× 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 #1561 - 2018-11-25 09:54:37 to 09:54:45; Start Time 1543139677.149121

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 19.800000000 () 0x0016BD4cb70Bd98CA07A341DA66450b5d22A55aa/57390 225582 0xc5c6e6c666f2c4b8fd8b29442ab084f203a748ed8df9ee5b75d0e0748b0b74c4
0.146 19.800000000 (0.0) 0x0016BD4cb70Bd98CA07A341DA66450b5d22A55aa/57391 341112 0xfa9f9254693861853bf8bffa7938e7168ecd7f181163120d1af8ebc7d5c1d06a
0.398 18.000300000 (-9.522146649629764) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/415 2000000 0xfa9e7645b2f505c0ed9d85b9bf3a1662a6dad6c335c38fa559fb49755f823cd4
0.426 80.500000001 (126.9025576579269) 0xDF4E525428eF1cd68a438f1d0E6A64f9163089F8/1413 1430000 0xdf1d12f5ce2582f0a01f9693f464d490a70cf2218f2e695abd062f4a3760e9b0
0.429 80.500000001 (0.0) 0xDF4E525428eF1cd68a438f1d0E6A64f9163089F8/1414 1430000 0xe13be2d74cdeb92a45e98e5f72cd1242498bea3db0f5215d5bef1c5b951ca897
2.632 11.000300000 (-151.9114144986201) 0x9F994f73dCF01ecB1a82b7bf157a0CE45eF4D851/67 2000000 0xa88805950ca75eba3f02e682f932d8ae0b6c42f2e17aca2e2c526946d466196e
3.267 27.000000000 (84.20828256619026) 0x5C87915F26B5414e9748300caa7A67f5f0c1b989/3966 145864 0xdc1cf88de0dc54458132c29b08a1696114b5b26b457d21952615be2cc7ff4f77
5.228 19.800000000 (-30.76923076923077) 0x0016BD4cb70Bd98CA07A341DA66450b5d22A55aa/57392 332819 0xe904f98daee1ad6ae062f91fcf29bad294cd7822b9430bb67dbee8ef290d476c
7.589 224.000000000 (167.5143560295324) 0xCd5f8fa45E0cA0937F86006B9eE8fE1eEdEe5FC4/863 279622 0xdd26517627b43b02cb459fa187a3700e9767437af152ebebc0dfe8e3f70fdfbe
8.058 224.000300000 (0.00013392848174432028) 0x9F994f73dCF01ecB1a82b7bf157a0CE45eF4D851/67 2000000 0xfc390d1de9cd15fc5269d0ed099fbcb32f6b1fa48cc2f6df24d9c05b420be5a7
8.335 224.000300000 (0.0) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/415 2000000 0xf71be41bd9575bd58caeab13a448abad3b87e27e451868363735ecc10a010319
8.767 224.000300000 (0.0) 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/136 2000000 0x51727fb0c3c14e6bf47c6d061ebc662eb4aba99d5df0b8c58468b7445031dd2c
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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.