× 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 #679 - 2018-09-25 12:19:26 to 12:19:39; Start Time 1537877966.0142787

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 72.600000004 () 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12873 376025 0x60cf1ad4d281f5a84eb11eb33cdc3e864ac5d359260c42578ad06bf847f97889
1.710 112.200000007 (42.857142857838596) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12873 376025 0x97aab8291d83f9897f0029f34f93168304a00fb5f350f8cdb5258b23e3be7d52
8.082 115.515000005 (2.9115341526252623) 0xfF1b9745f68F84F036E5e92c920038d895FB701A/53166 147593 0xdefbd14f6d8ff1a7ec291f0d1e68b669c2a74fa7e94b1b1950d491f1ba3cc9d3
8.254 135.762000009 (16.11528313603866) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12873 376025 0x0265eb1e52c464f8bb57736227c4ea735b211519dab487a258c3773ad6278d40
9.851 135.762000010 (7.365831380872591e-10) 0xfF1b9745f68F84F036E5e92c920038d895FB701A/53166 147593 0x9448c0a30f5b5f29348919450a1082d5ad7d350e48c0717a089e6e624cefe8f5
9.998 164.272020012 (19.004524886817503) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12873 376025 0x2415c1a4a4d42b6d285f91873b979c1d741249422ea2ca3ffdcef1540c25d982
12.593 164.272020013 (6.08746395109713e-10) 0xfF1b9745f68F84F036E5e92c920038d895FB701A/53166 147593 0x6a83463c50f0e45b65b75b550dab299b3cfeee8f8df57903ba89515fefd961db
12.773 198.769144216 (19.004524887012437) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12873 376025 0x02c88610df77fb9d9eecb8bdf4392e20f9e91838c09f6f4848e64825971ed68f
13.524 198.769144217 (5.030961943020677e-10) 0xfF1b9745f68F84F036E5e92c920038d895FB701A/53166 147593 0xd83e2ff091ae16c1e56e31df20d026fd4847181934e6208650041f22cff9b101 6396831 6396831 / 58
13.701 240.510664502 (19.004524886642972) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12873 376025 0x345f78a387ccca07de4e0c0f9e1a767a1fff5e410acea17b452ca919f9154539
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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.