× 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 #1583 - 2018-11-26 09:12:33 to 09:12:38; Start Time 1543223553.044017

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 11.000000000 () 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/313 500000 0xba2d19a16ba8210bd02af8727835d023b6b9f35cca1490e5d734585497a67a22
0.586 11.000000000 (0.0) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/377 500000 0x25aaa26b9d6b7d0699e31543b69f570935a46373f0ab3a303976a4483467b2a6
0.920 38.139974464 (110.45986392965173) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/313 500000 0x142b69b34ea407e02c83b32aa8df8e0d1987eb010d339dccca319c1c944f03fb
0.957 12.429999999 (-101.68078880012466) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/313 500000 0x7f500640b03247523bd301d73be5fb4ff293a629544553854ba9f8956801abaa
1.070 38.139974464 (101.68078880012466) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/377 500000 0x4e93769e27ca98f8354e54362659d720bd364f1a628bd3b8cac9d0912451e9ed
1.420 43.098171144 (12.206572769213327) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/377 500000 0x934aca62408be215035f7471a502ef19dc3307b37f9c229e35ecaf033713d0e1
1.543 22.856054500 (-61.382319165599874) 0xf1aAcA914cE6da8b2658d97F13E0f118e9618716/3889 21000 0x4ec1ee9266c5aa2f0e45a046a505333970d0275043bef2bf9972a9b7e5c0bb95
1.553 12.429999999 (-59.09447598509758) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/377 500000 0x8e33679242fa214efbf04ab6981c6b3028250042882a76648ab552323668cf9f
2.034 48.700933392 (118.66638175146853) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/377 42000 0xdf79b1c625b8fc54625b0e5ac7dfc885ffcba977880568b1747e29aca0216373
2.294 48.700933392 (0.0) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/313 42000 0x0803ba922088912bef6bcb324d8b2121fbc62c8c2a6c18e9a0ea8a00e0606d9b
2.532 43.098171144 (-12.206572768480148) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/313 500000 0x3bb9e28a03531a2bf2d77cd4e5d0dd8d2daa8f0a1c1d511e4e050c1b9ac71c6b
5.138 134.000000000 (102.65699331484002) 0xa8660c8ffD6D578F657B72c0c811284aef0B735e/56739 121000 0x552d3adb3ac0d146b04fae267c2fcaca2a8999be7048da299d541e9f7ae2eaf7
5.788 110.000000000 (-19.672131147540984) 0x77521132FAD812cedB7dd5b4f34835E71821B4EB/542 150000 0xe7adac145a902142c931e3a02bd99908b8fc4664a8fdfcfd52c1d1ffb9d293bf
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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.