× 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 #195 - 2018-08-08 08:05:00 to 08:05:07; Start Time 1533715500.262702

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 60.000000001 () 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11893 339968 0x45e1a1c16b75ff97d8d228df057f56cc71c2074ead1d843fba8d7449a10da6e8
0.499 69.000000001 (13.953488371876691) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16056 312235 0xa83cc42b1387d441e347a4f36ceb76d52733c225202b8feca36edb140ba748b6
1.705 75.900000003 (9.52380952630714) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11893 339968 0x0f836c2e8b41dc96a09b9f54be68f448ad39e530630b02a05c022e77b9b583a6
1.948 79.350000001 (4.444444441753444) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16056 312235 0xb2f2ccafdecc6ff2f2af23586e1c1d668216d874ca3812cc124d7ea2c917543c
3.090 91.839000005 (14.590890774012669) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11893 339968 0x99563abec3352b42f0b54234af74c66bd2ea44d4c5461281a60924b8f2a07987
3.334 92.839000005 (1.0829660272970811) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16056 312235 0x44faff8106452477845b668a9a9517c9bbbab3c3af2e9ebac7c54be07e4b7630
4.456 111.125190007 (17.930784811710478) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11893 339968 0x6519d892e55fc6e4192b408da36bc06f3a6b43552d10d9ab9ea83e489074c41b
4.704 112.125190007 (0.8958551380179421) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16056 312235 0x13e3a581ec31266e5840048aff935e891dfd9458ea5b16030f59da34ab144608
5.834 134.461479909 (18.116380670219424) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11893 339968 0x281f0a969c9fb2ae6459bdbab096ac002bb8e784ae313ad6755d8c5b9e160fa4
6.061 135.461479909 (0.7409521595897336) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16056 312235 0xcf3a90e1346226377eac045708c275f78442c241723583962d06a607785035e8
7.220 162.698390691 (18.27000442895953) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11893 339968 0x6a6dd4f4f98bb79509f8f90474f669bee5f016ddeb582f07020a9ad4c1c2c797
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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.