× 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 #1068 - 2018-10-18 11:51:23 to 11:51:30; Start Time 1539863483.5058112

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 7.210235000 () 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/183547 98288 0x7501a972540080593453f799de69e451790d1664d282787510b9c72f93976c72
2.133 5.184987706 (-32.67786859561085) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 176829 0x30067237de9642f6ca4915d3914616f820edc4e7cda3ab504dc0c434cf9ec6f4
2.575 5.859036107 (12.206572756689873) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 176829 0x6e4323b3e16428cf8a77b61cf6d00b40eacc99e543ed11e1fd5c3a0829ce7224
2.642 5.184987707 (-12.206572737475266) 0xF3A3fD06A875A09d7Cd5fd18FDBE22493fC86aBD/7842 397815 0x90cad03d0120cf168d5bb348ba9ee066987896f5d1ff4564f50fd88aec4165c5
2.755 5.184987708 (1.9286448809772807e-08) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13314 250000 0x7d8f4c7f5a0818482926e63d674122a03dba9f15fec9a5450f97cdbab989e824
4.345 25.050000000 (131.40413671637668) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0x31464e29faf9ef8ab39696be80bb2bd304e5f94118de1900565630671ea8f608
4.351 25.000000000 (-0.1998001998001998) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0xabe56f8f3aa4cea095f52f7f90545ce3b96deac36a23ae9e74222709be6fb6e3
4.513 28.807500000 (14.152302188356641) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0xe8cd3a09cdeba03d0de2499ab5e34f719895db88b3e44f6ff7e6558736b61c68
4.571 28.750000000 (-0.1998001998001998) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0x5b00b82b9f358ac3f1b7631e0eef474de6aadfc286c33922cec7c99b60585c83
4.625 33.128625000 (14.152302188356641) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0x685356d67f34fcc3b147dbb0c6b4f24f62b09727820ea8aaaf30f48b7aa5924b
4.671 33.062500000 (-0.1998001998001998) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0xb05a53b784c520f33253adb981e4da106acbeb815bced5237a0c35b426753d24
4.924 38.097918750 (14.152302188356641) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0x451b27e0d83450f415fc24b76658aea30fead3c7620ab2ab5576e310bd97d1dd
5.004 38.021875000 (-0.1998001998001998) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0xe16dcf6a821f3978f4e6488dbd9f8b9c20a9ed0594047744d781f2d532bceb96
5.427 43.812606562 (14.152302187221133) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0x71e56b430e06da6f92e22bee1a0102fcb597157a8f2aae65649b08c2928753d9
5.452 43.725156250 (-0.19980019865897689) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0xbaa0b32bf043beb77dea689d24b2c6496dd776687f66db144171a0b1c2b3da40
5.807 50.384497547 (14.15230218860349) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0x1caed937bffb2c5ac76b1274b5629af465e50155dc7ad9357c866059f814121a
5.848 50.283929688 (-0.19980019905393923) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0xe295bd99a44e63c98ae705f232e3b01fcff6be1d16fcca30799264510a567add
5.949 57.942172180 (14.152302189245471) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0xdd42ec6a4524092c627e91d9df69b8fe1d296cccae9fcfd1d1a97f072810281f
6.018 57.826519142 (-0.1998001993100564) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0x2ca7bcfc9127e229459ceb15f43dae01fee246ee0331f31bbb085f15ea5a499a
6.052 66.633498008 (14.152302189362183) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0xde333b6f98c651d7452e23816d10407806680c284a2379d878f73735866840e1
6.132 66.500497014 (-0.19980019975817895) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0x68b9b51884ca5c69c00b225625f95501b205f74e748ac0b6123c29f74da963f2
6.313 76.628522710 (14.152302189353602) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0xd86f6bab77dfd82abf226bdd22c2e9afc2cb9c5205feeec0e77f8abd6f33f095
6.331 76.475571567 (-0.19980019962533035) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0xcf4eed3cb95dd58d4f370e546a12395773dedf1edb5c9d9f6006fe3ed15adb49
6.519 88.122801117 (14.152302188747196) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0xbde5129036acc45b9996806b048cef81b7836759fa1f539bc68f1980f0453248
6.528 87.946907303 (-0.19980019911252375) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0xfe885d3f6b6bf28ed149a88548c6291bf756ee839ccf826520e4198fec86e928
6.743 101.341221285 (14.15230218811423) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1136 207287 0x4d2dbefc34b5237a4e88f7c1f33a6ddb4f845c6a0ce823150e5e3c40ce1e31c1 6537882 6537882 / 1
7.035 116.309784909 (13.754646841060769) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 22000 0x1b323570f7bec77800a70a4c6b633145317ec4d9221aa12b38bd16368417f457
7.096 101.138943399 (-13.953488372221361) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1154 300000 0x1da86319591193399f08f2f3dd0b0f069e76baa6f04a49add40d01325bb30b03
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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.