× 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 #747 - 2018-10-07 14:06:51 to 14:07:56; Start Time 1538921211.2152631

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 9.000000000 () 0x389A98E1949d6892554E7421e7Db0c120E98913C/364 145825 0xd96f72d1857828912c2e01db4a6060238ab9188d44521b6b91f3bd58d92180a3
0.221 9.000000000 (0.0) 0x389A98E1949d6892554E7421e7Db0c120E98913C/365 850000 0xc6e6bfa12567e7378f66cf4b25ddbb4b9d0b37908eed40defb78a80db40afa4a
2.589 21.841000000 (83.27226743620506) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/860 192277 0x8d59e874d869511c0b854610d38eb1500f7670cec800393ae0418f07d0009290
3.253 21.841000001 (4.578544938313755e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0xae5f8fda040636906c3992de6e427b12708b5605b1ab55c70909e2ffee549001
3.465 24.680330000 (12.206572765391561) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/860 227726 0xc96701e24aa15415b059fc3e0261b73fbaac2c25123db9a4a9d52fb95528cdfc
3.747 27.148363002 (9.523809531159745) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0x0b644295cc4ba27c5e378025a97caca17818de6250896d9bb043570074486a31
3.878 27.888772900 (2.6905829522756624) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/860 227726 0x33cb7cada0600e5c70e723ec9b3ff2b81fc30baae45c526a4212c016b0950435
4.194 32.849519234 (16.334823254679826) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0x9846f37f8079dced2219786edad7ce56ce8dc4ad2b435d1aa4f87e23d249285f
4.225 32.915218272 (0.1998001983783665) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/860 227726 0xd0b945e8e3f24041b431600bd441d722ba0629e5e2d968ca565bbe0a6f2ce16e
4.434 39.827414110 (19.00452488906741) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/860 227726 0xd6de00e38e6bc6939df7de60fd0e952ac6c0d7765ef6a9cb7ef582fc60776b52
4.709 39.747918274 (-0.1998001984242645) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0x398f6c2c75e7bb8211570db47cca8d6589e0f520a8dbec55d8fa907018b53ef2
4.794 48.191171075 (19.202502239912068) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/860 227726 0x7d31c9645381d589eb1eb4a898d7a8dd99040b77b06d90287e47aa0e223fc098
5.512 8.000000001 (-143.0515517095752) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/19078 359935 0xe6d18e9b5baccd13294769cc28e139fc97e366c7c5ea3237541cc62178dfe090
5.616 48.094981113 (142.95389824810272) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0xb533c3111b2940e804db8a283e0bc9d788bef63d39606bf73efc18f0afdcd29c
5.978 8.000000001 (-142.95389824810272) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6513 360127 0xaec3780a78fa159409b7829b4e46acfdf4a387dab56b452c9c992dd1fa8b757f
6.510 103.095863338 (171.19604723143058) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0xe525427a0f14d13b03393c6b68a382d8b63232ce400aff39a457573c326f2007 6470740 6470740 / 2
6.638 58.194927148 (-55.67699935588993) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0x2333d873d5881ca9991923f864e7542531bbe33f2ece433277e8540afaae1642
6.667 8.000000001 (-151.65792700100673) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19627 360127 0x1510772857dfa2717ca5d03cbb2bcdbf79ebc27ae2b379fc25030802171c18d9
6.668 85.373599225 (165.72907088378622) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/860 227726 0xaebcf675b5927616dd619860bdd820a0e67214c119fe976ca55dcbe888b220b5
6.935 58.311317002 (-37.6689257767959) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/860 227726 0x0323b060115bae8a176d5a45da846cda62bfcc55fb4fdecb082ef03058167ec2
7.011 70.556693573 (19.00452488769244) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/860 227726 0x0c80c6ec85df652028980c1874124128d542dc6e41f277cb32d58edf8e61606a
7.240 70.415861850 (-0.1998001988080908) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0x090c53b092f324163024da3ed7067f7a49732bdf6d0a2d9a41e07b3d624df087
7.675 85.203192840 (19.004524888622427) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0x3c73e50d205ff30807a500db6524e9af6db0bbb34f3cbf61c792e576bd0437e3
7.730 8.000000001 (-165.66641224556503) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/17727 345127 0x019701a9da37709db59e59ef13d6bca1f748da6f58ae812f3c44f14ebe5ac067
9.157 93.910959150 (168.6000403974355) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0x20fc1521f1222e106180f8e4fd2a8d0ac3b03395ea648b80a520718f172690b2
65.567 113.405449672 (18.80650994561438) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13045 347815 0xb74668b7dbd119879aa62f3880a43fb1cc9f17cb4141f7fc738cc5f0232a3885
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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.