× 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 #1090 - 2018-10-19 14:00:12 to 14:00:24; Start Time 1539957612.288035

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 18.400000001 () 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/23796 22000 0xc0b3aa22b01bb15902fe970e5419d4d6897a76cb183e6b9f5d7a25aa34e59fbe
0.982 26.000000000 (34.23423422895869) 0xc69fE3b6fdB09D48563DdCf761450273D8E761Fd/6213 21000 0xc1c7611cf6d0b5fd42cec4ed7c7b32d5172028f86f0dab4e0feb0e83ed20a058
2.753 26.000000000 (0.0) 0xc69fE3b6fdB09D48563DdCf761450273D8E761Fd/6214 21000 0x062ecd0adf13397c443416fb6fe6567e07a977c86d06134c3c32fec942458c41
4.726 29.000000000 (10.909090909090908) 0xc69fE3b6fdB09D48563DdCf761450273D8E761Fd/6215 21000 0xbc1d062da077cf6da2d6a3b9b94c492b3b41056973ed97adddb283f87804691f
5.783 5.000000000 (-141.1764705882353) 0x8A4a0aE920291F260b2fc602D68e72C1965a3Fc2/4769 90000 0x64058097da6ca301800695c05e677e136cf2f1e0ba5e8a0c1817dc39674a58f2
8.187 5.000000000 (0.0) 0x8A4a0aE920291F260b2fc602D68e72C1965a3Fc2/4770 90000 0x04e329d1b2468cfd2b85bca0258e832c3626b703908a41aa0601430f632472fd
9.492 21.840000000 (125.48435171385992) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/12236 225124 0xa6bf93d1bb2ffa3867d3c7c02e57b0d7a5d7d453c8e2e346df63772fd062714e 6544508 6544508 / 7
10.480 134.000000000 (143.94250513347023) 0xa8660c8ffD6D578F657B72c0c811284aef0B735e/52365 121000 0xee27b4d898216f4cb50772fd2b27d2aa7a9d1c35abd9999ff5fc767d1a76f813
12.256 21.840000000 (-143.94250513347023) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/12236 225564 0x472e7e9374aa3cf8bf1d690b73c22a03b4a91f45a818de8129c5b738b7e2a6e4
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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.