× 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 #542 - 2018-09-17 13:26:57 to 13:27:03; Start Time 1537190817.0646582

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 190.974001037 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4194 198604 0x8f22e7ead5b1ee2beaa58356f7f9ee732c94e3066841c24fa8ac96d3ae1b6ab1
0.339 198.612961078 (3.921568627209397) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 239827 0x32cc9464a66f316de0a207a74813659e5ee0d16184b47ad20a0bf243d7e3776a
0.373 198.612961078 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 240129 0x721c2892eec10138bb3e5f93fcd4bcb29856a935142bc50acb54fcb80b0cb355
0.547 215.800621171 (8.294930875442596) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4194 233813 0x9f41b70de53f91d708c11db68b16cc21f41bb3354431509cdf1b4b9cd611caea
0.701 337.642033832 (44.030365769454306) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 240129 0x5ef7cd4d1c2d33ffc98e7c7d4e1c071c71efdde5a2ae8f6686e7b77ffdbadce7
0.943 338.317317899 (0.19980019960393453) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4194 233813 0x711f00f0586b8d0b3820906f0a09e1b8a762645927bb02773d61ae14ab698315
0.993 573.991457514 (51.6654330127014) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 240129 0xb56e606fe8d81092bf5fe211e3c77d0ac8afb2d7f499537706e844ceeee39f20
1.191 975.785477773 (51.85185185177538) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 240129 0x9accf6de1703f07aa716ab8dc87a50ca06cfefc43c701d1cc83577d82be31f2a 6348537 6348537 / 0
1.260 198.612961078 (-132.35244376778374) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 239831 0x4030a3d604fd64a07c0dbc07285880d144ad3cdffacaa833342dd5022fe25a18
1.332 575.139440429 (97.32479760131476) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4194 233813 0xd90f6eebbfc5790aeb7c7842da0468d91b00dbae2c0a3fc6010cfce8f7cb7bbe
1.719 975.785477773 (51.6654330125113) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 239827 0x07de13575fb126d32ce7fa75990a6b2ec330c77921fe9005075f60b4d702c66d
1.936 975.785477773 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 239831 0x9181062231900fd29a949b7acbb913cc4d008dd3a64116dc34d0c69c2e078c0b
1.999 573.991457514 (-51.85185185177538) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 239827 0xdf54aa522927299992fc2a4aa83bbd0afbbfdee26567cf3e36b8a10d9e33a5b9
2.881 598.145018046 (4.12128809837786) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 240193 0x0bd2dde51aee0175b3f718c118c60b9ac2f72533a31774b0a7e3d4a507d46c9a
4.711 6.500000001 (-195.69995630031323) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/15318 492004 0xe77883d2789a593b7bd4322b1fd44c8880642ed759272f36b8a7e05c2bec9a94
6.716 573.991457514 (195.52103658591253) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4705 239831 0x89c5f46fa97d7dbd115061438c9a969d54321cf08c1ad5f3055949733d887309
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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.