× 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 #210 - 2018-08-10 09:31:06 to 09:31:09; Start Time 1533893466.3688476

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 65.338229019 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4057 214340 0x242aa97e6ea642a22de014f859e07c29c4112301d9594b86966182a08daa745a
0.204 49.200000000 (-28.179637763253584) 0x4fCc2FF6c75923D33B4F5aF4C524461014B2EE1C/5746 780000 0x500acf5c637ef02834e83ed86ef9dda1a1b288060d8288297b5fecb7ca63a2b0
0.405 82.244506709 (50.279022739468274) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4401 255744 0xe9b2f81b922b8a5bb1a50096a98509d9f376fc69c075ae036c6bcb6d7e4aa6f6
0.633 82.408995722 (0.1998001992929741) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4057 249657 0xb42db5c4938e61d82995a1316b713c2dafad8d619bf731f44dc73b3dc8689b82
0.921 139.815661405 (51.6654330128564) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4401 255744 0x35d99cc86c577fd860e91e6ab68d793d6e88d0e5b1d252104a080971b02861c2
1.047 140.095292727 (0.1998001992220225) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4057 249657 0x79dbf2a3750ec721b6f5acffbbff32b1e9efce84733f0c8b9cd77798ca74865d
1.245 237.686624388 (51.66543301292654) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4401 255744 0x1299b1316c7004b3520a2636bf6ba7c905afe1a24ae5af8ebf9da89667d666cb
1.324 238.161997636 (0.1998001994743715) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4057 249657 0xfc2813a81d90431c9487402e31f61661770aa12becd6faff3a4df6a13d92b6e0
1.405 404.067261459 (51.66543301274877) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4401 255744 0x2b3ca97683c16d680ed37f5b5db7697e32e79096b27fa0610f66652930cf70e1
1.543 404.875395981 (0.1998001995734636) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4057 249657 0x4084630149abff9b6811fe342cf55eb111544c72431d11086ad71983d8379686
1.696 686.193340561 (51.567410037171534) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4401 255915 0xc7850455f52c6bc0031a5b32e29a67fdd0ba3a3b9fb5baa371307c6e9e034760 6121528 6121528 / 0
2.489 49.200000000 (-173.2388112394559) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16168 737762 0xcdabc3047fbf6c727e23e0141d1475f15f52533618875a03d42596d8b5f59583
2.668 237.731908323 (131.4122987749199) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4401 255713 0x7f3f84ac24cf2a4cc27748679eff63a47af24ce705dec2ca048e084023866a1b
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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.