× 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 #486 - 2018-09-14 03:03:07 to 03:03:10; Start Time 1536894187.6909409

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 87.415449282 () 0xf666666666E8025c503209ac580a5aA4b39A090c/375 213092 0x18cf5acedc301211c72b50ca0d64335ca449f96b849e3874513e106d05b03d7f
0.298 90.912067253 (3.9215686271431087) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 254953 0xa11cea3af5f1a5f047a69c1900f1c163441f7cdcb6624cbec5d3c49d65d2cca4
0.365 98.779457688 (8.294930875216492) 0xf666666666E8025c503209ac580a5aA4b39A090c/375 248299 0x4c6a1d27a8eb019fe87199378dd051cdef3ce3df441fd9a7acdf128f34d03adf
0.597 154.550514330 (44.03036576977735) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 254953 0x8573fbe387d571cf9fe4604b033b762efc2f0747ce28c55aaa38059181fb82f5
0.776 130.969225442 (-16.518149608031088) 0xf666666666E8025c503209ac580a5aA4b39A090c/375 248299 0xf8a525ef2a690b901d822ded5a50127b525d789e504272eb1e772c7a47b7dd3f
0.805 222.203276699 (51.6654330130016) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 254809 0x66f3ffb6879433fe829eb411357828658a3f8a0442ee5c4b0e5f5fb80c7c3047
0.844 262.735874361 (16.71657055257435) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 254953 0x3655605be1e7d3c85ae41262d3f61969f6bd9a77a6b8e905a23dbddfefe7b10e
0.976 154.859615358 (-51.66543301298102) 0xf666666666E8025c503209ac580a5aA4b39A090c/375 248299 0xb9e7a61535bfb5753435844c1ec8bdc5e459213bc66f52106c270c3860172176
1.177 90.912067253 (-52.03817415061136) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 255039 0xea1eecb1ab3b33e8778586f850222038b91aa94389e7e32cdd95fbe3d7a6d294
1.227 447.544288385 (132.46467142520316) 0xf666666666E8025c503209ac580a5aA4b39A090c/375 248299 0xf2e79d0b8ac02dac39984dd68c048e0966d75abdb175240ff08cdf0ff351b745
1.270 759.306676902 (51.66543301274322) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 254953 0x18126047ff810ffa5189c9af170921c7c36627ac115aa4220dbca083f4dfae0b
1.365 446.650986413 (-51.85185185183957) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 254953 0x401b7e8284b08b5a3fd35e8d3c2cf0ec5762877745f5e56cc11135a6612da862
1.509 760.825290255 (52.03817415095823) 0xf666666666E8025c503209ac580a5aA4b39A090c/375 248299 0xe6e1912a2ff46af6dcc2be7ae9a70a83c8d4d8f6e547c982fdbc9593158b2f87
1.546 154.550514330 (-132.46467142527635) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 255039 0xcc32c024f99bf0bf22dd6f9b87ca78e3846e5fea22d5af164803fd2a53bd7bc4
1.796 859.914811591 (139.0612925327187) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 254953 0x9c7535b4a2f6aa82893cd56437862f44c3183c0fc711acbd874757e77b9f5107
1.883 764.629416706 (-11.730723390016548) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 254809 0x7a2c5164e979e9631c553e0f08f2f2aad8c64a61ff33fc2871a31526cffa1334
1.924 262.735874361 (-97.70498316596698) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 255039 0x6d555dba3be86c3331dc70f3072e555f30c3a7726e8b463088c110a3cc17dd56
2.444 859.914811591 (106.38731079981419) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 255039 0x58da7c5c16adda3b3cab8b0f2a8c889fc5fe880c8ec4003c706bf173149c387f 6327776 6327776 / 0
2.701 222.647683252 (-117.73308818192902) 0xf666666666E8025c503209ac580a5aA4b39A090c/375 248299 0xde2f38ef2b4af4ca892543c10409d3cd279683e1c7168c22385efaca50b4d9c0
2.797 263.261346109 (16.716570552479524) 0xf666666666E8025c503209ac580a5aA4b39A090c/375 248299 0x7c8b4fcccfe9b749e6035c4a7201e2d0321b6eabaedcb099b5caa2b9f62446d7
3.199 446.650986413 (51.665433012692965) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4663 255039 0x1e243a02d3224d1eada6714e15b540e6a4469b066ca5e9387df0ee4b9e3a59ce
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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.