× 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 #1102 - 2018-10-20 00:05:28 to 00:05:56; Start Time 1539993928.9055307

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 14.000000000 () 0xeB54F65775e6A2A42e243823D86486A64Fd1f0d6/2851 600000 0x8e7a72201defe3db09b5a6a695b0ef1df82e92d9edfa4208a8c05b80f8825946
21.569 18.000000000 (25.0) 0x47169f78750Be1e6ec2DEb2974458ac4F8751714/6916 21000 0x3c98510ad8aef5e7b06d4463979d2de674175a4afe0e10633ad81066f9066ec5
22.240 18.000000000 (0.0) 0x2bF90726636273b910AB0eA72cc3A2598AeBF1f2/1815 21000 0x90cb73fd2f0996a17fb49e752ff374bb82c2b6d938cd77546e4a1d7bdde34782
23.855 6.324999999 (-95.9917780183347) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/24109 22000 0x6090478ef808649b10c7c7098b4f19ab40e30634f512376d8308f1d9b9221a2f
24.307 113.000000000 (178.7974020563905) 0x89aaFA3488b07B2E88d06249e53c0506394433f4/1221 7600027 0x0e176083b0dbdc4d5bf98b8c3d7cbce6c1f89846ef0bf880964f45dc01922d6e
24.534 18.000000000 (-145.03816793893128) 0xC1A065a2d29995692735c82d228B63Df1732030E/2075 21000 0x7db8c87063cd20283e42b714a387bcc563f12ab111df34f9f1f86e65a4577a0d
25.195 18.000000000 (0.0) 0xeB54F65775e6A2A42e243823D86486A64Fd1f0d6/2851 21000 0x42631a0839fe7aee7a307fb340fbf55a56b35213eaaf6793ce571ee6fb2f0419
25.347 5.500000000 (-106.38297872340425) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/8052 779730 0x1b362e7f82e8590143200e10e8fa0ac33e7b7f2edfdf699c4637c9c3220d275c
28.065 5.500000000 (0.0) 0x55C9464B2285Fc7B27d0bc46248bEe0f1c51e4C4/5335 1150000 0xef95712b0e9e05a7e227dee427ffee9ebc8023d14e0a0ef387cbef822bcf0065 6547067 6547067 / 74
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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.