× 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 #1594 - 2018-11-26 12:42:21 to 12:42:27; Start Time 1543236141.1970959

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 11.000000000 () 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/526 500000 0x84ca03f7b8d80d1376a6f1424bbf6f6dc18591279126a77f9a37f5171de1c121
1.416 37.280622509 (108.86612948746061) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/526 500000 0x80f61699bd47348cea2c387bb8446d94e95a19320b2ec8034330c7e74c08e028
1.465 11.000000000 (-108.86612948746061) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/464 500000 0xe0cc9060e12868b5eef498471c6fc3fc7152c9055363e1f4e22aa311ebd1e155
1.711 42.127103435 (117.17974977906869) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/526 500000 0xadbc6d7385288c38e3120a7d1be939afdd967d9d9551103168bcc944c61f6e7b
1.902 47.603626881 (12.20657276880198) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/526 500000 0x6326a15a4f71f4807f706cbf31ea80d08d2c7f76b98c3f3084444a60bf29a9ef
1.903 47.185913529 (-0.8813490395527491) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/464 500000 0xccccbf060efafd40356636ae215ed092115b561a02b46447d9059833cdfc93fa
2.500 53.792098375 (13.084402676258893) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/526 42000 0x2ee8207577c07df2911748106fc67bf4cae87cbe57c2c208ad5e06de7b016c8f
2.801 53.320082287 (-0.8813490400115741) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/464 42000 0x3a2ae6cc45af4fafb5453f6bf1ca9193e33a9893e1317bcaf906c61c542a2757
3.698 30.100000000 (-55.67024546226938) 0xEcC996953e976A305ee585A9C7BBbcc85D1C467b/6907 150000 0xd57f4fbe24ea189bbbf496f00ecf115ac719ea118dbb607c04c0cd6ad2ffa533
3.787 12.429999999 (-83.09428639273676) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/526 500000 0x1444e3329de2aaac4a4288e694c545771a05347614c7d76249f23513667aaedd
4.393 122.000000000 (163.01420814076482) 0x0dB368a4f0d93C8A34D7079b1E76FB8666b750a3/1001 45000 0x2b93871f990bcc140b40f375ef464b0670357adebe21598366d045c4e96b4f66
6.127 6.000000000 (-181.25) 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/221825 104866 0xe76137d221d18fd06e69165e27d0e66bb3448156b48e1f587169f567fabcbdde
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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.