× 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.
*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 #1249 - 2018-11-28 02:46:58 to 02:47:07; Start Time 1543373218.4717226

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 102.000000000 () 0x0fD081e3Bb178dc45c0cb23202069ddA57064258/182527 105000 0xe7c7af068107835ba7f8af30df81b390f1c4ff4084812e3456d8e488ee30212a
0.324 180.000000000 (55.319148936170215) 0xcE85247b032f7528bA97396F7B17C76D5D034D2F/52921 150000 0x41604582e4321f061902d8c0bb7aeef9efe1a4651fdbedcb07d6b2cccee1677b
1.579 10.000000001 (-178.94736841905817) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/33066 531942 0xa1cab34373d81e4fd70e91beaab0422b5b0bc4a05b1fd2da9daaa14b7d12f752
2.200 15.000000002 (40.0000000032) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/33066 531942 0x4872ba5a53e36030f09d5794544fc5adb3f21d23f9ab3bbcf3ad3e18ae88e094
2.512 10.000000001 (-40.0000000032) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/10962 531942 0xe7b1abf934a9dcb76313a3fc844c680b04f37672a5f52c7893b9c51f3dd36a3b
4.357 134.000000000 (172.22222221963733) 0xd6cB6744B7f2Da784c5aFd6B023D957188522198/38001 121000 0x1f3c807e817e858a3b76a0abb231e3e604187c58a8b7a1c72ebb6ece4c46a974
7.274 10.000000001 (-172.22222221963733) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/21684 531942 0x1e8ebf2a8396b42db3d8af20f11c3ad80460516ee0fdc8f1abbf804e38bfc12f
7.817 15.000000002 (40.0000000032) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/21684 531942 0x1c6a25382e0ca026e4e58ffccb329fbae3efa59ce915c31c9b43d408fe661aa2
8.566 10.000000001 (-40.0000000032) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/19116 531942 0x8444860ea2eacfc56c609cada4c040c3904c23f84a7e3fd1240ca5d738204eef
8.918 15.000000000 (39.9999999904) 0x6427Fc587266813B6993ae4c8DE672640cB3B43F/4088 250000 0xa38e0541b86e6725d8793d77ab9795f5f5a6232c75dd2b968ba1dc1aa7c409ac
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This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. .
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.