× 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 #201 - 2018-08-08 18:42:30 to 18:42:35; Start Time 1533753750.9532297

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 65.571472433 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4053 199340 0x68b2424b4dffaeeab0c9140a3fce1d72091f4b10a18e83c503890079e36589a7
0.937 68.194331330 (3.921568626981914) 0x0000F7F39325076881E5fC566E99595542532aE2/15827 225919 0x392d0f492a6cc5a3b1705f7fd2959347569f6286155cd672b58206be8825d2b1
1.040 96.010287923 (33.87962740578238) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4396 210808 0xe25b2786bdc5a4916943db56c99706265977232f25e34e33e11464288b350936
1.116 93.163212200 (-3.0100153786326738) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4053 234419 0x654d11d97c862f952b85104e3fea8e594090b0d160d2295bce77f2ebbdd091e8
1.939 92.977257685 (-0.19980019940304775) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4396 225968 0x883a6a03332300755c9ca33047eb1d05884918dbbb32c59bafed684c908e383f
2.566 280.011350587 (100.28943981345743) 0x0000F7F39325076881E5fC566E99595542532aE2/15827 225919 0xceb8a73adb1929094ce3c8fe308828e143d065b63c921f7453f474868237ced1
2.709 476.019295997 (51.85185185167549) 0x0000F7F39325076881E5fC566E99595542532aE2/15827 225919 0x3942e00e2df37dce4333281f399c6415be3ddb50b9ceeb63281ebe41e4ef1aee
2.716 776.555353905 (47.98692963034396) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4396 225968 0xf3626879904954e5015818a6b9c6efe4d0d6c4c0e46b0906c30dcb5d4507a0f1
2.830 158.377460740 (-132.24006762447976) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4053 234419 0x5d6e9ca20bbdecb448d1075d332060a4850d70bbfc1fbce618d4f07518fa36bd 6112000 6112000 / 0
2.936 158.061338064 (-0.1998001997193803) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4396 225968 0x07c3946ad981dea5a1a3db0d5f60cdd526823713169752ee14d1d8c82ca2bf8f
3.360 269.241683257 (52.03817415064741) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4053 234419 0xb3b477e8238a3d608a7353e60de676a87b5d0ac6347b43f5638ec9076f28efe5
3.573 268.704274708 (-0.19980019964569193) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4396 225968 0x087addeff8440119985a51196adf6a25ecff6db5d67a50aabe1aa0e55aead7d2
3.653 457.710861537 (52.03817415094535) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4053 234419 0x7a22c84c281faff6aaa7a1a73d9a107e01e43099a9279936ddcf3cff4698b336
3.786 456.797267003 (-0.1998001997988889) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4396 225968 0x5089075de4d6fd6d81a3979905944760b16e9bcb7ae59536aa513ba362bcc1f6
4.231 476.019295997 (4.1212880980973745) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4396 210808 0x73ee164ea72f6984e48b5a0acb60538e76dab397b745c57dd2141a5f3d2c25e4
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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.