× 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 #382 - 2018-09-03 10:52:59 to 10:53:00; Start Time 1535971979.556198

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 197.010409818 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4175 199148 0xae0d7e7a52c63a388fb6c99a95bf97f56198834972b1ae8aaa59550baba37741
0.365 204.890826210 (3.9215686270997088) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4585 240615 0x8ee92d3dfc20945ca4bd390d9e0271ec75188697172856cbf93df5bbb91e374d
0.463 204.890826210 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4585 240814 0x6ae7e7fdde6038f344db608a8afce4053a0199c3c4352661fc3203a32b15892a
0.551 222.621763094 (8.294930875774376) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4175 234401 0x08219931a5221ff0586594500995f6266a7f6f066d233a792d9ce1dc2b695b16
0.709 348.314404557 (44.03036576930715) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4585 240615 0x0ca6fda988a986bf5bd6e006c779e62b3c809cbed7b4fb922d8e09d2b191a428
0.717 349.011033366 (0.19980019976753613) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4175 234401 0xfa2a9ff45eb0e48890aa6c85036f7bb28061e6b377b50c7d558aee233d333714
0.883 592.134487746 (51.66543301247191) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4585 240615 0x5718323d9f535beac2058cba021af42b6449745773f0043906e5fb2e73f3910e
0.952 593.318756721 (0.1998001997172765) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4175 234401 0xd33107e3b6c60b1284135ef841857e85e6ddd3c4588cf9b3eedbf7b5af52b921
1.163 1006.628629168 (51.66543301264211) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4585 240615 0x793a1e76ce06d957849baa1eb3e4e0e6fdb395611fdca172e501815da44ec1b6
1.200 592.134487746 (-51.85185185183332) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4585 240814 0x2a45330e7db45694c908e0b9d68ea60326a4f10ce39e820c2a07e4fc68e96cf6
1.311 1006.628629168 (51.85185185183332) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4585 240993 0x1f61e9c587a2c32e98ceb37ed47f4a6c3bce414489f78777fffe1fce3a966aeb 6263962 6263962 / 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.