× 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.
*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 #1535 - 2019-02-21 05:17:14 to 05:17:19; Start Time 1550726234.5992496

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 40.000000000 () 0x0fD081e3Bb178dc45c0cb23202069ddA57064258/202792 105000 0x54d605ffeb45da537b7806efc40dfbd9d447ecb2cbbca46715fa17a0ad367294
1.430 60.000000002 (40.0000000032) 0xF3A3fD06A875A09d7Cd5fd18FDBE22493fC86aBD/9090 338884 0x1696ac27a0351a23f17eb3e152f2adb640331b02d860736b17b7d1cf383a5eac
1.684 85.918597411 (35.524734843278985) 0x0000F7F39325076881E5fC566E99595542532aE2/16046 241299 0x4c80b33a7e2a5794a9991eabaafe3bbc0aba59d7469dbba34f8a378a43793b93 7247528 7247528 / 1
1.714 60.000000003 (-35.5247348416649) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/14333 250000 0x67c22d66897861dbd7c08cf5c9e2e94b0800450466020ec89f94ef60a7c81a24
1.796 296.174662198 (132.61732922580526) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5513 225966 0x5b05dbe681ee12d589ac7d7fe03e3b39e416db9e5d0deef227662d5bae53d67f
1.830 296.518549917 (0.11604240169137472) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5513 225777 0x8b61f118c8aefc0b11c27a08ef39363e628b49163cc39464b27fd69e4b51f9ad 7247528 7247528 / 0
3.109 62.400000003 (-130.45775982666993) 0x0000F7F39325076881E5fC566E99595542532aE2/16046 226253 0xed0d08e87b027dc46e0a1cb27efca6f8a3b8fa59e1e8ba7d44ee8e8094663ad9
3.267 295.853331126 (130.32863107639216) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5513 226143 0x76a6d756b26b63b66ae4a5e55656822e61209989b6c702511a20953e19d0d546
5.125 40.000000000 (-152.36015689837723) 0x0fD081e3Bb178dc45c0cb23202069ddA57064258/202793 105000 0x4670a362bed8e595b17175cc5b00160ecbd893a003dbb02e37f5db9dc817f9c1
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This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. .
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.