Optimistic MEV (Maximal Extractable Value)

Optimistic MEV refers to a class of speculative, on-chain, high-frequency arbitrage strategies that have become dominant in Ethereum’s Layer 2 (L2) rollups and fast-finality blockchains. Relying on inexpensive blockspace, optimistic execution models, and incentive structures unique to optimistic rollups, this type of MEV (Maximal Extractable Value) is characterized by its lack of off-chain pre-verification, frequent failure or null-action transactions, and distinctive impacts on network congestion and security.

1. Definition and Conceptual Foundations

Optimistic MEV describes extraction strategies in which:

• The core detection logic (search for arbitrage, parameter selection, pathfinding) is executed within on-chain smart contracts.
• Bots submit transactions “optimistically”—without off-chain verification that a profitable arbitrage or MEV opportunity actually exists at the time of execution.
• Most such attempts either fail to produce profit or do not execute any economic action at all (e.g., the contract decides not to trade after probing live state).

This stands in contrast to traditional L1 MEV extraction, where off-chain search and guaranteed-profitable, atomic bundles are the norm. On rollups and L2s, the dramatic reduction in transaction costs and increased blockspace prompt bots to “probe” by high-frequency contract calls, making speculative MEV both technically and economically rational.

2. Mechanisms and Economic Models

The prevalence and structure of optimistic MEV result from the interplay of L2 economic primitives and transaction ordering mechanisms. On FCFS (First-Come, First-Served) private-mempool rollups, the strategy becomes:

• Splitting a large arbitrage position into many small transactions, each acting as an independent “bet” on opportunity arrival before competitors (Gogol et al., 2 Jun 2025 ).
• Using smart contracts to initiate on-chain state queries (e.g., calling getReserves or slot0() on AMM pools), compute trade parameters in situ, and perform swaps only if a profitable opportunity materializes (Solmaz et al., 17 Jun 2025 ).

Formally, if swapping $q$ units in a constant product AMM (with reserves $(x,y)$ and fee $f$), the swap output is: $\Delta y(q) = \frac{y(1-f)q}{x + (1-f)q}$ The expected profit from a transaction of chunk $q$ is: $\pi(q) = p(q)[\Delta y(q) - P_c q] - (1-p(q))[P_c q + \phi] - c_g$ where $p(q)$ is the probability the swap succeeds, $P_c$ is the CEX price, $\phi$ is the penalty on failed swaps, and $c_g$ is gas/latency cost. The optimal strategy, in the fast-finality, ultra-low-fee L2 context, is to maximize profit by submitting many small swaps rather than a single large transaction.

3. Empirical Prevalence and Network Patterns

Empirical analyses of Ethereum L2s such as Arbitrum, Base, and Optimism in 2025 show that optimistic MEV dominates on-chain activity in terms of gas usage, though not transaction fees (Solmaz et al., 17 Jun 2025 ). Key findings include:

• Optimistic MEV accounts for 51–55% of total on-chain gas usage on Base and Optimism, and 7% on Arbitrum.
• The majority of gas is spent not on successful swaps, but on “interaction probes”—on-chain computations searching for arbitrage that rarely lead to action.
• Success rates for actual arbitrage are exceedingly low on OP-Stack rollups (~1%), far lower than on Arbitrum (where designs force more failed attempts to revert and a higher percentage of successful trades).
• On fast rollups (e.g., Arbitrum, ZKsync), reverted MEV transactions (failures) cluster at the very start of each block, indicating an intense latency race rather than a price-based priority mechanism (Gogol et al., 2 Jun 2025 ).

The March 2024 Dencun upgrade, which lowered L2 fees via proto-danksharding, further intensified these patterns: revert rates for swap transactions spiked above 10–20%, blocks became persistently full, and duplicated spam transactions by MEV bots increased.

4. Security, Incentives, and the Verifier's Dilemma

Optimistic rollups fundamentally rely on “optimistic” assumptions: aggregators (sequencers) are responsible for batching and publishing blocks, but their work is accepted as valid unless a validator actively challenges fraud within a set window (Landis, 2023 ). In theory, the threat of slashing and rewards for challenging should create a Nash equilibrium where aggregators act honestly, and validators challenge only when appropriate.

However, the introduction of non-trivial search costs for validators (required to detect fraud) breaks this model:

• Validators act rationally and may opt not to verify blocks if expected rewards, probability of success, or compensation for their effort is insufficient.
• Aggregators, recognizing the probability of challenge is less than 1, may occasionally and strategically insert fraudulent or MEV-maximizing transactions with reduced risk.
• This fundamental “incentive non-compatibility” enables a structural window for Optimistic MEV: value-extractive behavior pursued by aggregators betting that monitoring is undersupplied.

The model formalizes the breakdown: $g = 1 - \frac{s_A}{b s_A + b z}$ where $g$ is the probability validators challenge blindly, $b$ probability of not searching, $s_A$ aggregator stake, and $z$ possible value from fraud or MEV.

A direct implication is that full security would require random checking of almost every block, especially if possible fraud ($z$) greatly exceeds the slashing risk ($s_A$), which is operationally and economically infeasible (Landis, 2023 ).

5. Detection, Code Reuse, and Transaction Profiling

Detection of optimistic MEV is performed through transaction-level analysis and contract inspection (Solmaz et al., 17 Jun 2025 ):

• Contracts engaging in on-chain cyclic arbitrage are identified via multi-stage pipelines that extract atomic swap cycles, classify DEX/router interactions, and exclude aggregator/router addresses.
• On OP-Stack L2s, a high degree of code cloning is evident: the same contract bytecode is deployed repeatedly, often with only minimal calldata (sometimes a fixed 1–2 byte payload), as crucial opportunity search and parameterization are conducted internally, not off-chain.
• Manual validation further separates genuine MEV bots from false positives, and rich labeling libraries per rollup standardize classification of reverted and successful transactions.

6. Network Congestion, Fee Disparities, and Economic Impacts

Despite making up more than half of gas usage on Base and Optimism, optimistic MEV transactions pay only a minority share of total fees (23% on Base, 17% on Optimism) (Solmaz et al., 17 Jun 2025 ). This is possible because:

• Such transactions often use lower-than-average gas prices.
• Blocks are kept full by low-value, high-frequency, speculative probing, crowding out organic (user) demand for blockspace.
• Priority fee auction mechanisms (PFAs) are routinely bypassed or ignored by MEV bots, which instead submit duplicated, identical trades in order to maximize inclusion probability, sidelining fee-based ordering (Gogol et al., 2 Jun 2025 ).
• On L1, by contrast, high fees make this kind of speculative probing uneconomical; nearly all opportunistic activity is precomputed and guaranteed profitable before submission.

The elastic blockspace demand of MEV bots further means that protocol upgrades (such as Dencun’s fee reduction) serve to increase, not mitigate, congestion by optimistic MEV.

7. Drivers and Network-Level Differences

Regression analyses link optimistic MEV activity on rollups to market and network parameters: $\Delta y_t = \beta_0 + \beta_1 \cdot \Delta \text{Price}_t + \beta_2 \cdot \Delta \text{Volatility}_t + \beta_3 \cdot \Delta \text{RetailTxs}_t + \beta_4 \cdot \Delta \text{RetailAggFrac}_t + \epsilon_t$ Key findings include:

• Cryptoasset volatility and retail trading activity are strong positive correlates of MEV probing activity (particularly on OP-Stack rollups).
• Use of DEX aggregators typically has a negative effect, as they more efficiently route trades and suppress basic arbitrage opportunities—though Base shows anomalies.
• Block production time, transaction ordering mechanism (e.g., Priority Gas Auctions vs. FCFS), and minimum fee parameters strongly affect the proportion and nature of optimistic MEV.

A comparison across networks highlights: | Aspect | Base/Optimism (OP-Stack) | Arbitrum (FCFS) | L1 | |-------------------------------------|-------------------------------|--------------------------------------|---------------------| | Optimistic MEV Gas Share | 51-55% | 7% | Negligible | | Dominant Gas Usage | Probing/interactions | Executed swaps | User trades | | Success Rate | <2% | 77% (non-reverts) | N/A | | Code Cloning | High | Low | N/A | | Fee Disparity | Large | Smaller | N/A |

8. Mitigations and Protocol-Level Responses

To address the security risks and inefficiencies associated with Optimistic MEV, the literature details several possible mitigation strategies within optimistic rollup economics (Landis, 2023 ):

• Protocol-level random block checks: enforcing pseudo-random validation of blocks to increase the expected cost and risk to aggregators contemplating fraud or MEV extraction. The efficacy, however, is limited for large attack values since $p \to 1$ as $z \gg s_A$.
• Direct compensation or “Easter egg” rewards for validators: incentivizing thorough checking even in the absence of detected fraud by providing protocol-subsidized non-fraud rewards.
• Designing deliberate “mistake” blocks to keep validators engaged, though this introduces other game-theoretic complexities and cost requirements.
• Adjusting block production and fee parameters (e.g., increasing minimum transaction costs, enforcing more efficient ordering) to reduce spam-based speculative probing.

A plausible implication is that certain forms of protocol-level MEV capture, such as execution ticketing and transparent MEV futures markets, may ultimately be required to align incentives, reduce waste, and improve equity—though these mechanisms introduce their own design and market risks (Burian, 5 Mar 2024 ).

9. Broader Consequences and Future Directions

Optimistic MEV demonstrates that blockspace demand on L2s is not inherently user-driven, but rapidly elastic to formal or latent MEV opportunities as transaction costs drop. This has several consequences:

• L2 scalability gains may be illusory if MEV bots, rather than users, consistently saturate available capacity.
• The structure and security of optimistic rollups cannot be treated as cryptoeconomically robust unless validator incentive misalignments are addressed, since rational actors will continue to extract unseen MEV so long as the probability of detection and cost of fraud remain low.
• Design variations across rollups—ordering mechanisms, fee structure, and minimum cost—result in markedly different MEV footprints and network congestion profiles.

Optimistic MEV will remain a central factor in the economics of Ethereum and its L2s so long as core incentive and network design parameters privilege speculative, on-chain probing by economically rational actors. As the protocol community considers new approaches to MEV capture (e.g., execution tickets, direct protocol auctions), understanding and controlling for the dynamics of optimistic MEV is critical for network security, efficiency, and fairness.