× 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 #283 - 2018-08-20 04:33:20 to 04:33:23; Start Time 1534739600.1739087

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 82.743919122 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4123 199148 0x3d57fcf53fe761d52b165ea29ca646cea86c689d3607791f352eefaa17f15ab5
0.627 86.053675886 (3.9215686264287557) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240428 0x4c7e9965379b7d2b4722ac473b9d19e08e35dbf3868c6c728d20930eb571fa37
0.846 93.500628607 (8.294930875678698) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4123 234163 0x52b3bc7e5a29148cfe04ba68a83f0cf2919bcddbf6d3a12ef1c1d098e8d34f08
0.875 86.053675886 (-8.294930875678698) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240434 0xe5d4e45d7f8e7051e0db4980724db6e497a425e742d869e739d3d689fd9f00de
1.099 146.583831504 (52.03817415093393) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4123 234163 0x8e09c5f1204e63914fcb3a82a20177253eae26232423b0ccaa2dfa0470abcfe8
1.184 146.291249006 (-0.19980019979201338) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240428 0x048ef39f4bdf35fa7702cc2b2d3d6a87b566058ba08a6a6c19f154812231ccc7
1.313 146.291249006 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240732 0x5d47d972d263c7ff279a52af4597aee056377093cc8e43d4bc66a0ba61e70eb6
1.361 249.192513556 (52.03817415076208) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4123 234163 0x97002cce50e7916cc28cb91347cb871d11f0745adf314cde0869721fd41ce066
1.401 248.695123310 (-0.19980019955139644) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240732 0xedc81e7f8d397f253034ccee08fdde5021a8e415a5d6073f9a255937f454c5a5
1.707 423.627273046 (52.03817415101313) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4123 234163 0x5545499f7f54fca105aac2333dbb82b71e39b65dd85ba7c0021f47fd8115734b
1.719 422.781709627 (-0.19980019974024152) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240434 0x8ddea7529915a235cd98dc130c4be2b6d22d924048cfd1fe6e5616470bbf1eee
1.813 422.781709627 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240428 0x5708edbaf5917a80c2d13fe66e78402153acbe131ef7aa7361d7e6823fe502d5
2.024 720.166364177 (52.03817415085778) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4123 234163 0x652444e10c227676f62293d59b0beb589175ff767e8938535e2d5909b099307a
2.048 718.728906365 (-0.19980019969883445) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240428 0x5b1fc7678a4472304e045aaadcc1377db76e0e8f3f8b88cf41972014ba8d1e8e
2.326 815.588407430 (12.625745690821475) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4123 234163 0x87339f1442591e858dff3cde458b16bb9f657d63549dded09fc28f44fcc44aef
2.351 248.695123310 (-106.53050014329118) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240428 0xf93020a352c7021cb4691989f357e0e414250b85fb8d5cead3ff8873e0af2cbf
2.571 718.728906365 (97.17223650376037) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240732 0x3b9adee71337c3e92f3893d97b69c62caa6866e231639d65aa43f2878a23946c
2.614 813.960486458 (12.426729191045906) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240428 0xc78f3431d0f881240f238370ef6b2a82f19d15fadf7ab0164f51518dfe0d0939
2.657 813.960486458 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240732 0x8a241802a9d7e235196be871cd6803b493bd4238f70a03b207b9994eb7f9e865
2.832 921.810250913 (12.426729191016246) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240428 0xb15600cca835d789ff36c50df28b003dd582e1afadd982dd19e4f7c129ecb8e5
3.214 921.810250913 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4492 240732 0xf5fd0970b453d9ebdaa04d273fdae9df8b789fd5e76d3a793fd1962141663227 6179443 6179443 / 0
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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.