× 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 #1107 - 2018-11-01 22:18:34 to 22:18:38; Start Time 1541110714.6819015

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 5.110000000 () 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 191829 0xc901fa9b41d50225f9ad764ecf5f905584544be286f5dc40414a2cf33446a5fe
0.197 5.110000001 (1.9569471622351323e-08) 0xF3A3fD06A875A09d7Cd5fd18FDBE22493fC86aBD/8102 442815 0x848e5586f19991293035834adc38ec548f61010395015147df7c219d02d1ca83
0.275 5.753860000 (11.853245512013848) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 191829 0x85151a9e09be540bf7bd52ac68a56312e0d31f4b12caf9f4bd5793ddb2ebc859
0.292 5.110000002 (-11.853245492513114) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13530 250000 0xa91afd07388909e865f56bebd80f9b22bd7a0ae10f44bca485f21e34bbb562b4
0.708 25.000000000 (132.1155761984646) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0x606a47a3b97bba2f5cbb3f73e052c1b83f2d493f21109982d9f2bb0a90667af6
0.885 25.050000000 (0.1998001998001998) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0x0f46db0ed75d3bf0e0b9a9622b3192af059d6db0c998086b89c8fd852a3d12a6
1.009 28.750000000 (13.754646840148698) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0xa541cc7709c9f77acfc3cbc35171da0bce12dbc90481826fea6cd8a84ceac659
1.060 28.807500000 (0.1998001998001998) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0x94200e102f552dcd652f2649d40e2fc1b1408d269d07f1a5b1725c93348c6728 6626120 6626120 / 27
1.258 33.062500000 (13.754646840148698) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0x0341dc231f18386b4760eb7ef51f291de16835f1f8eba2fcf5b7355e252fa73a
1.297 33.128625000 (0.1998001998001998) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0xce6de8031ce65fa7e7d6202945d623f025ac7fc816d9840ae009285298ea4539
1.471 38.021875000 (13.754646840148698) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0xcc9d6612a879170c1bd854c0179d78c99ce5efe6620f9782df436c40d5b166aa
1.616 38.097918750 (0.1998001998001998) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0xd0e450827b7629895901ec5cdc515ea0cc0a3b257a9e7185ad7882ff5946e85a
1.711 43.725156250 (13.754646840148698) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0x243bcb679845207b0e8518cd12859896003259e7ffff2e06706d3eb0191b5d95
1.801 43.812606562 (0.19980019865897689) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0xf9fb08cae748790243c6adae5fb46e035f8d361d9b503ed339f393e09a611446
1.917 50.283929688 (13.754646842274177) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0x48beabacc13d5a851723fcb4ba4f6929a5cf9dd72502800e1d371d9baacfed85
1.995 50.384497547 (0.19980019905393923) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0xacac594ebb58e4f1eaba0328e1850e5422a41be0b06f31f75e446dd6c88cace1
2.104 57.826519142 (13.754646842268336) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0x2f3798acf26e6a44508e8568bee39649bfd64612e5d585d94b6e1d27cd502f61
2.177 57.942172180 (0.1998001993100564) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0x503b4a91be4cd06fc842248f8bb874d3114be407db73f9ed0096b101b9ecc083
2.188 66.500497014 (13.75464684168417) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0x7ae55ba3c054e1bb7136f3f923758182890eb502c5c7b8900f1ac22ff9186234
2.297 66.633498008 (0.19980019975817895) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0x669142052f7ae8f58e288531de5bd682b25ea11e4d3e2788a1603636f643bc10
2.491 76.475571567 (13.7546468413618) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0xe226e0e73e4e49ec40b0703c78f51e7fe09fc9c16a9b9c4b125cd20bad075df0
2.596 76.628522710 (0.19980019962533035) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0x10554718eba90657c88f52a10f71892e8e922c5261c8bc62eb9dee0d8d729504
2.880 88.122801117 (13.953488372657652) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0x15d2bb7a803cf0e12ffc5065925bfef9e332b179dfb8800773fd414cbf4e298c
2.922 87.946907303 (-0.19980019911252375) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0x3ab1c18b92e5832868584929cd2c9d81d219ec38499307f199907d4df91f73dd
3.000 101.138943399 (13.953488372634181) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0x41d646ea60ea0ea22c88136397b6a4e92781495244112b2a1a26a472ed465542
3.137 101.341221285 (0.1998001990127619) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0xcbd893ca9c0ec8ddb6b09fa275b895ccc6ab781459f9348bb8b2c9f0ab6c7a42
3.139 116.542404478 (13.953488372306493) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1334 227214 0xe18bfc57a26c2dd8f3661d22b4cbe4f9e94a94334844bed6534d7619da089e04
3.505 116.309784909 (-0.19980019909831004) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1379 230708 0xc529eacade6928eba5e1f1af1b4e513dd8f5148d18896ef0e44599e20fb15a8d
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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.