Orbis Ranking

How collections are scored and ranked on the marketplace.

Continuously evolving

Overview

Every collection on Orbis receives a composite score from 0 to 100, computed from 10 independent on-chain and marketplace signals. The score reflects a collection's overall health, activity, and market position relative to its peers.

Rankings are recalculated periodically and update automatically. The algorithm uses percentile-based normalization — each signal is compared against all other collections, not measured in absolute terms. This keeps rankings fair regardless of collection size or age.

High scores (70+) indicate strong, active collections with healthy holder distribution, consistent trading volume, and stable or rising floor prices.

Mid-range scores (30–70) are typical for most collections. Many signals are neutral or mixed — this is perfectly normal and not inherently negative.

Lower scores (<30) may reflect limited trading activity, high listing ratios, or new collections that haven't yet built a track record.

The 10 Signals

Each signal captures a different dimension of collection health. Signals are weighted to reflect their relative importance. Weights may be adjusted over time and additonal metrics added as the algorithm evolves.

Volume15%

Blended trading volume: 70% weight on 24h volume, 30% on 7-day volume. Recent activity is prioritized.

Market Cap15%

Total market capitalization of the collection, reflecting its overall value in the ecosystem.

Bot Sale Health10%

Inverse of the share of sales where the buyer is a flagged bot wallet. Collections with cleaner organic demand score higher; wash-trading / sniper activity drags the signal down. Requires at least 10 lifetime sales to activate.

Floor Stability10%

Measures price consistency over time using coefficient of variation. Lower volatility = higher score.

Holder Ratio10%

Unique holders relative to total supply. A higher ratio indicates healthier ownership distribution.

Listing Health10%

Inverse of listing ratio — fewer listed NFTs relative to supply suggests holders prefer to keep their assets.

Sales Velocity10%

Recent sales momentum, with extra weight on the last hour. Captures real-time demand surges.

Price Trend10%

Direction and strength of floor price movement using linear regression. Positive trends score higher.

Collection Age5%

How long the collection has existed, capped at one year. Older collections have more proven track records.

Offer Engagement5%

Number of active offers on the collection. More offers indicate stronger buyer interest and market depth.

How Scores Are Calculated

1. Signal Extraction

Raw values for all 10 signals are gathered from on-chain data, marketplace activity, and staking integrations. Each collection's data is evaluated independently.

2. Percentile Normalization

Raw values are converted to percentile scores (0–100) by ranking each collection against all others. A collection with the highest volume doesn't get "100" — instead, its score reflects its percentile position relative to the full marketplace.

This approach ensures that one dominant collection doesn't skew the entire ranking. Ties are handled by averaging their positions.

3. Missing Data

If a signal isn't available for a collection (e.g., too few lifetime sales for bot-activity analysis, or not enough price history), it receives a neutral score of 50. Missing data neither helps nor hurts a collection's ranking.

4. Weighted Composite

The final score is a weighted average of all 10 normalized signals. Each signal's contribution is proportional to its weight. The result is rounded to produce the final 0–100 score displayed on the marketplace.

Always Improving

The Orbis Ranking algorithm is not static. It's designed to evolve alongside the marketplace.

Signal weights may be adjusted as we learn which factors best reflect collection quality.
New signals may be added as the ecosystem grows (e.g., social engagement, cross-marketplace data).
The normalization approach ensures rankings remain fair even as the number of collections changes.
Small collections and large collections are evaluated on equal footing through percentile-based scoring.

Our goal is to surface genuinely healthy, active collections — not just the largest or most hyped. The ranking rewards real utility, community engagement, and sustained market activity.

Help Shape the Ranking

Rate how important each signal should be when ranking collections. Your feedback directly informs how we tune the algorithm.
1 = Not important, 10 = Critical.

Connect your wallet to submit your ratings