× 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 #297 - 2018-08-23 01:26:56 to 01:27:01; Start Time 1534987616.3727067

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 25.001000000 () 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 172745 0xfc9df6e68f7da0a3fdeb871db1da8233d981e6c0f2abf43e10c67bb2e0cff083
0.512 27.501100002 (9.523809531065469) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12150 347815 0x713af0f9ca46f5c23bd89dd07c5cc4db05ac9c3b9699be6856b1b240cf9d5dad
0.708 28.251130000 (2.6905829523701357) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0x628828d85cd8e15aa8f4dd72f39e1b9ed46b338927370255830f3c33ad7d9467
1.270 33.342883666 (16.53327446271181) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0x734a499b5e3d632e16f44ffce7fd8985ba2f7e20c0dbea789414a274ef3226d7
1.272 33.276331004 (-0.19980019977620672) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12150 347815 0xf0b3c9bd854979902aefc78789e2b3706631dc52cd40ccf1ec109dd781f23377
1.779 40.344889237 (19.202502240144852) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0x007e31d87a74512d48f94400c7732b3b3a43b0297bb03fdbd082379de08bdce0
1.799 40.264360516 (-0.19980019972088378) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12150 347815 0xe62cca65741405c81b0403f4036b6d0ebaf17f615c37a9640176620270c4ff78
2.368 48.817315977 (19.20250223775725) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0x24a27b5d07179dc0dbf553fc7b225c1c27fcd7d4a10cb276274a163cd3ee4b4f
2.376 48.719876225 (-0.19980019887839667) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12150 347815 0xd07d95295b3458c92d67fff9604f976236903cb897cde5f5bd5a14dd22b24467
2.565 56.139913375 (14.152302190009353) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0x2e306ac6913778e8eb354788b05e546ea25a905ed7ae86bb06ca0e7a98397664
2.757 64.560900381 (13.953488371707676) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0x7172e14374f38ddc72a61ec569c093536504d75dd402acf04c6da5024c09b4f4
3.087 58.951050233 (-9.083898554127648) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12150 347815 0x6b4f2b5235d67918f57d004861840cfc076d7d06798c0bfda2a505a2b7f54471
3.102 74.245035439 (22.96461660842192) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0xa823c9a9b27bab6bb8daee86e4fc7ba92606bb777dbbaab6af3bb89898df4d61
3.284 85.381790756 (13.953488373433359) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0x9d3cafc3b3229fef6f60abb4475b54aa5c746f9087fbfb5ff85ad796875ed779
3.776 98.189059369 (13.953488371687628) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0xb90f47e13b8d1d740195eb18fc97ec6cbea08120c4c20a901eb964452ee4b172
3.960 71.330770783 (-31.687488787497614) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12150 347815 0xef56f75d6bd0c52bf59cca88246a7a0a1562edf2fc682c82cef91734ac7c3895
4.114 112.917418275 (45.1419877770509) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0x2fe2fc173f6f769f107dcee8a7590697d45f3159b844dccd14b57af9666a25fe
4.297 129.855031017 (13.95348837266778) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0x8630c59fd5827b9860541d5b86d3c5e65a21ab05ce703b4b14374a334881194d
4.519 149.333285670 (13.953488372392897) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/618 203139 0x79bee6a8c74953db5dda5a5571f38f07a1f969d6d31500f7490293224843f0ee 6196494 6196494 / 15
5.119 86.310232649 (-53.490164695031574) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12150 347815 0xef648ec2bb6bcc9ff0861e2bc320cefb51f0dbc9ce459c14407306ed6058a8ce
5.518 112.917418276 (26.710334136315623) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12150 347815 0x08f25ecd599ed06e18ef8feef1d719e7f8862d6cf0d41a8c10fcbb268b89fbb7
5.612 129.595839340 (13.75464684112975) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12150 347815 0xf0f910ea307dd2e6a0573092c803f6f8304260c7934f7bdb2151bc8e6d20d352 6196494 6196494 / 16
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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.