In-depth analysis: How big is the scale of MEV at L2?

Orijinal yazar: sui 14

Original translation: Ladyfinger, BlockBeats

Editors Note: This article deeply analyzes the impact of the Dencun upgrade on the Ethereum L2 network, reveals the positive results of the upgraded L2 network in reducing transaction costs, increasing user activity and asset inflows, and points out the negative effects such as network congestion and high rollback rate caused by MEV activities. The article calls on the community to pay attention and jointly develop MEV solutions that adapt to L2 characteristics to promote the healthy gelişim of the Ethereum ecosystem.

giriiş

In this post, we yapay zekam to provide a data-driven overview of the current state of L2. We monitor the importance of the Dencun upgrade’s gas fee reduction for L2 in March, examine how activity on these networks has evolved, and highlight emerging challenges driven by MEV activity. Additionally, we discuss potential barriers to developing MEV tools and solutions for L2.

The good: L2 adoption after Dencun upgrade

Gas costs dropped 10 times

Ethereum L2 gas fees consist of two parts: the cost of executing transactions on L2, and the cost of submitting batches of transactions to Ethereum L1. Different L2 gas fee structures and sorting rules vary depending on their development stage and design chobuzs. For example, Arbitrum operates on a first-come, first-served (FCFS) basis, and transactions are processed in the order they are received. In contrast, Optimism (OP Mainnet) and Base as part of the OP Stack use a priority gas auction (PGA) model that combines L2 base fees and priority fees. Users can choose to pay higher priority fees to be included faster and appear earlier in the block. Understanding the fee structure is critical to understanding the growth of the ecosystem and the dynamics of MEV.

Historically, Ethereum L1 fees made up the majority of the total fees users had to pay when transacting on L2, accounting for over 80% of the cost, as shown by the black bars in the figure below. However, after the March 14 Dencun upgrade, L2 switched from using calldata to a more economical method, so-called blobs 1, for submitting batches to L1. This temporary storage includes its own gas auction, consisting of a blob base fee and a priority fee.

Data Sources

Since Dencun, there has been a significant reduction in the fees paid by L2 to L1 – the chart shows a significant change in the gas cost breakdown of the OP Stack chain, with L1 costs plummeting from 90% to just 1%, while L2 costs now account for 99% of the total costs. This shift has led to an overall drop of about ten times in average total gas fees on L2, for example, the average gas fee on OP Mainnet has plummeted from about $0.50 per transaction to $0.05.

Data Sources

Activity surges on L2

After the cost reduction, there has been a clear increase in activity and usage on L2, which can be seen from the surge in L2 gas fees in the figure above. Notably, on March 26, Bases average gas fee exceeded the highest level before the upgrade. In order to accommodate more transactions and reduce network congestion, Base increased its gas target starting on March 26 and has made several adjustments since then.

The chart below highlights the number of daily transactions on L2, showing significant growth for networks like Arbitrum, Base, and OP Mainnet. In particular, Base has seen a fourfold increase in daily transaction volume, now processing approximately 2 million transactions per day.

Data Sources

While it’s difficult to determine whether this is the result of organic participation or the result of incentive schemes and Sybil activity — since late last year, with improved market conditions and the onset of the memecoin season sparked by WIF on Solana, active addresses and DEX volumes on all major L2s have clearly increased post-EIP-4844 upgrades, particularly on Base and Arbitrum.

Assets flowing to L2

With the improvement of market conditions and the arrival of the memecoin season triggered by WIF on Solana, TVL on L2 has continued to rise since the end of last year. Notably, Base has become the fastest growing chain, and recently surpassed OP Mainnet in total TVL.

Data Sources

Since the beginning of March, Base has seen inflows of around $1.5 billion in USDC, part of which is Coinbase moving customer and corporate funds onto Base. According to Artemis data for 11 major bridges since January 2024, there has been $14 billion in outflows from Ethereum to the main L2s. Arbitrum leads with around $7 billion, followed by zkSync, Base, and OP Mainnet. Further data from Debridge Finance, a cross-chain bridge widely used in EVM chains and Solana, confirms that Arbitrum and Base are the top recipients of all outflows.

Data Sources

The bad: As gas fees go down, hidden MEV activity increases

As we further inspected the transactions, we noticed that bot transaction activity was driving up gas fees and rollback rates on L2. We will explore this issue more fully in the next section by using Base’s statistics for a case study, highlighting the impact of cheaper gas on L2 after the Dencun upgrade.

Dencun’s upgraded L2: like Ethereum without Flashbots, but without the transaction pool

Network congestion

The challenges began to emerge on March 26, when the average daily gas fee of the Base network briefly surged, surpassing the level before the Dencun upgrade. However, on June 3, Base raised its gas target to 7.5M gas/second, compared to 2.5M gas/second during the Dencun upgrade, which brought the average gas cost back down to about 5 cents.

On the Base network, the contracts that consume the most gas include Telegram exchanges BotSigma and Banana Gun, as well as digital wallets and DEXs such as Bitget and Uniswap. In addition, there are many unmarked contracts involved in activities such as token minting, meme coin trading, and atomic arbitrage. These contracts are the top contracts on the Base network ranked by gas fee payment.

By comparing the behavior of popular Telegram Bots, such as BananaGun, it is clear that the gas fees incurred by them are much higher than ordinary transactions. After the Dencun upgrade, users using the BananaGun Telegram bot saw gas prices spike to a peak of 30 Gwei when performing transactions on the Base network. Although this rate has since stabilized at around 3 Gwei, it is still 43 times the gas fee required for other transactions.

Daily gas prices on Base, comparison of Banana Gun transactions with other transactions

When analyzing the average monthly gas price paid by all major DEX trading bots on the Base network and comparing it to non-Telegram bot transactions (represented by the black bar), it is clear that users using trading bots incur significantly higher gas costs. Below is a comparison of monthly gas prices on the Base network, showing the difference between all Telegram bots and other transactions.

Data Sources

High rollback rate surges

The rollback rate of transactions in a blockchain network is an important indicator of its health. We noticed an increase in rollback rates after the Dencun upgrade, especially on L2 networks such as Base, Arbitrum, and OP Mainnet. Currently, the rollback rate of Ethereum Mainnet is about 2%, while the rollback rates of Binance Smart Chain and Polygon are between 5-6%. Before the Dencun upgrade, the rollback rate of Base also remained at about 2%, but then it rose sharply to about 15%, reaching a peak of 30% on April 4. At the same time, Arbitrum and OP Mainnet have also seen periodic surges in transaction failure rates, which fluctuate between 10% and 20%.

Cross-chain transaction rollback rate

After further analysis, we found that the high rollback rate on the L2 network does not always represent the actual experience of ordinary users. Instead, these rollbacks are likely caused by MEV bots. By adopting the following heuristic method (Query 2), we identified a group of router contracts that exhibited bot-like behavior – they showed a high rollback rate when executing MEV withdrawal transactions:

Since Dencun was upgraded,

• Active Router: This contract has processed more than 1000 transactions.

• Limited Interaction EOA: Fewer than 10 EOA (Externally Owned Account) wallets have interacted as a transaction sender.

• Sender distribution: Less than 50% of transaction senders only sent one transaction, indicating that the user population does not exhibit a long-tail distribution. This suggests that the router is unlikely to be used by retail users.

• Behavioral patterns: Transaction history covering exactly 24 hours or showing multiple transactions within a single block, indicating non-human behavior.

• Exchange Concentration: More than 75% of successful transactions involve an exchange.

• Detected MEV transactions: More than 10% of successful transactions used the atomic MEV strategy, as detected by hildobbys heuristic.

Using these criteria, we detected 51 routers on Base, which likely represents a conservative lower bound estimate of bot activity on Base.

We divided all transactions processed by routers on the Base network into two groups and conducted a comparative analysis. The results show that robot-like routers have significantly different rollback rates compared to other transactions: robot-like contracts have an average rollback rate of 60%, which is six times the approximately 10% observed for other transactions.

Daily rollback rate on Base, by Bot, similar contracts and other transactions

Based on the above data, we can infer that automated trading activities such as MEV robots and Telegram robots are likely to be one of the main reasons for high gas fees and high rollback rates on the Base network.

The single sequencer architecture of L2, combined with the lack of a public transaction pool, has fostered a large number of MEV strategies that exploit the sequencer, which have become the main cause of network congestion. This congestion is especially evident on L2 networks that use the priority gas auction (PGA) mechanism, such as OP Mainnet and Base. The result is not only congestion in the network, but also a large amount of block space and gas fees wasted due to rolled back transactions and MEV seeker activity. This is similar to the situation on Ethereum before the emergence of Flashbots, except that due to the current lack of transaction pools on L2, there is no sandwich MEV phenomenon.

How big is the scale of MEV on L2?

Understanding MEV activity on L2 networks is critical to assessing its impact. However, there is no widely accepted number for L2 MEV data that is verified through multiple sources and reliable methods. In addition, compared to the Ethereum mainnet, L2 lacks real-time monitoring data provided by tools such as mev-inspect, libmev, and eigenphi, which are critical to measuring the total amount of MEV and miners profits.

Some L2 MEV datasets and studies published so far include:

• Open source datasets built by hildobby on Dune Analytics (inspiration links: Sandwich | Sandwich | Atomic Arbitrage)

• A research paper by Arthur Bagourd and Luca Georges Francois titled Quantifying MEV On Layer 2 Networks quantifies MEV on Polygon, OP Mainnet, and Arbitrum using the mev-inspect implementation. This research was funded by Flashbots.

• The research paper, “Rolling in the Shadows: Analyzing the Extraction of MEV Across Layer-2 Rollups,” by Christof Ferreira Torres, Albin Mamuti, Ben Weintraub, Cristina Nita-Rotaru, and Shweta Shinde, quantifies the activity and discusses novel MEV strategies on L2 that exploit the sequencer role and its L2 batch confirmation latency.

In addition to the above resources, Sorella Labs will soon release their MEV data indexer tool Brontes, which will be an open source repository that can be used for Ethereum mainnet and L2. Flashbots and the Uniswap Foundation are seeking grants to expand L2 MEV taxonomy and quantification. If you have worked in this area or are interested in collaborating, please contact the Flashbots market research team.

Although further validation is needed, the dataset published by hildobby on Dune Analytics provides a valuable initial reference standard.

Atomic arbitrage volume on L2 using the hildobby dataset

Data Sources

In the past year, the atomic arbitrage MEV trading volume on six major L2s, including Arbitrum, OP Mainnet, Base, Zora, Scroll, and zkSync, exceeded $36 billion, accounting for 1% to 6% of all decentralized exchange (DEX) trading volume on each chain. These MEV trading volumes were initially concentrated on Arbitrum and OP Mainnet, but have recently gradually shifted to Base and zkSync.

Compared to atomic arbitrage volume, sandwich attack volume on L2 networks is significantly lower, in stark contrast to Ethereum, where sandwich attack volume is four times that of atomic arbitrage. This difference is mainly due to the L2 networks single sequencer setup and no transaction pool, which limits the ability of searchers to perform sandwich MEVs using user transactions in the transaction pool unless there is a transaction pool data leak or a sandwich attack initiated by a single sequencer. Therefore, on L2, atomic arbitrage, blind backtracking, statistical arbitrage, and liquidation become more viable strategies for searchers.

Data Sources

Ethereum MEV volume breakdown

Measuring how much MEV revenue is left on L2 of the MEV market?

While it’s difficult to precisely quantify the MEV market, we can examine numbers from other ecosystems with MEV solutions for size comparison:

On Ethereum L1, annual validator revenue from MEV-boost blocks is approximately $96.8 million (estimated based on a $3,500/ETH price); the median value of a MEV-boost block is 4x the value of a normal validator block.

Block reward distribution for normal blocks and MEV-boost blocks

On Solana, the additional MEV revenue that validators collect from validator tips through Jito’s bundling service is estimated to be approximately $338 million based on 50,000 SOL per week (estimated at a price of $130/SOL).

Daily tips earned through Jito Bundles, by Authenticator and Jito Labs

While the exact total MEV volume of the Base network has not yet been announced, we can estimate the market size by observing the revenue of the Banana Gun Telegram Bot, one of the most active players in the market. Banana Gun has roughly the same trading volume on Base’s L2 network and Solana, each chain bringing in more than $1 million in daily trading volume, equivalent to more than $10,000 in transaction fees per chain per day.

Banana Gun Telegram Bot, cross-chain volume and costs

Please note that the market share of Banana Gun Bot on Solana may be significantly different from that of Base. For example, there are several other major Telegram Bots on the Solana platform, such as Sol Trading Bot and BonkBot, while Base may support fewer Telegram Bots. Therefore, the trading volume and MEV revenue ratio of Banana Gun on Solana cannot be simply used to directly estimate the total MEV revenue on Base.

However, using another forecasting method, we can see different results: in March, the Banana Gun Telegram Bot paid more than $23 million to Ethereum block builders and validators. In particular, in the week of March 26 to April 1, Banana Guns transaction volume on Base actually exceeded that of Ethereum, as shown by the peak in the chart, which suggests that the Base network has huge MEV revenue potential. This cross-chain transaction volume comparison reveals Bases growth prospects in MEV.

Of course, there are significant differences between Base and Ethereum in terms of the MEV ecosystem. Compared to Ethereum, the competition for MEV on Base may be less intense, which may result in lower fees for bots to pay when bidding to validators. Nevertheless, meme coin trading bots that mainly rely on blind sniping and arbitrage mechanisms are still viable under Bases sequencer architecture.

Banana Gun Telegram Bot MEV income paid by users to validators

Focus on MEV issues in L2 networks

Ethereum has formed a mature MEV ecosystem, equipped with infrastructure tools that serve participants at all levels of the supply chain. At the protocol level, MEV-boost allows validators to outsource block building tasks through auctions. For searchers, bundled services provided by Ethereum block builders – similar to Solanas Jito Labs and Polygons FastLanes – enable them to implement MEV strategies that include rollback protection. These services ensure that block builders simulate transactions and only execute those that are determined not to be rolled back. In addition, private RPC services like Flashbots Protect provide ordinary users with a way to bypass public transaction pools and their potential risks. However, the current L2 network still has a lot of room for improvement in developing MEV infrastructure comparable to this.

Why should we pay attention to MEV strategies and solutions for L2 networks?

The MEV phenomenon persists in an environment lacking trading pools and plays a key role in maintaining market efficiency, especially by executing strategies such as statistical arbitrage, atomic arbitrage, and liquidation to liquidate liquidity in outdated AMMs and lending markets.

However, the lack of mature MEV infrastructure, such as bundling services, may lead to some negative consequences. In the absence of a trading pool, many MEV strategies may degenerate into spam strategies, which will lead to:

• Increased network rollback rate;

• As a result, network congestion increased.

By implementing bundled services, the focus of MEV competition is shifted from the main chain to the auxiliary chain, which can effectively reduce the high gas fee burden faced by users due to MEV robot competition. At the same time, searchers can enjoy higher returns due to rollback protection, reducing the risk cost of failure.

For L2 networks that use a shared sequencer, current mainstream solutions often require users to publish transactions to a public transaction pool, which may lead to the recurrence of sandwich attacks. In this case, MEV protection tools like Flashbots Protect are particularly important. They can not only protect users from the threat of sandwich attacks, but may also provide refunds for MEV or priority fees, ensuring that users get better transaction execution and more favorable prices.

The development of complex MEV infrastructure faces several unresolved challenges. First, as more value flows to sequencers, searchers’ revenue patterns change over time, potentially reducing marginal profits. This change may raise questions about the sustainability of highly competitive search strategies in the long run. We expect market mechanisms to moderate this phenomenon, such that common search strategies will pay a larger proportion, but not all, of their value to sequencers, while less common strategies will pay less.

Additionally, existing MEV infrastructure, such as Ethereum’s block construction market, is experiencing rapidly evolving order flow dynamics. To date, these factors have been the primary drivers of the trend toward block construction market centralization and the rise of private trading pools on Ethereum L1. Ensuring that the block construction market remains competitive and fair remains an issue that needs to be addressed.

Finally, the MEV solution for L2 networks may need to be different from the current Ethereum mechanism, mainly due to the unique characteristics of L2: such as shorter block generation time, lower-cost block space, and relatively centralized governance structure. For example, Arbitrums block time is only 250 milliseconds, and it is not yet known whether such a fast block rate is compatible with the existing MEV infrastructure. At the same time, the ample and economical block space provided by L2 has greatly changed the landscape of transaction search, making the spam problem more serious and urgently needing new solutions. In addition, compared with other environments such as Ethereum L1, L2s governance is more centralized, which may allow additional requirements for MEV service providers, such as requiring block builders to avoid sandwich attacks on users to ensure market fairness.

This article is sourced from the internet: In-depth analysis: How big is the scale of MEV at L2?

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