Item Analytics
Advanced metrics powered by machine learning algorithms
Projected Items
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High Demand
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Items Analyzed
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Last Updated
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Potentially Projected Items
0 items| Item | Projected Score | RAP | Fair Value | Risk Level |
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How Projection Detection Works
Our algorithm analyzes price history to detect artificial RAP inflation:
- Spike Detection: Identifies sudden price jumps above rolling averages
- Outlier Analysis: Counts sales that deviate significantly from the mean
- Volatility Check: High volatility + spikes = suspicious
- Recovery Pattern: Fast price drops after spikes indicate manipulation
Trading Tip: Items with scores above 50 should be verified before trading.
Score Legend
0-30
Low Risk - Appears organic
30-50
Moderate - Some anomalies
50-70
Suspicious - Verify before trading
70+
High Risk - Strong manipulation signs
High Demand Items
0 items| Item | Demand Score | Sales Velocity | Volatility | Trend |
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Demand Score Formula
Demand is calculated from multiple factors:
Sales Velocity
40%
Price Trend
25%
Price Stability
20%
Liquidity
15%
Most Liquid Items
| Item | Liquidity Score | Active Trading Days | Avg Daily Volume | RAP |
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Most Volatile Items
| Item | Volatility Index | Price Range (30d) | Spread Risk | Fair Value |
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Find Similar Items
Cosine Similarity
Our similarity algorithm uses cosine similarity on item feature vectors:
- Volatility Profile: Similar price stability
- Demand Pattern: Similar trading activity
- Price Tier: Similar value range
- Trend Behavior: Similar price movements
Use this to find items that behave similarly for portfolio diversification!