Limited interactions EOA: Fewer than 10 EOA (Externally Owned Account) wallets interact as transaction senders.

Distribution of senders: Less than 50% of transaction senders have only sent one transaction, indicating that the user base does not exhibit a long tail distribution. This suggests that routers are unlikely to be used by retail investors.

Behavioral Patterns: Trading histories either cover a full 24 hours or show multiple transactions within a single block, indicating non-human behavior.

Swap Concentration: More than 75% of successful trades involve swaps.

Detected MEV Txs: More than 10% of successful trades employ an atomic MEV strategy, as detected by hildobby's heuristics 2.

We divided all Base transactions processed by routers into two groups for analysis. The comparison of recovery rates between bot-like routers and other routers is shocking: the average recovery rate for bot-like contracts is 60%, six times higher than the approximately 10% observed in other transactions.

From the above data, we can conclude that bot activities such as MEV bots and Telegram bots may be one of the main reasons for Base's high gas fees and rollback rate.

L2's single sequencer infrastructure, coupled with the lack of a public memory pool, has fostered the dominance of MEV strategies that involve a large amount of sequencer spam. These strategies have led to significant network congestion, especially on L2s that use Priority Gas Auctions (PGA), such as OP Mainnet and Base. The consequence is not only network congestion, but also wasted block space for reversing transactions and gas fees paid by MEV seekers. This situation reflects the state of Ethereum before Flashbots, with the notable exception that there is no MEV mezzanine on L2 due to the current lack of a memory pool.

How big is MEV on L2?

It is critical to gain a deeper understanding of MEV activity on L2. However, to date, there is no unified number for L2 MEV that has been verified through multiple sources and robust methods. In addition, there is a lack of real-time monitoring data similar to the work done for Ethereum (e.g. mev-inspect, libmev, eigenphi 3) to obtain L2 MEV volume and seeker profits.

Some of the L2 MEV datasets and research published to date include:

• Open source datasets built by hildobby 2 on Dune Analytics (inspiration links: Sandwich 1|Sandwich| Atomic Arb 3)

• Research paper funded by Flashbots, Quantifying MEV on Layer 2 Networks 1 by Arthur Bagourd and Luca Georges Francois, quantified MEV on Polygon, OP Mainnet, and Arbitrum using the mev-inspect implementation.

• The research paper "Rolling in the Shadows: Analyzing MEV Extraction in Layer 2 Rollups"3 by Christof Ferreira Torres, Albin Mamuti, Ben Weintraub, Cristina Nita-Rotaru, and Shweta Shinde quantifies activity and discusses novel MEV strategies for L2 that leverage the role of sorters and their L2 batch confirmation latency

In addition to the above resources, Sorella Labs2 is about to 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 classification and quantification. If you already work in this field or are interested in collaborating, please contact the Flashbots Market Research team (@tesa on Telegram: @tesa_fb)!

While further validation is needed, hildobby’s dataset on Dune Analytics is a valuable initial benchmark:

Over the past year, the six major L2s (Arbitrum, OP Atomic arbitrage MEV volume on L2 (Arbitrum, OP Mainnet, Base, Zora, Scroll, and zkSync) exceeds $3.6 billion, accounting for 1% to 6% of all DEX volume on each chain respectively. This MEV volume is mainly concentrated in Arbitrum and OP Mainnet, but has recently shifted to Base and zkSync.

Compared to atomic arbitrage volume, sandwich volume on L2 is significantly lower, in stark contrast to the situation on Ethereum, where sandwich volume is four times that of arbitrage volume. This difference is due to L2's single-sequencer setup, which essentially does not introduce a memory pool, in which case searchers will not be able to perform sandwich MEVs and observe users' transactions from the memory pool (unless there is a memory pool leak or sandwiches from a single sequencer). Instead, strategies such as atomic arbitrage, blind rollbacks, statistical arbitrage, and liquidations are the most viable options for searchers on L2.

MEV market size

How much MEV revenue is left in L2?

While it’s difficult to accurately quantify the MEV market, we can check numbers from other ecosystems that have adopted MEV solutions for size comparison:

• On Ethereum L1, MEV-boost blocks generate approximately $968 million in annual revenue for validators (estimated at $3,500 ETH); the median value of a MEV-boost block is 4x the value of a vanilla validator block.

• On Solana, the additional MEV revenue collected by validators from validator tips through Jito’s bundling service (calculated at 50,000 SOL per week) is approximately US$338 million (estimated at a SOL price of US$130). While specific figures for Base’s MEV trading volume are unknown, the market size can be estimated by analyzing the revenue of the Banana Gun Telegram Bot, one of the most active bots in the space. The bot’s trading volume on Base as an L2 is comparable to its trading volume on Solana — consistently generating over $1 million in daily trading volume, and therefore over $10,000 in daily fees per chain.

  

  Note that the market share of Banana Gun Bot on Solana and Base may be significantly different. For example, Solana has several other major Telegram bots, such as Sol Trading Bot and BonkBot, while Base may have fewer Telegram bots. Therefore, Banana Gun's sales volume does not translate into Base's total MEV revenue at its Solana revenue ratio.

  However, consider another prediction using a different metric: In March alone, the Banana Gun Telegram Bot paid out over $23 million to Ethereum builders and validators! When comparing cross-chain transaction volumes, its volume on Base actually surpassed Ethereum in the week of March 26-April 1 (as seen in the spike in the chart above), indicating that the MEV earning potential on Base is huge.

  Of course, the MEV ecosystems of Base and Ethereum are very different. Competition for MEV on Base is likely much less than on Ethereum, meaning the bot needs to bid to validators less often. However, memecoin trading bots operate primarily through blind sniping and arbitrage, which is still feasible in Base's sequencer setup.

  

  Calling for MEV attention

  Ethereum has built a complex MEV ecosystem with infrastructure tools serving participants at different levels of the supply chain. At the protocol level, MEV-boost allows validators to outsource the block building process through auctions. For searchers, bundled services provided by Ethereum's block builders (similar to Jito Labs on Solana and FastLanes on Polygon) enable searchers to propose MEV strategies with recovery protection. These services ensure that builders simulate transactions and process only those that are unrecoverable. Additionally, private RPC services like Flashbots Protect provide retail traders with a way to avoid public memory pools and the associated risk of being caught in the middle. L2 in its current form still has considerable room for progress in developing similar MEV infrastructure.

  Why should we consider MEV solutions for L2?

  Even without a memory pool, MEV still exists. MEV strategies such as statistical arbitrage (CEX-DEX arbitrage), atomic arbitrage (DEX-DEX arbitrage), and liquidations maintain market efficiency by clearing stale liquidity from AMM and lending markets.

  However, without mature MEV infrastructure like bundling services, negative externalities will occur. Without a memory pool, most MEV strategies will default to a spam strategy, resulting in:

  • an increase in the reply rate of the entire network;

  • an increase in gas fees, leading to network congestion.

  By introducing bundling services and shifting MEV competition pressure from on-chain to Sidecar, users are freed from the high gas fees of MEV robots. Seekers can also gain higher profits from recovery protection because the cost of failure can be reduced.

  For L2s that aim to have a shared sorter, most solutions today require users to submit their transactions to a public memory pool, reintroducing the "mezzanine" phenomenon. At this point, MEV protection solutions (such as sending user transactions directly to private RPCs of block builders like Flashbots Protect) can provide protection against the “mezzanine” phenomenon, or even provide MEV or priority fee refunds, thereby providing better execution and better prices for users.

  However, more complex MEV infrastructure still has some challenges. First, as the value captured by sequencers increases, the economics of search will change, causing searchers’ marginal profits to decrease over time. This, in turn, raises the question of how sustainable competitive search strategies are in the long run. We expect market forces to be at work here, with common search strategies paying sequencers most but not all of the value, and less common search strategies paying less value.

  In addition, the order flow dynamics of existing MEV infrastructure (such as Ethereum’s block construction market) are still evolving rapidly. At the time of writing, they are a significant contributor to the centralization of the block construction market and the rise of private memory pools on Ethereum L1. How to ensure a competitive and fair block-building market remains an open challenge.

  Finally, MEV solutions on L2 may also differ from those on Ethereum due to its unique properties of faster block times, cheaper block space, and relatively more centralized governance. It is unclear whether fast block times (such as Arbitrum’s 250ms blocks) are compatible with the current performance and requirements of existing MEV infrastructure. In addition, the abundant and cheap block space provided by L2 drastically changes the dynamics of search, which makes spam a more prominent problem and may require new solutions. Finally, L2 is relatively more centralized than other settings (such as Ethereum L1). In this case, it may be permissible to impose additional requirements on MEV service providers - such as requiring block builders not to cross-pollinate users - to achieve fair market outcomes.