× 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 #749 - 2018-10-04 19:12:49 to 19:12:55; Start Time 1538680369.511329

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 121.000000000 () 0x3B677F7093FdF292D61007FaC8d6bC03B90bF5A0/16 21000 0x7e5dd281d6c4364300de9f2a939424833cc9117bcaf768e35fe4e630af523b57
1.181 21.840000000 (-138.84066087930552) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/12104 225711 0xeb748de0ccb95bad525984f7b522cf474f1771d4a397be54be3d5dcae6a2870d
1.729 21.840000000 (0.0) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/12104 225708 0x77ee82b6b989219b87ac3798ac9d3a5886805158b37b1afe54badd5a78537c37
2.522 6.000000000 (-113.79310344827587) 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/170612 98096 0xfbcb6332e698f8863a72b9d58775759c1d04b0a8b35b933f387a00d0e60af78e
3.440 60.610768028 (163.96978940415227) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/12104 225708 0xbaf7ba5e338384abcd0e73719f82225ca05588cc84074638b81aa607d370a848
3.478 60.610768028 (0.0) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/12104 225741 0xc9d8dfdfbafd516e8396dad0c5edd832217b98837cd57734ac5d09e4a8d5c6fb 6453535 6453535 / 3
3.833 60.610768028 (0.0) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/12104 225711 0x291732479372f1380aa4b4631fc441d35d581e81e11b08c301664f02f7ca1c14
4.542 3.300000000 (-179.34620345320067) 0x3B677F7093FdF292D61007FaC8d6bC03B90bF5A0/14 21000 0xd09aacda861742bb75a2ad3c80fcb61c627bcaddaa9c6f6b112942d34a536bbb
4.865 35.000000000 (165.53524804177547) 0x77977a3723F17e2a0457416B7A1307b16B77d8Cb/517 249892 0xd63ac0f7a3c0307132af0851434f2567b9d343f0510e24679fd6ddabbdb1bd39
5.002 35.000000000 (0.0) 0x77977a3723F17e2a0457416B7A1307b16B77d8Cb/517 250125 0xb572b1598394755e4ce0caf82d4a25ea26de76674b72309b7c105802f9dda33d
5.313 7.000000001 (-133.33333332539684) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/18518 464599 0xbd9cecf465d144cf2111587ffd72e8529fb7acdd6c7723443af429715fd399d9
6.190 7.000000001 (0.0) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6355 464407 0xb52badf927a09e71ea9957df0228b918894c695d4de9aa779150c98cfdaf451a
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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.