× 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 #885 - 2018-10-10 06:58:20 to 06:58:35; Start Time 1539154700.8565667

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 122.000000000 () 0x0dB368a4f0d93C8A34D7079b1E76FB8666b750a3/894 45000 0xcbd8a9a7f42de35d239109e3c5c4b181e681ead19614ab747124c23116944788
1.756 40.250000001 (-100.77041602279957) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/19875 22000 0x254a7b525cf26fbbf80a63f2cbd4d143e38cc3a577f9e8ee2e699a131813804d
2.174 6.000000001 (-148.10810810170344) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6781 360063 0xf7c459500b912a6af0a5681300c6ee44bdf981d5a7d6cb5ffdbf7ef805608d73
3.060 35.000000001 (141.46341462724567) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6781 22000 0x3fd9a9a461e55c00179cd9dec3525ccdce16a3c8e3908764cb088506eb07dea8
3.179 6.000000001 (-141.46341462724567) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19804 359551 0xa0e90a9ecf96d9515b01d9c7af7f18b9b06b9689cefe7a388043cd799ca316b9
3.355 20.000000001 (107.69230768402367) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19804 22000 0xf261994b2cf7ef31d1eab29c1279c2059375d09d093e2b32c0ecc5c1727748a8
3.549 6.000000001 (-107.69230768402367) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/17865 344999 0x789cc2ba78b5d0006e6a8d487353b2617d944362bbae088239b2d4647a85fe33
4.249 35.000000001 (141.46341462724567) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/17865 22000 0x455d2a63b130159b3114511846b88ee3448c47eedfb8e530270f1edbf2cca2a0
4.411 6.000000001 (-141.46341462724567) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/7671 359551 0xfd84949bc86d3f52269c02c022dfdaa3e34712c35bf3d6712b12e0e2ea2eb79d
5.075 35.000000001 (141.46341462724567) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/7671 22000 0x8c922c23f04054bef87057978d5009ec12f5b821d1b772e8397fb697f0f671a0
14.213 40.250000001 (13.953488371722166) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/7671 22000 0x91880b71acb63633a9f3421392c44778da8bdc9ae39106aeee33227617b4bfa0
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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.