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How to evaluate the rarity of NFT more reasonably?

December 16, 2021
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This article will discuss how to evaluate the rarity of NFTs more reasonably. The rarity score is an aid. Different NFT project parties will give more important announcements about certain attributes. Will also be affected by personal subjective aesthetics.

What is the rarity of NFT?

Generally speaking. The rarity of NFT includes two concepts: feature rarity and asset rarity.

Feature rarity: a measure of the frequency of appearance of each feature. That is, the proportion of the feature in this set. For example, the rarity score of the feature “Background_Blue” is 10.44%. Because the total number of Short Bear Club is 5,000. Among them are 522 “Background_Blue” bears.

Asset rarity: represents the total rarity score of the asset. Can be used for horizontal comparison and ranking. The value of a single NFT is usually largely affected by rarity. For NFT collectors, when they are considering which NFT to buy. They hope to spend the same amount of ETH to bring the greatest return. Therefore, rarity has become one of the most important reference indicators.

Existing rarity scoring model Rarity.Tools Rarity scoring

Rarity.Tools is currently the most widely used rarity scoring tool. Its core calculation method is to add the reciprocal total value of the percentage of each feature’s frequency of occurrence.

However, Rarity.Tools has recently adjusted its calculation model. And no specific details were publicly disclosed.

Rarity.Tools is an NFT rarity data analysis tool that existed before the outbreak of NFT Summer. Its advantage is that the calculation model is simple and easy to understand. Users can intuitively see which feature contributes more to the overall rarity score. But the disadvantage of the simple summation method is that it may overestimate or underestimate the true rarity of an asset. For example, if the score of a certain feature or the number of features is too high, it will raise the NFT’s ranking to a certain extent. But users may not pay much attention to this feature.

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