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Dynamic Rarity Score

The Meta Cricket League Collection uses a Dynamic Rarity Score (DRS) system to rank the different NFTs. Here, weightage is given to not only the image properties but also the game properties of every NFT.

How did we calculate?

MCL Player NFTs have 3 properties:
  • Visual: Each NFT looks different from the other as they all have a unique image property.
  • Player Stats: This metric is predefined for every MCL player from their respective genesis level. As their levels increase through upgrades, their stats will be boosted to predefined values.
  • Player Elements (Coming soon): Based on player upgrades and player category, owners will be given a set number of Element Upgrade Points (EUP). The user is free to assign available EUPs to one or many of his preferred players' elements, increasing in-player card performance in a particular direction.
Likewise, MCL Signed Bat NFTs have 2 properties:
  • Bat Stats: Predefined and fixed for every MCL Signed Bat based on their category. These values are static and do not change as bats cannot be leveled up.
  • Visual: Each NFT looks different from the other as they all have a unique image property.
Now, comparing values of player stats to player elements to visuals is similar to comparing apples to oranges to peaches. Similarly, this issue persists for bats when comparing bat stats to visuals.
The ranges of these properties are different. Therefore, to reach a level playing field for all, we needed to normalize them first. For this, we compressed the entire properties range to a range of 0 to 1.
Note: We used the min-max normalization algorithm to arrive at the normalized scores for different parameters.
Note: To normalize the game score for MCL Bowlers, we had to do an additional step of calculations. This is because the bowler players have scores for only 1 or 3 traits. Hence we only had to consider the traits with non-zero scores.
Once we get the Normalized Image Score (NIS) - Visual, Normalized Stats Score (NSS) - Player Stats, and Normalized Element Score (NES*) - Player Elements, for the MCL Players, multiply them with their respective weighted factors (W1, W2, and W3), and add the three for the final score, as seen below.
Similarly, for MCL Signed Bats, we get the Normalized Stats Score (NSS) - Bat Stats and Normalized Image Score (NIS) - Visual, multiply them with their respective weighted factors (W1 and W2), and add the two for the final score, as seen below.
With this, we reach the final score for each NFT. Additionally, as MCL Player NFTs level up in-game, the scores will update to reflect the new changes.
Note: For MCL Players, in the initial beta, we are using weighted factors for Normalized Image Score (NIS) and Normalized Stats Score (NSS) at a 50%-50% weightage.
Note: For Meta Cricket League Bats, we used a 75% weighted factor for Normalized Image Score (NIS), and a 25% weighted factor for Normalized Stats Score (NSS) as MCL Bats have non-upgradable game stats.
To check the rarity score: https://www.guardianlink.io/meta-cricket-player​

What does this mean?

A dynamic rarity scoring system allows users to enhance the rarity of their NFTs by reflecting the time and effort invested to progress in the game.
This one-of-a-kind system ensures that each time you level up your MCL Player NFTs in-game, you also improve its rarity score and overall ranking in marketplace.
Users can also use this dynamic scoring pattern to find the rarest and most impactful NFTs, one that will benefit them both in the game and in the marketplace.
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Disclaimer: The above-explained concept is subject to change. However, the process will have only a positive impact on MCL and its users.