× 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 #930 - 2018-10-11 01:55:53 to 01:56:02; Start Time 1539222953.091568

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 14.280000000 () 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/20189 816051 0xbc43e7364563bfa2a606af0e8b61dbe6e3b3e55bbae12d34dc1b554f7440ed10
0.594 14.280000000 (0.0) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6919 870201 0x96155b3e2ff3d1fbcbaef94bd6c8c3687746e36266b464332a036155ab6fb258
0.706 15.280000000 (6.7658998646820026) 0x7806C0FDa5870e1423446a7Ddc2A5Ec42ef80dd5/373 489614 0xce0de999347217aaab9a5976573ce15a1c7f40ee1ca8cafd15ac9a54de380edc
1.003 14.280000000 (-6.7658998646820026) 0x3bd189a9b1c11684b08f6464866dFa431362A06e/1369 1300000 0xdb190acefa2911fed1f6fe9e93af2fefc6cd6ce14490c0818a80b4c4bd1bade4
2.877 16.000000000 (11.360634081902246) 0xc597A5d92F5dC1137D847db733cfe02c6d209f13/24865 97000 0x6b2385d762fb6bac9bdb8cc6a2d064e0ce448d8d9bcf3bd674e0c68e35332ab7
4.110 8.000000000 (-66.66666666666666) 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/176772 98480 0xfe417ae1ab8e4466f31f074e6961068fb7b0ddb8fdddadbe7f5848b98be2cc4a
4.252 5.000000000 (-46.15384615384615) 0xAf337ba6a96b627512e3b52e7ed1456BaA89dDEB/115 250000 0x69be0a0427ad2047a3ee77964fbf4d9d51ebfe5d85100c2757a616ab89fcc024
7.216 16.421999999 (106.63803565991215) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6919 22000 0xc1786357e9be5177af15374a0dca7d2be39de5fbf98664e94f106ca021cad38c
7.219 16.421999999 (0.0) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/20189 22000 0x1e3875b50198d16dcca4894bb45d059ebfa80a23def90802924c81f56d6ae85a
7.992 6.721773214 (-83.82580226418156) 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/13370 231858 0x03270daf0cddc958893ba867a437f440a682ffdaec74a775857bcb61a6ecd7ff
8.291 14.280000000 (71.97703459593218) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19894 869825 0x3cc691a28354879785b642b4aa3fd3d2f6de19ee24cc5380a35a54e015b13ec9
9.837 140.000000000 (162.97640653357533) 0x5BCbdfB6cc624b959c39A2D16110D1f2D9204F72/6253 300000 0xb520980e68e08fe64c2142922f57c25c6467169956f99e56b788559d39222fe0
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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.