× 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 #305 - 2018-08-24 01:15:31 to 01:15:35; Start Time 1535073331.646626

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 483.990904961 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4132 168412 0xe4eb1ff1c32a2827b865f75935d47d2b9b48002f2ca385a6f215744690863298
0.613 503.350541159 (3.9215686273635995) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4517 225196 0x3221acb6c821ac1a704f75e0f620bf8195c89d631cfee34eee5750a932d922b7
1.043 486.410859485 (-3.4229828851636355) 0x0000F7F39325076881E5fC566E99595542532aE2/15847 224863 0x386e399d1f2f485e18ecab4644a8d3a9a1297fc37674fcbb609101ace2ac5672
1.198 759.174142613 (43.79681557959857) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4517 210042 0xe54bfa4fc09d7c1f13e8443ddb3c295070422eb813282a53553e581f082606ff
1.431 760.692490898 (0.19980019977049007) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4132 198046 0xaa21413946800e503743602811a111d380f97de9e42754749dfda42147c8dc9b
1.486 1454.683063949 (62.65218297029814) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4517 225196 0x1657f125389e036e231c0871d613cf66a4404158eb6f6424aa514acf5b8ca1ee
1.660 859.582514714 (-51.42888998753566) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4132 198046 0xa67a6268f4f816cf44e935b09004ab20a8e0125289943555bcd789e24e28ca9d
2.056 1293.177234526 (40.28268551240557) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4132 198046 0x187f067725cb904f2b87c6f86c19d8ff165f207b07d18e9b61304f22dc8c8e4f
2.259 503.350541159 (-87.92813604742027) 0xCC4A5831dd286b3De8820f4D562Eccc4af635B43/112 210307 0xce57da7608ada581f23d1a3cb0fd22fea3f4f9d0c5995d68c5f2b8e17321652e
2.283 1299.643120698 (88.33004756310186) 0xCC4A5831dd286b3De8820f4D562Eccc4af635B43/112 210307 0x9ac874eacf39b7f6fdabe2ace65dc61ca89a259e521ca52b8045899223fb62aa
2.405 1290.596042442 (-0.6985515766067516) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4517 210042 0xa22445aa732dd599e3a4adde8ddb135cf816a899ab89060b7afaf638e2a7df3d
2.488 4253.634460812 (106.88727377517742) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4517 225196 0x1ffb39f7b1d20211759af216d9aa92a39303908895c466fe77949b41ceb169ee
2.667 1461.290275014 (-97.7211184704924) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4132 198046 0x14de09acc4f89a2b73522b45b54a30ab7d87f2d2dab8be967c97d3dd4a487bd3
2.683 2198.401298695 (40.28268551242735) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4132 198046 0xa0f61b3ef74f788711d3a0866617a31e50ba32bd7b4b3274cc21d9e21b0c1113
2.684 4223.128894792 (63.06059568638541) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4132 198046 0xca64a0bb78fb5647e0672e268cde0a56ea7eae5f86c8d8120a77407e3270bbb6
2.884 2209.393305188 (-62.611073137384935) 0xCC4A5831dd286b3De8820f4D562Eccc4af635B43/112 210307 0x7f3a4ddda9436a34fea2d7d69e4d72c926ece4842aca676c3c7fce3a8bf627df
2.896 2194.013272151 (-0.6985515766883479) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4517 210042 0x68d4d141edb4a7cfd8ab4ec4656d0d4d62a7c9da4fae16aa235e416f32b31041
3.114 2484.193467525 (12.405616575812001) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4132 198046 0x6b36205bf70b653972214959eedcb7b80662f7219337ee1bc0142769d770ceea
3.309 3737.282207781 (40.28268551236817) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4132 198046 0xedec4f869184ec9167a99dace8eb93939922a0d0534b7e7ac393ca358f6cd6dc
3.507 3729.822562656 (-0.19980019979185148) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4517 210042 0xa5806f0f17a3493e67814258da2d3c017ef7dd141665f2490f677443f203a55e
3.708 1471.845834190 (-86.81740380971269) 0xCC4A5831dd286b3De8820f4D562Eccc4af635B43/112 210307 0x199b59d500fae8c2990bf04198245b0befb84ceda39c1420ae5669be85420911
4.049 2472.961208713 (50.75611372799999) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4517 225196 0x4c1f17ffd6674597e73e53971c07e0fedfc9151b763b1b6420479de731b3165e
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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.