preserve?
The project says it is built to handle ultra-high-definition 3D and 4D material, including detailed timelines that preserve how scenes or environments change over time. ROVR positions this capability as suitable for broad real-world scenarios rather than a single industry. Specific capture devices, supported formats, retention policies, and storage architecture are not specified.
How does ROVR connect its 3D and 4D platform with machine-learning development?
ROVR states that its large-scale collection of spatial material and time-based detail is intended to support the next generation of 3D machine-learning training. In that framing, the platform’s role is to establish a broad foundation of richly structured real-world examples. The project does not specify which models, training methods, organizations, or commercial applications will use these materials.
What role does decentralization play in ROVR’s platform concept?
ROVR describes itself as a decentralized platform spanning the collection, processing, and storage of high-definition spatial material. This positioning aligns with its stated aim of giving individual producers greater control over their contributions instead of concentrating control in large institutions. The project does not detail its network architecture, participant incentives, governance procedures, or how responsibilities are distributed.
Why is ROVR associated with robotics and the DePIN category?
ROVR’s stated emphasis on real-world 3D and 4D collection helps explain its association with robotics and decentralized physical infrastructure categories. Spatially detailed, time-linked material can be relevant to systems that interpret environments or train machines, although the project does not identify a specific robotic product or hardware network. These category associations should therefore be treated as positioning rather than confirmed applications.
ROVR Network metric comparison
This comparison is a stored snapshot generated 2026-10-23 06:31 UTC from 275 daily observations available from 2025-12-30 through 2026-10-23. It is separate from the latest analytical cards above. Percentiles compare the snapshot value with that day's analytical universe; a higher percentile means a larger observed value, not necessarily a better investment characteristic.
Metric
Snapshot
30d before
90d before
Change vs 30d
Universe percentile
Price
$0.00012688
$0.00017619
$0.0001855
-28.0%
n/a
Market cap
$1.26M
$1.75M
$1.85M
-28.0%
P67.6
YearBull Rank
#5,598
#2,340
#5,782
Lower by 3,258
P34.5
Bull Score
41/100
64/100
18/100
-23.0 pts
P35.3
Turnover
0.01%
0.01%
0.00%
+0.0 pts
P11.9
YB Market Risk
Low
Low
Low
Unchanged
n/a
Cycle
Early
Early
Mid
Unchanged
n/a
Median absolute daily movement 2.22%; distance from the highest local daily price -98.4%; circulating supply change +4,556.6%. These measurements are descriptive and do not predict future direction.
YearBull Rank overview
Most recent YearBull Rank reading for rovr-network is #6054.
Rank timeline (last 365 days)
Rank movement (time windows).
Reading rule: lower is better in this ranking.
7d window (2026-10-20): #5999 → #6054 (down by 55).
30d window (2026-09-27): #1709 → #6054 (down by 4345).
YearBull Rank is a relative placement score used on YearBull to compare a coin against peers within the same dataset. It is best read as relative context across time windows, not as a guarantee.
Market access: If the line range narrows, access may be stabilizing.
Risk context: Read it as "how stable is the position" rather than "how exciting is today".
Rotation context: Compare the 30d move with the 7d move to see if momentum is accelerating or fading.
Liquidity framing: If the line flatlines, the coin may be moving with its liquidity peers.
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
Related Research
Continue with contextually connected profiles and category data:
BOOP analysis - nearby market scale in the current dataset.
GaiAI analysis - nearby market scale in the current dataset.
XRP analysis - editorially reviewed peer in the same category.
Venue refresh pending. Markets last checked: 2026-07-26. The next refresh is queued in the hourly updater. Venue listings and volumes are stored snapshots, not live quotes.
