× 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 #1106 - 2018-11-01 19:27:53 to 19:27:56; Start Time 1541100473.423668

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 25.000000000 () 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0x2c4b8c56c985e30ba0af7ca4abbbc020dd5ed2fb04b36d4a75c0b4653261f767
0.107 7.000000001 (-112.49999999023437) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/27392 359617 0xc44a3ee5fecf2d1f8ad19caf5e45a8387086005075f1cff9daacdb0cf4edc8da
0.133 25.050000000 (112.63650545046376) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0xffec02c367b0b372c0aadc64724898ac486ee8fc127f118b81a06f1f0575b5fb
0.391 28.750000000 (13.754646840148698) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0xaa2b6d4092918e5c1fb679983412ed00d79730e50d7791953cd4ef0f1bdf574c
0.428 28.807500000 (0.1998001998001998) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0x533955ff8033eea1c1d17a74300b55a1fceab7a38968a06fe8426c8c64a7062b
0.487 33.062500000 (13.754646840148698) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0x0e7851e9ff60a0eee17a46066c00f62332e957fd90322797945e4645194b3d19
0.563 33.128625000 (0.1998001998001998) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0x5974dbf46fee85a3cf0ceb0c6fdf3511aa61e92329be927dc8d42ec30da3002a
0.833 38.097918750 (13.953488372093023) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0x0a309164d6008c59202d7201779920445b12cdedfd1ab9722afb3babf06005aa
0.837 38.021875000 (-0.1998001998001998) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0xcc47143396ece89739f2ac4b9a37994e9773c6711c3804dc3dc2b144457c1dd7
0.943 43.812606562 (14.152302187221133) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0x7a5581c3954dda05589de7a22226717363bb229682f71303e1d817dd6507b6a2
0.947 43.725156250 (-0.19980019865897689) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0xef31cfa69d687a028330658dd5513e20b3f1d72a7b0484fd682c276745a4a8cc
1.116 50.283929688 (13.953488373082537) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0x8fda4de9eb30771d2f57b6b3c5c9b3a6d75e20c07e2a7efc9bc393f06bdd4096
1.122 50.384497547 (0.19980019905393923) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0xa433bfb1a4fa92b3065affb9062100be6b8594f34811d3b7eeeabfbb41c608ae
1.262 57.942172180 (13.95348837372461) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0x1d7859c1fc8b9cd02af5a2603d1b759ed50d7c6bdb2cd27301dcd6ceccd50b9c
1.282 57.826519142 (-0.1998001993100564) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0x0bfcf9cb847dc138d873c4eaca73f8cb91363a6b10eea05f99740c5bdb8c4aa8
1.895 76.628522710 (27.96771814432383) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0x702971f67fa85fe0c09589c0e9036fab4b9811aa1ce6406f98a85a4f67344dcc
1.896 66.500497014 (-14.152302189353602) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0xc26f06949fe1c5a5206f61666183179c3013d97869cbadebef2a2245668e46d5
2.239 66.633498008 (0.19980019975817895) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0xd90f2b4cdb1372d445af7139591f1f0fd38919a2f270862cc550715ba478cc0e
2.559 88.122801117 (27.771797633442535) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0xfcb5fafd553278bb3f65d04306204f397604c0a0dd803b6f73a139ccfaf8f1ae
2.935 101.341221285 (13.953488372534906) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0x974a177e6c31841aacf4029de2c60590197f1ad0481fb71e529222f395ce7993
2.942 76.475571567 (-27.96771814312961) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0x2648bcea9bf419f54aa77321117c66ffd3e7a9f4c68125a73d8af4b593bedd36
2.992 116.542404478 (41.51616728346469) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0xef7232ddfbe2a88e9056a7e00aacabeac60f77c06374fef469d0ff063f2520c6
3.124 134.023765151 (13.95348837305828) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0x0faedbc393a07fcfad969e0dc3bab75fc40bd3f22d1e8d568c343188281588bf
3.129 87.946907303 (-41.516167283359216) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0x8b52ff9e781db8da4ce05dae6a6e00df848a27d369a0660ea25531f62c20f9d3
3.166 154.127329924 (54.67779089514653) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1333 227342 0x47c6600b360fd7684c38961bf3703b2f9f09d979d2320b3840cd99cbcb151406
3.207 101.138943399 (-41.51616728305614) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0x2d91a4e78dedcb8153a18ab6d7c0fa7000f990bf034acaa728c925b82eb2b727
3.247 116.309784909 (13.953488372221361) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0x614fb616f0cf8802474428c64c85120d2c8853450d0e8e36545121bf58e3e5ba
3.368 133.756252646 (13.953488372576617) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0x5d25619c3ce6150c8fdcac091e2a3f430958edbe7b56926faa093f65eaba646b
3.432 153.819690543 (13.953488372157718) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1377 230708 0x9260e2b2bff3b11049101e49f83cd442194ee5837a39b6a8fe15eca57774be7a
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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.