× 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 #1094 - 2018-10-19 15:40:46 to 15:41:00; Start Time 1539963646.8586135

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 9.000000000 () 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/7914 747901 0x6fce41d39622b424c1b0a46f2a2c0cb1f52558e3f10c86f3ff935799d4f0c773
0.552 9.000000000 (0.0) 0x55C9464B2285Fc7B27d0bc46248bEe0f1c51e4C4/5228 1150000 0x045c7150c6d2be033b2ab71e22dec46eeddf5f3ed6ff913be86b7559b814b764
3.537 264.000000000 (186.8131868131868) 0xA093A1B185c88C20318Aa8A511B13207D0A5E930/1 38135 0xed4f648a24dabc1aade19366ebac008fa2e6ea798102db1a29dde644d3813d0a
4.444 10.350000000 (-184.90978676872606) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/23873 22000 0x1256d417d359239860478c6d0813281819cb3aeaf13184c9f07baedb1f25af76
5.285 18.480000000 (56.399583766909466) 0x0016BD4cb70Bd98CA07A341DA66450b5d22A55aa/40252 196593 0xc9060db9e0702216eb7ab49f35b4eff0ad2baee74e07f1981438e4d1b2b6cc0c
6.309 10.350000000 (-56.399583766909466) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/7914 22000 0x0484eed01b7e03d463f22aecb9697d1b106d0e33fe39e183a5b6f173dba71562
9.257 9.600000000 (-7.518796992481203) 0xA093A1B185c88C20318Aa8A511B13207D0A5E930/1 21000 0xd385dc62b266fe32e2231bc9bfa50ab47eb6022bf568e1678fd4e0245588dd52
10.129 9.000000000 (-6.451612903225806) 0x8A17a3DC0574Bcc3FDB73b1A851D9677907A51C2/364 850000 0x5e07b6b175a217aaac88f629680d1f3303bdc65e1963a922abf6662e52043539
11.332 10.000000000 (10.526315789473683) 0x4EF377462B03b650d52140c482394A6703D0D338/7365 345537 0x727a1506200f39916249e02899e58a59d4784f242fbfd45fc21cc715bf98cc6d
13.213 9.000000001 (-10.526315778393352) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/20326 497439 0x5ae17b566bfe6dc53c29059e6265ae8fca4c7c9d6a5f121dd20cb591cb80ef2c 6544937 6544937 / 45
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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.