Burak Öz

Fei Wu, Burak Öz

Maximal Extractable Value (MEV) on high-throughput blockchains can be captured through targeted search, where bots identify opportunities off-chain and submit route-committed transactions, or through probabilistic search, where bots submit repeated attempts that resolve opportunity discovery during on-chain execution. This distinction has direct implications for spam, blockspace consumption, and protocol fee revenue. We model how ordering granularity, fee floors, and opportunity-access shocks shape competition between these architectures. Using cyclic arbitrage data on Base from June 2025 to February 2026, we develop a trace-level classifier for search architectures and show that the resulting labels correspond to distinct execution behavior. We test the model across three episodes: Flashblocks selects against broad on-chain probabilistic scanners; token-launch opportunity shocks temporarily revive probabilistic search; and higher fee floors select against probabilistic bots whose opportunity flow cannot sustain repeated attempts. In our sample, probabilistic search accounts for only 23% of arbitrage activity but produces 95% of spam and consumes 20% of Base gas. After Base's configuration changes, protocol fee revenue shifts toward successful arbitrages and away from spam, probabilistic bots pay higher priority fees, and spam consumes a smaller share of blockspace.

Burak Öz, Fei Wu, Luis Correia et al.

Decentralized block building mechanisms replace the monopoly of a single proposer with multiple builders. However, their censorship-resistance and fair-access benefits depend not only on the number of builders, but also on whether builders are geographically positioned to provide timely transaction coverage. We study this tension between builder location choice, user transaction coverage, and reward concentration by modeling decentralized block building as a stochastic coverage game. Builders choose regions, information sources emit transactions over a block construction round, and latency determines whether each transaction is received before the deadline. We show that the builder region game is an exact potential game and therefore admits a pure Nash equilibrium. We prove an asymptotically tight factor-2 Price of Anarchy bound, quantifying the price of decentralization from uncoordinated builder placement, and derive tight bounds on builder utility concentration, showing that the lowest-utility builder earns at least half of the highest-utility builder's payoff, and the utility-share HHI is at most 12.5% above the egalitarian benchmark. We complement the theory with simulations, studying the builder region game under richer latency and source environments. We find that welfare losses are most pronounced in intermediate regimes where peripheral sources are reachable and valuable, but selfish incentives still favor regions with strong access to high-value sources. We also find that geographic and utility concentration need not align: planner allocations can improve coverage by assigning builders to lower-payoff peripheral regions, while equilibrium outcomes can be more geographically concentrated but more utility-balanced. We connect our findings to protocol design and discuss future directions on location-market modeling and alternative reward-sharing rules.