Timing Games: Probabilistic backrunning and spam

A new research paper titled 'Timing Games: Probabilistic backrunning and spam,' authored by Bruno Mazorra, Christoph Schlegel, and Akaki Mamageishvili, provides a formal game-theoretic model for the costly spam wars seen in blockchain arbitrage. The core problem involves 'n' players competing to time their actions to capture an opportunity that appears randomly on a time interval, but is only observed with a delay. The winner is the player who acts fastest after the opportunity arises, but each action is costly. The authors' primary motivation is to analyze 'probabilistic backrunning' on blockchains, where arbitrage bots spam the network with transactions hoping to land one immediately after a major trade or oracle update that shifts prices.

The research characterizes the unique symmetric equilibrium of this timing game and quantifies its worst-case inefficiency, directly linking the number of actions taken to the measure of costly spam generated. This model explains the real-world phenomenon where decentralized exchanges and oracle networks are flooded with transactions from competing bots, driving up gas fees and creating network congestion for all users. The paper, available as arXiv:2602.22032, offers a mathematical foundation to understand and potentially mitigate these inefficiencies, which is a critical step for blockchain scalability and user experience. The findings could inform the design of more robust transaction ordering mechanisms or fee markets to disincentivize wasteful spam.