× 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 #181 - 2018-08-05 11:55:22 to 11:55:32; Start Time 1533470122.1652505

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 8.096374185 () 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0xc5a002ded9e3f205bcb939c1726a519975ba5250f5d10dd90ead461800ab2468
1.166 25.001000000 (102.15085777204231) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 187745 0x2532a627d1d0ea4b149b57331c64253f2f0cfe45295c0c5143613e70368bf366
1.583 27.501100002 (9.523809531065469) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0x0d76bbdb6d40103ff6d3b5702fd752e71562e468a359487030d257a0b364964e
1.920 28.251130000 (2.6905829523701357) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0x7fc70ceadcdc86c3654b0fc482c029e897abec21e62a7477e8a54744a87d5e8a
2.358 33.276331004 (16.334823254524686) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0x9011f8863f5839fde4d806a83e2e688369e40de919d537236b7159e35bc08689
2.646 37.677458542 (12.405616574282359) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0xe13aa4662de20e8aebed34d5338afb508139e30344fa9a72b01da6114dcb6067 6092550 6092550 / 6
2.847 33.342883666 (-12.206572768419404) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0xd0752bde77d174cc80005828b33336362c783b72660e59cc525c3eaf698d4a80
3.690 40.264360516 (18.806509948629717) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0x9b1332538bdcedf0d259dd3be356a4bd5a20d0f6ce63f3535c4ac00d3e5b77d7
4.721 42.575528152 (5.579842448274015) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0x1a0c743686eee28a9a07b67f6c3b1feb6b6e679acda46dbdadadfc9437f9efa8
4.817 48.110346811 (12.206572768379234) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0xa9488ef7c24705146ce75cebf2483017a51897bc6765ecb8253a67309f07b180
5.362 155.434393394 (105.454993801273) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0xfc199c72285ac555811c281796ef4e59dd0f280c7cc39d5e6a4dd6d048826484
5.912 72.359404916 (-72.93876224404048) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0x653b58a3f54729785d04b0420dcea920c615fa7a8073156bd54e0fa191333458
5.945 54.364691896 (-28.3998284031108) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0xc68be8dafa708036a55ce0aa83d07f0b75560e57fef4dbdaf01af320ff15ccb2
6.423 61.432101842 (12.206572769174612) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0xfe242ab96fb9e2297b9812b0fffea730e2821bbd888bf25b10642f68c4b73861
6.491 205.561985264 (107.96485044612889) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0x004bd67cbdf5bd0fa7f40061bd096d899637cecae8d07880a292bdefc86efb69
6.628 69.418275081 (-99.02071516856465) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0x4fecfdaa04d70960b4e473d8269237941eeb6aa5716470107374d26007685cf1
6.750 78.442650841 (12.206572769279916) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0x1c9452155536494e73117783dfce1cb47e9d252911dab8f7ca1c5a8b3d511c32
6.939 88.870118898 (12.464641011282469) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0x0d1fc55c4003cc0e20971dbdb2238cffe491436076624ee3368d329c57ec5d8d
7.247 129.283805470 (37.05061615469898) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0xe1e6da3f9602ea8b8c1b1865b34416443ebc8fe69f268e5925bd5f993dc28881
7.345 48.719876225 (-90.51939654039525) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0xf9d1138efab1c70dd74d8befaf6c774fd6b57159c5e8f9cc0ebf46eeb3a37a6a
7.449 59.801161087 (20.422371802696833) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0x1185b79663dd704ec895a3e9d1ac5c6b013357e8cf189ce59856b9d04068fd60
7.624 102.200636733 (52.34445076110823) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0x54c1e61a0ee812446c12a2d16b8fed3bc1fd3d57ca5a2092e90fdeddea853db9
7.730 117.530732244 (13.95348837298206) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0x99a673e4591315e9c9be4c15f57f6caba1cadd6052567d22e53b5dc9cdb61ed4
7.904 135.160342081 (13.953488372387527) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0x948a19106a1e9e9796fd79b37a97228a02849d565a2fa0b4ba633c5597401409
8.413 178.749552404 (27.771797632892316) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0x27438db54e36d865c273e6d755dab65b4e6c0f00c0561f83df9ed910702d42db
8.631 87.554879949 (-68.4890383905566) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0xb0e76a2f6dafca3c87ec22f04ce1b048e35c8ab23780b2a68575d37f374f74e3
8.728 178.749552403 (68.48903839006276) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/571 218139 0xf3ba915514dd7843d34a797bf718174c621af32123eed88561a1a0f70f7b96ab
8.980 105.941404739 (-51.14890082559545) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0x6891716d439307d822c8bd56bccf7fdb16c03889977ab9feeb8b4911644e6d5f
9.950 156.433404620 (38.4884509334989) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11843 362815 0xf44019cf5f81fd529b41ff6c67d03d1cc194394ccdbbb0052128a495cd5e531b
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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.