× 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 #656 - 2018-09-24 06:42:33 to 06:42:42; Start Time 1537771353.0692196

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 8.800000000 () 0x0005ABcBB9533Cf6F9370505ffeF25393E0D2852/43535 342366 0xc5ed03e1d74d4119346782361b70e82360ecd050b43d56896efec3b3b568aadc
0.837 13.000000000 (38.53211009174312) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/13796 100022 0xae84812203223e8c29c7a4b682f54be28b783098da3fb07b284e8971f70eab3f
2.931 8.000000001 (-47.619047607256235) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/17033 348962 0x16b4da685de6c01d20a35e15d646aef07de1784ace5df5b0a1ef8d0833b3a9f1
3.988 8.000000001 (0.0) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12839 307581 0x33eaadeeef569d57be155db1c7e4cde09118b0faf5417806ea86f198012da99c
4.036 9.680000003 (19.004524905202597) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12839 307581 0x904bf6a930ef571d8b414b76b229ed6bb5ae98c131abacbd916d5f34878b8b8b 6389313 6389313 / 26
4.707 9.200000001 (-5.084745782821028) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/17033 348962 0x9b95dbe74dcb231c9c94fe7ad9df106f3767d33460ac721ec17c78b481bdd053
7.016 8.000000000 (-13.953488382909681) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6023 816338 0xd9e4b8f2ed990895b9fecfa43c857922f9e8c5a00402f04735a728b7733126b0 6389313 6389313 / 57
8.571 13.000000000 (47.61904761904761) 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/13797 108048 0xd35b8486523cd59d514eb8c6449b70268abaf5da5bbfb6bc8d3e78642a504529
8.630 9.680000004 (-29.276895903125766) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/17033 348962 0x0c20573cb7e7acbec66464a8c5e36174ce65f902bb330fb7ed3e60a578645ae9
9.168 134.000000000 (173.0512249339351) 0xa8660c8ffD6D578F657B72c0c811284aef0B735e/48913 121000 0x578c2b6593b2a25101752484479f19a44150a063b863624a1c5de6224e6342b4
9.749 8.800000000 (-175.3501400560224) 0x0016BD4cb70Bd98CA07A341DA66450b5d22A55aa/33648 196529 0x29dc697264fcc8127704f8a1518281678cfe6e635df18057ce86424fce06fe44
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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.