× 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 #1481 - 2018-11-19 21:39:56 to 21:40:06; Start Time 1542663596.0599418

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 7.000300000 () 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/8 2000000 0x70e02ef757cb82354323f330393ac90884665379de3836875b0ddcbf6b2116ea
0.001 7.000300000 (0.0) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/260 2000000 0xa19b675c2d01f886f7a1faf0ac494f1a971d13baca5681ebd0f510137523fb5a
1.708 229.750300000 (188.17270156865496) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/260 2000000 0x17dd5915a5c6bd4acc2b312b650f5a14df9a516e8cfed0ecb96980202c02c522
1.849 229.750300000 (0.0) 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/8 2000000 0x9db116545f87351a5e9eb99e468d41f52a19951395f788ea7fb391c94e9c80ab
2.046 134.100000004 (-52.57673279090245) 0x36F94220C57E34b6b3a294523De1977602Aa625c/620 2900000 0x3a557d76e5cdc1bdb000c097de6f620ac9adf0ba7729b01afeb51771fca8303f
2.580 9.000000000 (-174.84276729630068) 0x10AB85a549136fcCCe8f30F1B65dbA435519d00e/293 146196 0xcacd0a46bd266ac22e51f69792a2594e6dee04fc93688d3ddca3559a10086281
3.179 30.000000000 (107.6923076923077) 0x3a13696EBc60603873DAA01D417b502697A57414/1624 150000 0x11189b21cf20091374a4a2aeb67d387ea4795b6666e91a787ec2848e8921fa1b
4.586 5.000000000 (-142.85714285714286) 0xf8856124ea157D6f26472E38224ee6744aD13AF3/5160 110205 0xaeee48026d0ed52484e35d99be8919a06d327e2eb4cf484780a1350e7b78c7ba
6.594 15.000000000 (100.0) 0x60739eC82729C3cAE0F4aD0e0511cA231E64200C/857 53323 0xc355f7fa5d9e1a2756db7b5408e75f024fca8bfa3e094792453bb9c5921b9bb4
9.393 9.000000000 (-50.0) 0x10AB85a549136fcCCe8f30F1B65dbA435519d00e/294 850000 0x1fc9af379683abba64846757130b44cb710b8e86848974471aabb06b0c31305b
10.344 258.471385003 (186.54061629822712) 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/8 2000000 0xe6f2fe5c22b5329db3b904da3653319a1b5d50320aba065c366a87b2de9125e7
10.365 258.471385003 (0.0) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/260 2000000 0xea0d71752c351113cb1765298052a26c1c45e53073aecc87ba91a86468ffe479
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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.