Methodology

This article has 6 part. Overview and a little bit explain(1), NFTs(2), Transactions(3), Swap(4), TVL(5), conclusion(6), and Codes(7). part 2 and 3 has been made with Flipside tool, but part 4 and 5 has been made with defilama data. It was really hard for me to work with defilamas' API(untidy and nested json), so i made part 3 with some screenshot of defilama website, but i made part 4 with defilama(data in csv form) and Altair(visualization). As it was impossible to import visualization in velocity, i made part 4 with screenshot, too. All screenshots have been made and uploaded in Feb.2 .

Here, i explain about metrics that i used for this article and reasons that i chosed them, and at the end of the part 7, i put the codes of visualizations of part 5(TVLs). All codes are in Python language and you can fine the csv file of TVLs in defilama official page

What are we gonna do in this article, is to understand the future of L2s in 2023. Of course im not nostrodamous and my thought could be wrong.

NFTs

i chosed some metrics about NFTs? Well, in the recent bullrun we saw a great hype in world of NFTs. Lot's of big blockchain games like axie, use NFTs to reward their users and im seeing that event protocols use NFTs to reward their users. So that's why I focused on NFT trading in each blockchain. I analyzed daily volume, cumulative volume, daily transactions and daily sellers of NFTs in each blockchain. For polygon I analyzed Opensea, For Optimism I analyzed Quixotic and opensea, and for Arbittrum I analyzed Trove and opensea. These marketplaces are well-known marketplaces in each blockchain.

Transactions

Why transactions? We can understand a lot about blockchains from their transactions. Transaction part has been dadecated into two sections. First sections : metrics like daily count of transactions, daily count of users, and daily generated fee. Second section : Monthly count of transactions and average spended fee per transaction,and generated fee per user and count of transaction per user, both in monthly timeframe. These metrics tell us more about L2s.

Swap

Based on data of defilama, we understand more about swap volume of each blockchain; which make it easier for us to compare them with each other.

TVL

This part is based on data of defilima, too. In this part we check TVL of each blockchain.

What L2s have been considered for this article?

Arbitrum, Optimism, and polygon. All of them are great, but polygon is more popular between users than Optimism and Arbitrum.