× 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 #174 - 2018-08-04 13:03:44 to 13:03:53; Start Time 1533387824.9232435

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 56.466746363 () 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 172745 0x89c4938c4250364fb3c4b2745b83bc96c6df90967c04181b3d6fae1773f0df15
0.326 56.466746364 (1.7709538168935447e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x7ac95b1887cc578291d11a310b56d4827394aef500f7db0f76ae7ffcbb6a456f
0.430 63.807423390 (12.206572767892032) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x32d50e1d44f8a474e26c4c0fa217a6546e9405a16b34be1451b881e41230ba1a
0.703 70.188165731 (9.523809526652546) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x76d2b00782b981448a1f0386df290029f31e85af49bce7db8b7acc2a9c51eadb
0.746 72.102388430 (2.6905829558216223) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x6691c2109f0c74c7305ce8e9bbe2a27aca6ec8185d92785f61e7d170b3295b0d
1.014 84.927680536 (16.33482324812189) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x7921d7ae8d33e43096f69e0108ca039611b67153625bb34cd456cb61b5e63042
1.024 85.097535897 (0.1998001997155911) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x6227d5887b50626b6059db88ddc0bb94a9f4648294b384058ff253030d912428
1.226 97.862166283 (13.953488373567488) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x1eddf3b80854df4b574ddbbad68bf56afe0326b9bd55dac0351396a146c51a85
1.400 112.541491226 (13.953488372579354) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x8ae4d1905c75be16a624bb934318e29b36956dd60cbe0905aed74be7bb552681
1.435 102.762493450 (-9.083898554609583) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x57abba2850b9ee4f0082d233ac94aa0b7dbaec5baf20af0c7ead3cee7997d72b
1.900 129.422714910 (22.964616607844967) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x3730751eedeef3de345068ef3ee0cea3fe5b49cf48315fb79b80c514aacf4b56
2.035 124.342617076 (-4.003776082605534) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0xae4249956ede67703c4d9d03af73ef2c0a9cf739778d8955d032f8a52e84a412
2.223 148.836122147 (17.932219132913982) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x2b78ef19c841837708bd2cd3071033a1ccd0d5bfc815de7b1d1be4b679a861a1
2.522 168.184818026 (12.206572769887892) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x825742cafd0a131eef000d77991302fd6a06ca7c73f0bf52173f6b39966ad614
2.737 190.048844369 (12.206572769753848) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0xe03f86fa774d449e2e13dbece5afb49e890cd02b71f407fc936e20da72529316
2.752 150.454566663 (-23.256317806624843) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x966922226d73e9e803f0ecf9f644a5506316c7d18e4593cdc79dac57e0373cc6
3.196 214.755194136 (35.212984084721136) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x835de0244c278e255ad173212a89b0c5fb54611e3ef5843ff8099c465189cabe
3.416 242.673369373 (12.206572769673883) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0xec6a44c3f32d8afbf2babf008f528ee657ddaeacc797c4ab0e1f1971400e111d
3.599 185.003299830 (-26.96900424821933) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x833a0bde6f9d031fb3dc807f55d97995a8a0f1f4d2411041cb6a28d5ead5c065
3.617 274.220907391 (38.855794689439946) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x4ff49469da2556f899cbc109d62ae3097b329f30aa90cfce8f1c5b54ff025656
3.808 223.853992796 (-20.2246347190312) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x2b4dbb66e96ab15bb6d2458af69d11a7c8f91f1e222a2408863c507f4941bf11
3.841 309.869625351 (32.23227514406503) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0xb90e16bfbea1960180038a1e01d02698c3c332185d121f3c674b7e81503614a9
3.977 391.210402005 (23.204419889342002) 0xf2F7D4B9E10c3d871dA5F8002350A34981BFcF33/336 309034 0xfc36a01a27bdcb569511bcbef5836235000114dc8cee67943ce3c07b7518d2c0
4.093 350.152676646 (-11.076280041814197) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x209996d39e047675245b7e4fdb42bf2abdd0b537f6ff1e3a0e30c9a4a8d973c1
4.324 397.364145342 (12.631546824710224) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x2a4152d215e6c78a78ee27e1725bfbb6f975646a1b32306479375eafa2501ec9
4.573 480.810615866 (19.004524887327136) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x3611fb5f791247fbefbf431d2d2cc70ea151f4f64e30630746fa99592bc8c404
4.879 270.863331284 (-55.86126414997433) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x6935b1958b7d56030eefe4695a0db06bd73d8f47f1f964700e6ebe757100dfbd
4.920 742.875961232 (93.12308074327703) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0x08387209b10abd5d65c28a8929a7307fb4d29b94b32daba67d590bf6ea12950d 6086931 6086931 / 37
4.991 581.780845198 (-24.322543809389753) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0xb8e5b1723421ae4063a28136cda4508a9cc0e6487ec90bcec7cead1962a5e564
5.228 657.412355074 (12.206572769992453) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x88a21cb4216e4d93affc0d8ac7dcc1c6ac04fc84c4ac45f4e5f656eae54fde84
5.229 657.412355073 (-1.5211153126080177e-10) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/564 203139 0xbeedb3e5a9e022b60f5d7462fcfc3fd125043f0457ad8a05efc40be1091cfcab
6.118 580.619605987 (-12.405616575560817) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0xb2559b587a010b6008b7977a1f785814fb9ffc8fc313fa01ba8492e87372279d
6.936 327.744630855 (-55.67699935240511) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x253b9245564fec59d184a631a10de8a68099f98513c5eeaf369440621b9749d5
7.368 396.571003336 (19.004524887240162) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x42d1df221af82a13fa80a47264a76087256521d106c5ac4a4683d4403710abbb
7.606 479.850914038 (19.00452488717521) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x2bc761c5e1d465950cbbd1b3f7ee1063b95fda5ee48d10fd53efca8f53b4f05d
8.987 638.681566586 (28.399828400046555) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11833 347815 0x2a6907842a952475af979d9c63d318f92d77de991bdeab05839637b2c3dfac81
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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.