× 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 #503 - 2018-09-15 17:08:16 to 17:08:23; Start Time 1537031296.7274747

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 21.841000000 () 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 192021 0x7859a9e707dba106b078e0ef0338cb7d4af31d65399491c15602f078cc1285b0
0.237 21.841000001 (4.578544938313755e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12679 362815 0x3bb809659122016f28eddbc256f839b5429b2b7ecdd9cd9389e9b078ada90b34
0.364 24.680330000 (12.206572765391561) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x88165ef0a85eb861a9bbec8fc3f0898082debb4cc6876c9c477870d0788a699f
0.626 27.888772900 (12.206572769953052) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x455129bd5f5fb0b1d824aa25fa58fed7b01740c58009dc469c3bfa0e9e6cac8e
0.640 27.148363002 (-2.6905829522756624) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12679 362815 0x614122428a4f662443d9872d6fd9c8bc7ebbde8f7feb01836064cc893219100e
1.008 32.915218272 (19.20250224072578) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x9bce757188a1e42902fe70006930429c9e99391454bdf3eccb175a10ca81ce23
1.034 32.849519234 (-0.1998001983783665) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12679 362815 0x638b69174bf6025027ebc2eda5c17c54d00adacf582435fd65a0324e7a2a181b
1.174 5.750000001 (-140.41376561202136) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14688 309155 0x6144e27d56ccd52f40e7b9369e569e386fc4c9aca44927f4bff1dbbc615ad36e
1.311 5.750000001 (0.0) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5479 309219 0x204d91aba06dc5fe51f0e51c6d3a73727c22f023e093ad8350c2a1f9a9d76b44
1.320 39.827414110 (149.53640865191383) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x6a81b695476f9162aa83f722e3f4a59c114f452ac0d0101ec18c5a432935f609
1.475 39.747918274 (-0.1998001984242645) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12679 362815 0xc5930c432baf348932d2eeff24d095e9aae1a81195be38ff0e4fdccc175bb33e
1.657 48.191171075 (19.202502239912068) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x65589174bcc77095a987df4ec5c31f72a7fdcffb19eb8f7dd12c15d5ee60fd78
1.813 39.827414111 (-19.004524888296697) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14688 22000 0xc28406fb55d671ccf61ea5c1e43d0ff2d79de34584eac6d9625999012ca16883
2.085 58.311317002 (37.66892577756494) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x58ae9b5679d67effe9769d4dc6aa081e9cfd91e09e97d860b464fd706a442152
2.205 48.191171076 (-19.004524886945806) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19220 22000 0xa3add4cf1c03aaafb9d18971c9dc759776155d9e950774272f49bd5d87b4402c
2.217 39.747918275 (-19.202502239475344) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5479 22000 0xed34ef52d94e29c7c6a3b36bb0e43ee66a10da85ff525c1d6791704851185a13
2.271 5.750000001 (-149.44823658859042) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19220 309283 0x3c57aa269d49af1e14c5dc8839c938473760c5d45ffec613f098ff5e87a889d3
2.368 48.094981113 (157.28478397029306) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12679 362815 0x9d3fd728ab752b1d96e311cc7b222e230aa8ad7105036bff50d0d093114d81f3
2.507 70.556693573 (37.861602070839226) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x544777bbf1ef5f178e99aa24ce6d7edf2aa7e8e217691dff1a41c26118f076b2
2.622 58.194927148 (-19.202502237680548) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12679 362815 0xa965522d324f087da0e8e1e017ef073319be545e1e52b1957de84c785c7a6627
2.646 70.415861850 (19.004524888172554) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12679 362815 0x035079c7289b5d6c8232c684ea1dde5bbf0d33b5a6cb981ab559801636a1c80c
2.790 85.373599225 (19.202502238324147) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0xe8c93db159b78f10f98e80476b1946e20aa4e3179d03d0398584a240340afa57
2.953 5.750000001 (-174.75955712969963) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/7189 309219 0xe0e15214768b2bb4aac38c69836c9a736ea623af572715fd5edfd50dd0a4caed
3.243 96.472167124 (177.4999878687027) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x98d75f67a7d7635c66c988c7e36c9053466a521eb53ad7d4a853930465a83bc0 6337398 6337398 / 1
3.297 85.373599226 (-12.206572768527915) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/7189 22000 0x4b26aa89985d955f1c34924094c50e4bd41f22a7f5791a1914b4ed8caf41c755
3.344 85.203192840 (-0.19980020017502254) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12679 362815 0xc9156b984d2cad35a24328374fa28a1484483367f90439dc7f6dea998342c5f4
3.664 109.013548850 (24.519365120443652) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0xcb83f425e548a87456bde1dcaead7906261d8d70e5ac932b7860b8c99455fd10
3.781 124.197243476 (13.021433934991364) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x46a0ea29fce144c3844e06661fa9064be5203fe5ba95cde5407ec3e04ad41913
3.934 142.826829999 (13.95348837320781) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x27e5e1172fb7573d7d88611e69682c4ef5c6863c45a5858e92f395b78784a8da
4.528 164.250854498 (13.953488371578041) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0x612e8be8f9bd3d68589bdfecae5f387557637af279438cf4fca3f767a85d0b06
4.542 103.095863338 (-45.749573179734824) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12679 362815 0x2f66a7e83294cb0f6b082adf8d2ac73719016ae35029be37c9c07a0c980a3d26
4.851 93.723512125 (-9.52380952429341) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12679 362815 0x3420ce13ee4eb0deb7dc5c1af85ba70c46dac78dee19a3b823c63170e874b3b3
5.514 188.888482674 (67.34673142000463) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/747 227470 0xce9b5ce1d600fa29bbd4b9f339f124152c65b507e247f7eb06fe2d04c269d0cd
6.299 55.419846737 (-109.26245229442478) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19220 22000 0xbacf1306eb15ceb22ffff656a884b71a7b378800b03fe948c7fa1c141155c426
6.300 45.710106016 (-19.20250223930212) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5479 22000 0x1c964f1a2169979b52852ac4cac938ef2481f9d9984cbc1501af752a397cf600
6.357 45.801526227 (0.19980019754700204) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14688 22000 0x6358130831813d8049832826f3158714e260ad46f5850e09a13746a7e9d67690
6.520 98.179639109 (72.75689533387012) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/7189 22000 0x540ba094f541ac29a9846a6e40289dfbda3c2fc63957c86de643190fa25774e4
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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.