× 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 #461 - 2018-09-12 18:43:21 to 18:43:44; Start Time 1536777801.9564025

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 60.000000002 () 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12576 322581 0xb380dde9db8f908f19a2cef50544cfe72976823b264356d8792ecc393af19aa6
1.552 72.600000004 (19.004524889034485) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12576 322581 0xbfcd9339f530e1f187aad05d4e2b75206f31a1eb67e07d2937870aeeeac7678e
2.823 87.846000006 (19.004524888186396) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12576 322581 0x0dedc2349e1cc63c8063b93310fbf50882228d56390613c4c61fc562f31db11e
4.258 106.293660008 (19.004524887567726) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12576 322581 0xa1c6087060fe1149a968c18e4fa7430a0869749660a94cadbf0beab40f666111
5.868 128.615328610 (19.004524887124386) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12576 322581 0x64fd5660f0d86dea855ce6a5f0dbd6ec0b2b97f38a8e305e5623fac7e3233abc
6.517 7.500000000 (-177.95986660256574) 0x3bd189a9b1c11684b08f6464866dFa431362A06e/691 1300000 0xe40920a3c748706f498e9b1c297b265621b80b1014d05cfbf7384f2aa9ae066e 6319634 6319634 / 71
6.517 7.500000000 (-177.95986660256574) 0x3bd189a9b1c11684b08f6464866dFa431362A06e/691 1300000 0xe40920a3c748706f498e9b1c297b265621b80b1014d05cfbf7384f2aa9ae066e 6319634 6319634 / 71
7.110 155.624547620 (181.6091444005808) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12576 322581 0x504e63bf517d14c146ef818943948633f60dd249202bab84358ea3d3e36fc074
7.971 188.305702622 (19.004524887825088) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12576 322581 0xf4ac865e7db0f8495a795c34d826c7d0e191858ee2b3899d92c39e208164c398
8.751 227.849900174 (19.004524887478023) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12576 322581 0xcafcb0032e3abeec970aa0d7ab6630a069fe4daa527eb0b5b2b6acbc57b394e1
23.028 7.500000000 (-187.25302199923593) 0x3bd189a9b1c11684b08f6464866dFa431362A06e/691 1300000 0x9802043461c0efc0aefeb3daa0be97f6b6b1c5134fe583846335cdc7d46e605f
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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.