× 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 #1474 - 2018-11-19 17:15:05 to 17:15:16; Start Time 1542647705.689604

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 21.000000000 () 0xc69fE3b6fdB09D48563DdCf761450273D8E761Fd/12719 21000 0x8ee764c84e6c8a88c796d1039433cec17ee907ba2c56ffddcc0b4de8dea5996a
1.806 21.000000000 (0.0) 0xc69fE3b6fdB09D48563DdCf761450273D8E761Fd/12720 21000 0x344b3b0a13dfbb48cb274ece57a70888a615a0cd8586454814d332ad0d374c46
3.675 21.000000000 (0.0) 0xc69fE3b6fdB09D48563DdCf761450273D8E761Fd/12721 21000 0x13d2ebc027d90d44ab876508fc8363b07dc7de97ed3b1a35889228640fb19b3c
5.510 21.000000000 (0.0) 0xc69fE3b6fdB09D48563DdCf761450273D8E761Fd/12722 21000 0x0847cc83028d69fdeaf5621cb57ef2d43c2b97a37183ae0efafc73fdad2c2746
7.037 110.000000000 (135.87786259541986) 0xA7B0Fc43050F617493bec8E090703B7F096fa328/49 70000 0x297f67f54e55239339f341a9f8713640ef95f6c1aa6b6d97fd179833b7c3fcbd
7.382 21.000000000 (-135.87786259541986) 0xc69fE3b6fdB09D48563DdCf761450273D8E761Fd/12723 21000 0xb8f174b93982f3936c4eb0c9aff44fd4888a7f75145d3245e40df71c268735a3
7.451 50.000000000 (81.69014084507043) 0x0bee6C5aE91178415A1Ff644De6667A6Ce683d59/2051 300000 0x0a47c01108bab606ea2c696ce41feb38d78ab75da594259be4006aaba0d07581
8.699 4.100000000 (-169.68576709796673) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20932 235604 0xcfed77cae2170cd770e523900b6f326c62cb9051a0e210c780c7239aafc65eca
8.807 3.800000000 (-7.59493670886076) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20932 235412 0xd286b3729ca1cf9a3ef64a45e696070f29c85e8a4c532da9a80eb82cb086f091
8.866 3.800000000 (0.0) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20933 235508 0x77d727f8b66f85b1cabfaa6f0a06c78fb727fecfe0f7a0902a18c71b2ce7768f
9.248 20.000000000 (136.1344537815126) 0xc69fE3b6fdB09D48563DdCf761450273D8E761Fd/12724 21000 0x9e53b5c744db998bd9d006501496623816bd6307c6d4161bc92c9b5cf53ebecd
10.915 4.100000000 (-131.95020746887965) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/20933 235508 0x560346b438cf02f9fb2d1ad20ace5bcdacf0f9579ce68029a363f39529129195
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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.