× 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 #1507 - 2018-11-20 08:17:37 to 08:17:38; Start Time 1542701857.247392

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 20.000300000 () 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/342 2000000 0x761a0f1cac5321ac54c15d6f15cae60978a56c9448d96ed42962cba96d71e4fe
0.114 11.000000000 (-58.06588968493853) 0xEF50EeD70D0Ff96354368749877BF51BFF73E4eb/5567 850000 0x82d6a50aae5564ca64603bd0a4dcb64ec95b195922ed536697c2367fd7b763dc
0.360 165.100000004 (175.01419647984068) 0x36F94220C57E34b6b3a294523De1977602Aa625c/647 2000000 0x5a4150605b3900926df54a2be88d0763853b0553e914001f938334f2703b40b9
0.802 20.000300000 (-156.77954060675688) 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/80 2000000 0x1832582dc80a814600a48784d05deee431a9eef5321f54128c0800ea87027e2a
0.815 20.000300000 (0.0) 0x9F994f73dCF01ecB1a82b7bf157a0CE45eF4D851/38 2000000 0x94468e4e47a76ca3f8d9e58faadaaaac7eef01f57c7c69f525217a25134809f8
0.954 20.000300000 (0.0) 0xC3Cd47aAbbab45EC41D9D46E159c2c0f55c47Bb7/63 2000000 0x41be85e41032efb9181975fe72b0eae5d238bbc748be099ac8828119e50fa859
1.261 165.100300004 (156.77961065589673) 0xC3Cd47aAbbab45EC41D9D46E159c2c0f55c47Bb7/63 2000000 0x0ffae4fbdcd624d104204da624283ca63605cc4107495bdc7fff18b74105b354
1.551 165.100300004 (0.0) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/342 2000000 0x30800cf28d4d5345716036609b8cec2194802ab66b84231ac3ce122419ec0da7
1.552 165.100300004 (0.0) 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/80 2000000 0x734ef24477ea38bc0ef81cfe634435870270dd42f95d1cb1c4ce0b665fa4b004
1.557 165.100000004 (-0.0001817078906304638) 0x36F94220C57E34b6b3a294523De1977602Aa625c/648 2000000 0x638041ff54cb74123e540bc601c575af4c5f0d99867a2ef1fe55e76d57f11af8
1.563 41.100000004 (-120.27158098466452) 0x36F94220C57E34b6b3a294523De1977602Aa625c/649 2000000 0xc3c637e9cd4a0acebffe143d64953da5f2662cb574c494875243fb1092b148a0
1.565 41.100000004 (0.0) 0x36F94220C57E34b6b3a294523De1977602Aa625c/650 2000000 0x590a5a3d8b6b1a819219ba85ff4901c61f1fc12b9092fcb8507dde69d67c54ce
1.612 165.100300004 (120.27169698122566) 0x9F994f73dCF01ecB1a82b7bf157a0CE45eF4D851/38 2000000 0x2edf335f0fa5ef7d5f767318dc3be7a24aeb4a758f36b11b3f8f93f9d1d52dc0
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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.