× 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 #938 - 2018-10-11 17:05:37 to 17:05:46; Start Time 1539277537.6907651

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 474.150938728 () 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4824 151855 0xbd90eaaeeef974e95f5bc4c03835978e32f566befdf9ef050ba070acc8f2f2b7
0.221 60.000000003 (-155.06887985965616) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13166 250000 0x9f5f2d746f6387ab554aa2e548b0684b52fc6755fac28d328042a87b8d91682c
0.242 475.043988995 (155.14387509306323) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4824 151703 0x3150129fefc1677f0849f50a4e158f820119eeade1ae72580127722e72546aac
0.269 60.000000002 (-155.143875093727) 0xF3A3fD06A875A09d7Cd5fd18FDBE22493fC86aBD/7715 368884 0xff6e174e2f22c319e5f9343f184d50544b4b4842571a1443053350b84d298005
2.315 496.614878212 (156.88221616028596) 0xf666666666E8025c503209ac580a5aA4b39A090c/435 129272 0xbb0cd2d8e8a75b9223d8074e11d91fc9558850f17e4c52bc69675fc48d29e5ac
2.480 806.056595837 (47.50878848420386) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4824 151855 0xfdbf23f4c8d3d4e7f929b2a5f0d79c059e2922b67c27cc6ed2b7ad37a4e25197
2.509 805.578354056 (-0.0593486485300845) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4824 151902 0x80fafc98578884aaf6b78f1d5eb748e4059e0bf1f06c41f27cf049963dca7e4f
2.538 807.574781291 (0.24751862563507404) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4824 151703 0x8da19c8cc3aed12a5599befef8e764f78a7614dae0c97fb737112301f12cf5bc
2.607 807.668709028 (0.011630164438112038) 0xf666666666E8025c503209ac580a5aA4b39A090c/435 144266 0x4f73ac2d8ab7534783e82675b9e60641d5d5b052f83c4dfbd98afff697b66b7e
2.748 1369.483201895 (51.610040626776446) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4824 151902 0x7e97d20feb1e7c82d445e223a0d3fcc8a62a942f0426423f998c6f09f28c0e44
2.766 1370.296212922 (0.05934864847900932) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4824 151855 0x14730e3e4439964d8dadb97d5f27b32807e5e0c8634e6843ce34db3594aee495 6496156 6496156 / 0
2.837 1370.058985006 (-0.01731366183328129) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4824 151869 0xa7d6058fc516f7823b246e630df889d29e47822fddfac9f403b2bbc7539d1a0c
3.039 1372.877128194 (0.20548369132172467) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4824 151703 0x75d58bb9765bf4912b533ae74fcd712bbc92ce20cd79ada834a0f616c23ccf91
5.765 7.053423921 (-197.95542640600593) 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/13528 226021 0x5b59659c16b7de9e0660826ece5ec627cbd686772f979a3764338d8cc12dbe15
7.931 45.000000000 (145.79857853958055) 0x274F3c32C90517975e29Dfc209a23f315c1e5Fc7/90278 58300 0xffa5ef254f3c17a4e806bc5d8ceed100561579c1136b9071d7cdb3d3ec69e9ae
8.616 5.000000000 (-160.0) 0xCF085317456133E93D72aB5Fc56025d8d3802C38/4565 21000 0x317de1200f9e862e6b859cc20013bbb44722da239a576d8d2f870fe78eafeafa
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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.