× Welcome to frontrun me, the premier site for visualizing Ethereum gas auctions. These gas auctions are often bids by frontrunners, arbitrageurs, and other programmatic network actors that seek to exploit inefficiencies in on-chain systems, ultimately profiting miners. On this site, we monitor these behaviors on the network in real-time as these bots compete for block priority in rapid-fire all-pay auctions*, showing users and mechanism designers the potential rent-seeking economy created by orderbook inefficiencies on-chain. Timing data is sourced from a global network of 8 nodes peered deeply with Ethereum. Read our full paper!
*Modern auctions are a special kind of all-pay auction, in which the winner of the auction pays some constant percentage of their bid; they do not pay full gas, as they do not pay for execution, but they must pay for attempted execution.

WARNING: THIS IS AN ALPHA VERSION OF THE SITE WITH PRELIMINARY DATA AND KNOWN BUGS. Use at your own risk and follow @ProjectChicago_ for announcements on release and more data being added.

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Individual Real-Time Auction Data


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Note: only auctions with a single detected "winner" (mined with 2+ log events) are displayed in this view. Other auctions may contain multiple sub-auctions, as the split is heuristic.

Gas Auction #1546 - 2018-11-25 02:40:47 to 02:40:52; Start Time 1543113647.4189115

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 6.000000000 () 0xC9D81352fBdb0294b091e51d774A0652ef776D99/18998 1150000 0x8f99ff26ceccad2f58f8fc7d294e9f4c32e8e563e7706b8b13feaae49d7e22e3
4.099 130.000000000 (182.35294117647058) 0x9f8646A35db0f466aC9322e2D194cc18f209Fc75/466 90000 0x0db05d6619f4970c0b980417ac02b776d0c189832d5920f9ef5ebba3a575c8c7
5.182 18.000000000 (-151.35135135135135) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/10600 389051 0x413358e13e057b54074ac77e55aab8e4ab0f4a0369d6e0e4152e0d2c4bba23a5 6767552 6767552 / 8
5.538 9.000000001 (-66.66666665679011) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/18998 484222 0x969a377a948a7ad988cabd475f2128c5cf4797a3344b03279ff77d5050dd0330
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This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1650441.
We would also like to thank NSF CNS-1330599, CNS-1514163, CNS-1564102, and CNS-1704615, ARL W911NF-16-1-0145, and IC3 Industry Partners.
Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.