× 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 #1157 - 2018-10-23 01:03:17 to 01:03:25; Start Time 1540256597.2970562

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 91.235291875 () 0x44c2e195AB76797Bf16f417D13f914e1dcA94FfD/187 280000 0x0d387acb77145a4d479532fae1652502718a628c93f56f5ff351cb87f06f375e
0.489 94.884703550 (3.9215686274509802) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/12282 225420 0xaaf70758ed6745a7e1b5fb03268e0110e961205b770c74bb7d600c0b48a77568 6565677 6565677 / 26
0.715 110.577173752 (15.275310834363964) 0x8edF6F4a065FA92311Fe087740b0bfC8A7Eb3d2a/1 249906 0x9816e47effb8cf46703fe29e858290e6d1c021c78eefd63901842b1174561d0f
0.833 110.577173753 (9.043457759539556e-10) 0x33F8a639B0a6a89943DCb570661674b331A0C7be/5 30000 0xfbee9a2fe34c7c60896982157bf86049b89204fc58dfcf4bf73fa65bb0bbe51a
1.077 94.884703550 (-15.275310835263035) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/12282 225267 0x29e274ceff77ccb2d42a5e18ed342e6bb85b74a9bbbdfc5997ff92541fdfd005
1.371 92.147644794 (-2.926829268021437) 0x33F8a639B0a6a89943DCb570661674b331A0C7be/5 30000 0x3658797c1fa53c5686d25147846b6617f4c717629ac3b14af8d1100bf8bc1329
1.398 92.147644793 (-1.085214931147691e-09) 0x8edF6F4a065FA92311Fe087740b0bfC8A7Eb3d2a/1 249906 0xff268bdb7247cf79346ade816d85b0095eb3127ee52298a08b91d2bca507e07e
3.676 6.000000000 (-175.5470444037474) 0xC9Fe8cCb4f7e28A39A3f4aA44FdF141469e3F77E/5274 447763 0x219f012ee49bd5ac3b53210aa23ee9ffd13f560ff86909c979aabe6c2d45ee9e
5.553 160.609467870 (185.59505632733524) 0x93f36930F94FBB5aFc5fB506D3f7ABB9179a4e4e/68062 90000 0x9bcd79de666ebb20d280c039d8fff28ed5f527c60e07694cfa4c70053b65f8fa
6.787 160.609467870 (0.0) 0x93f36930F94FBB5aFc5fB506D3f7ABB9179a4e4e/68063 90000 0x2b3709592beef02be588e7c9a876a0c20937d1d46b1bef4c4bb034f6d85f77e1
7.881 160.609467870 (0.0) 0x93f36930F94FBB5aFc5fB506D3f7ABB9179a4e4e/68064 90000 0xba979ce22763076ed8e34b3e2c6abc1fb2cf77614698507ea071c8f347b20b76
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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.