× 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 #1258 - 2018-10-29 19:36:54 to 19:37:14; Start Time 1540841814.288604

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 134.000000000 () 0xd6cB6744B7f2Da784c5aFd6B023D957188522198/35852 121000 0x00ee1a648981b2fae5fc42d17fa368b5b2a92832182807eaf599dba1bd0c8ade
1.555 36.301641381 (-114.7356629410618) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1313 191829 0x428f3164633308774e2f8e6f0e29148b474dba5600d072a46063ae59ca533fe3
2.147 5.000000001 (-151.57577438867511) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/9043 359617 0xb778814815f79e87fd7bea686c830e317246ce2b6062aae49231aff31297c199
3.466 5.000000001 (0.0) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/20884 359617 0xc48b0aeff1d0948c0fafec18051e5be991b30b4b92c4025fd5cbb6222b5e1b1d
3.657 36.301641383 (151.57577439102002) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/9043 359617 0x16d2089e315402b55320d59417e034437a3e7a0b67bcfe0dd43f92dee6986b51
3.725 40.875648195 (11.853245526009912) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1313 227278 0x0c6f9815dcd2c0873567cffd015132e69f63a408fa3c27fa30ab5dc806bffc2c
4.081 5.000000001 (-156.40388574227526) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/18625 359489 0xbdc341713c3837e3382ba46ade854d57b46745c6a57a1ea0e3656950ea38cab2
4.254 46.025979867 (160.80428037690143) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1313 227278 0x6f882cd8fdd0831763986e9c06d85498a2eade619cc74d808ea1407430da9aa7
4.273 41.746887590 (-9.750375944129502) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/9043 359617 0xd7e52d61d87d9f2235de0dcec736f9bcc37116115692489446e0b54b638da2f8
4.273 5.750000001 (-151.57577439167156) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/18625 22000 0xf8e6ad43f3195ae5a1239b76f801b2a800920aaee69fdd7adf2f8bf20c8542e2
4.394 5.750000001 (0.0) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/20884 22000 0x58905ba0fc73c423985fdb6a655750d5a6631d379c88e72c45280c971a89ffa0
4.474 51.825253330 (160.05228171246932) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1313 227278 0x9281ae6fd6465ea00406beffde65513918e7352b31f4fcc5a8b1752044403283
4.592 48.008920728 (-7.6453431663246905) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/9043 359617 0x0a1e302ffce1806280c3e4d2e0bded1c8a3088c49b9cbbd58d84281b9a2a4138
4.730 58.355235249 (19.45451346078893) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1313 227278 0x51941661227f69aa53067cec11a13211c1b590f4c1aa8991105a31b662e684ad
4.936 55.210258837 (-5.538612652217049) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/9043 359617 0x52635a26353166ef6c6b5177d2b1e3d926f2f40efccdc978cf9b8d7571745dec
4.939 5.000000001 (-166.7830692144815) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/8399 359617 0xad343b65663eb75ed7a3a84af61c7ceef0ea68808ba96934105bd32451192e35
5.065 65.707994890 (171.71465541508988) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/1313 227278 0x3da15bc273df8c9ba4cc4a92189a675b59755e5638826437473b170c27e215a7 6607166 6607166 / 7
5.158 63.491797662 (-3.4306513721498906) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/9043 359617 0x4beef2d9fea51ef68f09cc78e64c30ad030cab033165958b548ce12e5e905692
5.162 5.750000001 (-166.78306921501223) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/8399 22000 0xe144a7603c16d478b97f30cb144432a4d7528931ebe9c3931eed513f7097cf31
5.413 73.015567311 (170.79942316305016) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/9043 22000 0x238225cab19cc1b81c342a6fdab400acebded38fe395dc0a2be913851ec395f0
20.150 6.612500001 (-166.783069215578) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/8399 22000 0x6a6ff4a7a0493849db54cb67b64d6703c760c3f6a6c73ec0a8a2cc709a24480b
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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.