× 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 #1625 - 2018-11-28 04:35:51 to 04:36:03; Start Time 1543379751.9070625

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 122.000000000 () 0xD2bB24e348651970e0A3aE50EA89E5ff2B37C09B/576 45000 0x3e8e34c9fc420d05b9e15e821f3ffe029a21acd66604fc58625db7f518e4b362
0.267 8.800000000 (-173.0886850152905) 0x0016BD4cb70Bd98CA07A341DA66450b5d22A55aa/60627 342097 0xcc870f36f0d6a0c241d29786c6d1994c1d181ef979c10d5f8253ca6d83579597
0.786 6.900000001 (-24.203821641770457) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/21685 22000 0x68b5a374ed25277b9b845371573de2b7066153c66c960b9271d3dbcecc02064a
3.772 6.000000000 (-13.953488386515234) 0x8177573B5557e3a2213d4aEc44abe7BaEF6D737D/4003 850000 0xc4195aa1e63e8748936e01ff863a475060d8927643601323e8e9e01166f2b4c2 6786200 6786200 / 30
3.772 6.000000000 (-13.953488386515234) 0x8177573B5557e3a2213d4aEc44abe7BaEF6D737D/4003 850000 0xc4195aa1e63e8748936e01ff863a475060d8927643601323e8e9e01166f2b4c2 6786200 6786200 / 30
3.890 6.000000000 (0.0) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/33082 657275 0xe1e23ca7a2ec4cade46512c7dbf90744141417bbec5e8742d657c97bab8a143e 6786200 6786200 / 28
3.890 6.000000000 (0.0) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/33082 657275 0xe1e23ca7a2ec4cade46512c7dbf90744141417bbec5e8742d657c97bab8a143e 6786200 6786200 / 28
3.890 6.000000000 (0.0) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/33082 657275 0xe1e23ca7a2ec4cade46512c7dbf90744141417bbec5e8742d657c97bab8a143e 6786200 6786200 / 28
4.078 6.000000000 (0.0) 0x0087C5900B9Bbc051B5F6299f5bCE92383273B28/2151 1600000 0x8baaa73e005a41c8e04c1379fb8e8db8d9b72bc456d97f04b1024e1cfe004981
4.952 7.000000000 (15.384615384615385) 0xd72fBaE4B64079eDd64969F760cdf240eC7533Eb/2826 458469 0x2c339e4c852e0816476390b5894efb9d89a3e1eed9fd521bf0d7ff5fad1eacc0
6.117 6.000000001 (-15.384615368047339) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/10969 479828 0x7fa41911074f330db68cab32eaff505025d7f9571c338eefccfced5e5a4e0dec 6786200 6786200 / 27
11.704 6.000000000 (-1.6666666665277778e-08) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/33082 657275 0x415e8cdf31ef04699a0fc05e5b8f5dd8cf0d1921a158067c59060b0e7eadc4cb
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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.