Project Name: NFT Smash
Project Track: NFT
Team Name: NFT Smash
Team Member(s): 4 - @slum @yashmadhwal @Osoi @Yura
DevPost URL: NFT Smash
Project Goal: NFT Smash is a market-centric and machine learning-enabled NFT rarity meter: the greater the rarity of an NFT within a collection, the greater the value in TRX.
Project Info: People trade thousands of NFT daily. The NFT prices are expressed in cryptocurrency, and it is volatile. As the interest in the NFTs changes, their prices vary with time too. Is there an immanent meter to order NFTs by their value? Within a single collection, a vector of features–traits–characterizes NFT. People construct rarity meters based on the assumed value of the trait vector rarity. But this process lacks formalism. In this project, we formulate the optimal rarity meter problem and provide a pipeline for optimal rarity meter design. A proposed tournament score function is an essential part of the construction.
We computed the rarity meter for the BAYC and MAYC NFT collections (the hottest collection by trade volume): the greater the rarity of an NFT within a collection, the greater the value in TRX, based on historical data. You can check the rarity by NFT id. We also prepared a tiny NFT Smash game for you to examine yourself on how you feel NFT market!
Project Website: https://tronnftmash.web.app/
Project Test Instructions:
Visit the application: NFT-SMASH
Click on sMash It Now! examine yourself on how you feel NFT market!
Read the rules.
Select rarer NFT from five pairs.
Get the game summary!
Click Search My NFT to check NFT rarity.
Type NFT id and select the collection out of BAYC and MAYC and click GET
Here is an NFT picture followed by its rarity score (the greater the rarity of an NFT within a collection, the greater the value) and rank (the number of NFTs in the collection with a greater or equal score).
Project Details: NFT Smash Walkthrough Video
Project Milestones: 1. Collect data (done).
2. Compute the rarity score and fit it to the market data (done).
3. Implement “search my NFT” functionality (done).
4. Implement the “NFT Smesh” game (done).
5. More collections supported! (in progress)
6. Even more collections are supported! (blocked)
7. ALL collections supported)! (blocked)
8. Real-time trade data and historical rarity fluctuations. (in progress)
what a wonderful nft project, wanna use it so much honey
Cool project and game!
Rarity[dot]tools provides rarity estimates. You claim that your approach is different to it. Any examples?
Nice question, thank you!
Rarity Tools have a rarity estimate based on traits only with no relation to trade data. Their rarity is a sum of inverse trait probabilities. We use several scores like this as a starting point and then fit the weights for these scores to the trade data in our resulting NFT Smash rarity.
We prepared a few examples of NFT pairs. In each example, the left NFT is rarer by our meter and the right one is rarer by the Rarity Tools formula. You can decide if our choice is better, but the fact is that (based on historical trade data) the market values clothes and hats. And NFT Smash is consistent with the market.
Data is very important in decision making.
The value of an NFT should be driven by its utility it provides and not by the traits it possesses.
If an NFT possesses a trait that makes it super rare and has no use case, demand is shattered. So kindly consider adjusting the meter to also have NFTs with actual utility and actual inflow of revenue to holders. In that way when i am spending on an NFT, i know it will be beneficial in the long run.
Thank you, I see. Any math details of your approach? Formulas?
We considered two collections–BAYC and MAYC–based on their 30 days trade volume on Tron. So they are popular. As of their utility, creators states some. But all NFTs are equal in rights within a single collection: access to the club. But somehow BAYC NFTs have a different price on market.
NFTs in some collections can have utility like breeding, access to DAO or club. And our approach allows either to add it as an additional trait or within existing traits. But good news that we can fit the resulting score to the trade data. This means that we don’t provide an expert-driven information as a hard rule, but rather extract the knowledge of the real market value from the market–the only true source for value.
Some people have noticed that some teams are faking the trading volume of their collection, buying and selling to themselves with 2 or more wallets. This also artificially drives the prices up. So is the market really a “true source of value” and how to prevent those faked data’s from being taken into account?
Thank you for the response, but as @fabsltsa said, people fake it to make it, how will the system be designed to catch those fraudulent act.
what a lovely nft project, u got 1 vote kiddos
Yes, we have some formulas.
Sorry, We are not sure how to transfer formulas in the correct way to a forum. So, We decided to write in a pdf and attach it.
KRAMER_for_TRON_Forum.pdf (192.0 KB)
Ohh! What a wonderful question! For sure, it’ll be interesting to research it in the future. But let us give a preliminary answer now:
First, our models are quite robust as they are linear with kernel smoothing and logarithm of price. So they should be non-sensitive to such outliers.
Second, collection creators charge fees for transfers. In the case of BAYC on TRON, it is 2.5%. So such faking is costly.
@Nana66419, here is the answer.
Faking is costly unless it’s done by or with the team. I’ve seen a printscreen of one of those copy pasted projects telegram group and the team was clearly asking to their holders to do so in order to boost the volume and get verified faster on apenft. The fees were sent back to those nft holders.
I have to admit that I didn’t really understand the first part of the answer
Interesting insight! Maybe, it is even possible to trace these events. But as a separate project.
KRAMER_for_TRON_Forum.pdf (192.0 KB)
As per the first part, we refer to our model and the pdf prepared as a reply to @AAPecherkin. We also attach it to the current reply. Long story short: If the pump is successful and changed the market in a long term, we will take it into account and why shouldn’t we? If the pump failed, the model will not pay much attention to it.
The rarity adds much value to an NFT but getting it during mint is just by luck