📊 Trait Scoring: Rarity Formulas
Understand statistical rarity, trait normalization, and scoring
Calculate NFT rarity scores and rankings
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0 / 5 completed📊 How Trait Scoring Works
Every NFT collection stores traits as metadata—key-value pairs like "Background: Blue" or "Fur: Golden". To calculate rarity, we need to know: how often does each trait appear? If "Golden Fur" exists in 80 of 10,000 NFTs (0.8%), it's rarer than "Brown Fur" at 3,520 NFTs (35.2%). But raw frequency isn't enough—we need a normalized score to compare traits across categories.
🎨 Interactive: Build Your NFT & Calculate Rarity
Select traits for each category to create a custom NFT. Watch the rarity score calculate in real-time based on trait frequencies. Experiment with different combinations to see how individual trait rarity affects total score.
✅ Why This Formula Works
- •Inversely Proportional: Rarer traits get higher scores
- •Normalized: 1% trait = 100 points, 0.1% = 1000 points
- •Additive: Combine scores across all trait categories
- •Scalable: Works for any collection size (10 or 10,000)
⚠️ Limitations to Consider
- •All traits equal weight: Fur color scored same as background
- •No trait combos: Doesn't account for synergistic pairings
- •Missing traits matter: "None" has frequency too
- •Subjective value: Market may prefer certain traits
🔢 Rarity Score Benchmarks
💡 Key Insight
The basic trait rarity formula (1 / frequency) is simple but powerful. It transforms subjective "rarity" into objective numbers that allow instant comparisons across thousands of NFTs. However, this is just the starting point. More sophisticated methods weight traits by importance, account for trait combinations, and normalize across categories differently. The formula you choose affects rankings—a top 100 NFT in one system might be top 500 in another. Understanding the math helps you interpret rarity scores correctly and spot opportunities others miss.