× 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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Global Market Overview

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 #37 - 2018-07-04 21:57:10 to 21:57:15; Start Time 1530741430.8931787

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 61.000000000 () 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/401 250000 0x7b2f8f96764ec3a73d19b830c03df5bdff9eb04352e591c1a99ad87166713733
0.176 61.000000001 (1.6393442622816448e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11382 339129 0x26ea2735e45ce5c17bcdd1661a39267187ba4fcf10d973b85cd4ef0cbbc9971c
0.698 70.150000000 (13.953488370461658) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/401 250000 0xed0aa8790c7b4696a88861e634089bb810724e5410ab290f3447739ba40d2f85
1.302 77.165000002 (9.523809526395494) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11382 339129 0xeeefd30b3778fa5368457a9ee4ffacaf125b63bf82537db9912b311990bbd0f8
1.651 80.672500000 (4.444444441853876) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/401 250000 0x36b8630f71e1920ed7c49bb9a22cf3525dc56492912cf92187d8a6deb36dd393
1.974 93.369650004 (14.590890774112111) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11382 339129 0x8b1c04e619ea7a4a976a2afffa5a9edc9a5b5bdfddaa32714854b07cabd945ff
2.386 93.369650005 (1.0710118330226198e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/401 250000 0x626d24661c587dbc66c1e322d5a4c209a8258d035f354f5f7eb11427fbbbacec
2.599 112.977276506 (19.00452488683397) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11382 339129 0xc83ac58017d8c71ad89e717b1ef53c594fa1c32c7be8ed408af6ad913d56d561
2.984 112.977276507 (8.851337462914203e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/401 250000 0x714e11d9cb08aeca9186d239f116ef9044626455f3ca8cd2006751b3b7f21b87
3.200 136.702504573 (19.00452488653712) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11382 339129 0x4341f75d776570261e5af44e0bd053aa53d623dd99d4a1137df5419fe2437f08
3.691 136.702504574 (7.315154927994286e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/401 250000 0xc4c1e5158c66ed2b99fce505d2b7a1c0540509734b81b5bd91122766f54bdb95
4.270 165.410030535 (19.004524887153416) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11382 339129 0x3723c284d8d201eaaf8ca0f33073f8d2db3388a0136e6aa86a905ea585599a65
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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.