× 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 #254 - 2018-08-16 07:07:10 to 07:07:15; Start Time 1534403230.4241786

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 25.001000000 () 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 186538 0x5db1589852ea7408bd15ca945070093cdfa7e885b3e0f1a92171e76cc5b3613d
0.303 25.001000001 (3.9998400063197506e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12013 362773 0xb0adaec762fc5187c74638aa7a19717161155788a27b15b37bb9ada83812d51c
0.428 28.251130000 (12.206572765968112) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0xd28dbb973ff81547414a20ce1a62ca73a6013bfbd75f48ea977a4e6ffb7de1de
0.694 31.923776900 (12.206572769953052) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0x9a8aa11aaaecd8f9f78ca345d8c84594294334ef57cc4225f16b6168dc9fb558
0.696 31.076243002 (-2.690582953206636) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12013 362773 0xaef8e30668324352e6153c9b1739c05ec3d69db1aea7d2f1c25a5e397910fcd6
0.915 36.073867897 (14.884934151536672) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0xb43f802fdd287a641d4eb55a255acd5f6ce2441d7fc7d8e3473109657f3db3a9
1.154 40.763470723 (12.20657276846219) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0x3feccbb27e8517c5cd5a93f73ebc7b84435d045a6058918205b07dfb4bf31d12
1.271 37.602254034 (-8.067855427363032) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12013 362773 0x702e834208de4032b3633fec410699b965fec9f39f47b3fb43456aa14508a3ed
1.800 46.062721916 (20.224634707493752) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0xfa5042270ad3d703f3fb72b13ea563b2c6313aae3c922492e6ff361a4dafa108
1.903 52.050875765 (12.206572769799928) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0x11737151e4e246f27f01dee7e7a5963d66275f952aaa83553210c9d72f2d987f
1.956 66.747916136 (24.742743820572954) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0x091e6998f368862c3a2e89f68540f4afbe215bb7eb793c28b46fcbefdba6525d
2.030 45.498727382 (-37.86160207203426) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12013 362773 0xaf3d838e4b87174465259a01747f0ab5997c7e22ca1a33188aba79be479ff1b7
2.235 80.764978526 (55.86126415408111) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0x6969f0bafe1de9f978a23a8819005d7d7810654b7582ed86115e103fc96716fc
2.536 58.817489614 (-31.44734321503308) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0x1758a58babd34500677287e2adf6eb9ab2894a26ee4c803febb32ee04d455eca
2.876 55.053460134 (-6.611044323999959) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12013 362773 0x14b2bec76078e41a3f6dde7daa8ed53fdc5165ed45cbf9d6267519465a3bc78d
3.055 66.614686763 (19.004524888157178) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12013 362773 0xc87f2e3f4cb4d095512d3536ed36521cfbbb92ff629126fd3f76cd3daea711de
4.076 80.603770985 (19.00452488905393) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12013 362773 0x6972ebe6d62b981b0e265062fa41f018bf87d22f721236f87839b396e80ff79b
4.133 103.128801079 (24.519365119597634) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0xa2d8a410e53ee96cf037b654a909c3b4a65bb87068ed22e360fd4c87b82cf51e
4.271 97.530562893 (-5.579842450593214) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12013 362773 0x254405ca9f93ce5ffe4f5d7de55ba5892a4f2ce7e039553f33bf4024f56b03a8
4.282 91.264425734 (-6.63803335519666) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0x2174be6add79f8df23080c61d2c943033ff9eed0f0885ca5910325cda2e0813a
4.799 131.685166097 (36.25998148822778) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0xb119f78bed48354d45ac52321a6e694202eaadc7e2179c673a42453e81dce603 6156461 6156461 / 37
4.908 116.535545219 (-12.20657276959747) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/604 216932 0x05dfdf265e5d847d84321910877a25693ea0c52589d0f9d54695e9e01527dacc
5.116 107.283619183 (-8.267322470548304) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12013 362773 0x17e54cd7eb1659862214cbf01fc34918939055e7077ed24fdfef87374c51196a
5.330 118.011981102 (9.523809524401338) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12013 362773 0x9a93cc1cb722729c6bab8d600c8f399b1790e4f27d92882a270326bfc2c24417
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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.