× 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.

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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 #1473 - 2018-11-19 16:24:01 to 16:24:06; Start Time 1542644641.9223251

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 16.500000000 () 0x0016BD4cb70Bd98CA07A341DA66450b5d22A55aa/49104 225582 0x2cef6bcd2d6ca5ac12e8cec3c16804e3a3e5178a310881506e6fb9ca8105790c
0.527 3.800000000 (-125.1231527093596) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20892 235508 0x487b94d828bcba1cb4f8ac7c4ad8368e46c9f2e31616e8ae8aedb674ee6d8c32
1.184 13.915681000 (114.20030649682617) 0x8Ebd10FE696288c6ED1E024064FDF54541Aa63e0/4793 145510 0x78fd00c14c7703785959d332cb8a05c00e8ac0aa7238782231f5cd0546b18d56
1.326 13.915681000 (0.0) 0x8Ebd10FE696288c6ED1E024064FDF54541Aa63e0/4794 850000 0x1074b54aa3f1085276fb5cbcaa45714e23e493b13a537223007c0b5dd261f9f8
1.473 4.100000000 (-108.96819276495849) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20893 235508 0xf45d438288c6d6d4369fee585973aca5bb81a87153effa8e70d35ba95f687bc1
1.483 110.000000000 (185.62664329535494) 0xA7B0Fc43050F617493bec8E090703B7F096fa328/47 70000 0x4e9c8fd40721677404bddaa00891c8e2f28f9456c61ad6258e4a4cf6a8098ab0
1.629 4.100000000 (-185.62664329535494) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20894 235508 0x810a2766ad5dceb9fc24ca5e27f9eb1a819002d2e144847a25c60d0ebaa68e26
1.674 3.800000000 (-7.59493670886076) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20893 235412 0xb50127e61e3318844bc84171cccf33f550f78db475bf552fb7c8d29bb5c05441
4.657 4.100000000 (7.59493670886076) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20895 235604 0x38b8bab997f16acfcf9f99fa1cf06e21edaaf010b01ebc81f71f53a48f47b2dc
4.750 3.800000000 (-7.59493670886076) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20894 235508 0xd92814ab97af6df171b23b738081302a9573a5a46ae2d4563b70929e8f697929
4.798 4.100000000 (7.59493670886076) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20896 235508 0x2c4f5b0704d177cf4da579abdeda3abefd3d6c2af40d37b59d213315e1c40488
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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.