Floor Price of an NFT Collection

• The floor price refers to the lowest amount of money that can be paid for an NFT item from a specific collection.
• This minimum price is established by the creator at the time of minting. However, once NFTs enter secondary markets, the floor price is set by supply and demand.
• Typically, buyers try to sell their NFTs at a higher floor price than they paid at the time of minting, in order to make a profit.
• The minimum price in the secondary markets is shown in real time, which means that it changes continuously depending on the lowest value in the market in which it is located. Logically, the floor price can fluctuate both upwards and downwards.

Overview

However, there is not a set parameter in the tables that defines the floor price of an NFT collection on the blockchain. Thus, this dashboard aims to provide different metrics that can be used to estimate the floor price of an NFT collection. For demonstration purposes, the top 4 sports NFT collections will be analyzed, along with one of the most bought collections on Flow: Genies.

Average Price

Moving Averages

• The average price of an NFT collection is measured by suming all the sale prices in a collection and dividing the total by the number of sales.

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• However, this is the least accurate metric amongst those commented in this dashboard. This is because in case some sales were much higher than the lowest NFT for sale or there were not many sales on that day (and happened to be slightly higher in price than those on previous days), this value would be much higher than the actual floor price of a collection.

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• This metric provides some information about the price tendency, but it is far from accurate from the floor price.

• A moving average is a technical indicator that combines prices of an asset over a set period of time, and divides them by the number of data points collected to give a trend line.

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• The charts above show the 7 and 30 day moving averages (MA). We can see that these are much smoother compared to the daily average price, as in case one day has just a few sales but way higher than the floor price, this value is compensated with the average price of previous days.

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• We can see that for all 5 collections the 30 day MA is more accurate than the 7 day MA.

Percentile Based on a Continuous Distribution

• This last section calculates the floor price of these NFT collections using the percentile function. A percentile can be defined as the value in a normal distribution that has a specified percentage of observations below it.

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• This means that we take the X lowest percentage of the average of sales.

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• As the 4 sports collections sell their NFTs (moments) in packs, and this come in different rarity tiers, the range dispair of sale prices can be very big.

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• Thus, using the 5th and 25th percentile, we are only averaging the price for the lowest 5 and 25% of sales.

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• Percentiles seem to be the most accurate metrics, as we compare it with the official floor price stats for each collection. In conclusion, low percentile measures are the best way to measure NFT floor prices on Flow. If a collection has a large amount of sales, a the 25th percentile will be a great aproximation to the floor price of the collection (as the FP might have risen). On the other hand, if the collection is low on sales, the 5th percentile will be more accurate, as it will only take the lowest priced sales.

Methodology

The data used in this analysis was collected by combining the information on the ez_nft_sales and fact_prices tables of the core schema of the Flow database.

• The first table provided information about the NFT sales on Flow. The 5 collections filtered are the following:

  • Speedway Motorsports RaceDay: A.329feb3ab062d289.RaceDay_NFT

  • NBA Top Shot: A.0b2a3299cc857e29.TopShot

  • NFL All Day: A.e4cf4bdc1751c65d.AllDay

  • UFC Strike: A.329feb3ab062d289.UFC_NFT

  • Genies: A.12450e4bb3b7666e.Genies

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• As some sales were performed in $FLOW, the second table was joined with the first one to correlate the metrics obtained with the $FLOW price in $USD.