× 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 #1552 - 2018-11-25 04:11:20 to 04:11:25; Start Time 1543119080.8401992

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 72.000300000 () 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/384 2000000 0x5a51fa650d7426b462befcb85281a0ff5c9e05ba7d27a79d373a6e22cf957627
0.453 72.000300000 (0.0) 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/108 2000000 0x22d842ffe62b0814b360612c0456951cfa8f5b92ef0576fce450f1136bf42899
0.454 9.000000008 (-155.5557201288829) 0xc6e705e559518293a4dC4d294114Df502720B4cf/12 2000000 0x2e67081971913f950b8ebd00ef317ea6f4ab6bfe652311e151bf9498dd44a68a
1.118 9.000000008 (0.0) 0xb314371A82BD900fd70B83902665B2af93dc3294/17 2000000 0xc20b3dd36d2a646682e7f540185890489336aa1d319e19ef23133383971a6707
1.491 72.000300008 (155.55572013327244) 0xc6e705e559518293a4dC4d294114Df502720B4cf/12 2000000 0x7d428a155ea01ee71f197c5e18a8673c8dc9ca9f3c6f6e6602de1f7844648f71
2.117 81.001057503 (11.765591680260606) 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/108 2000000 0x48b043d6563feb52b6bba1f81f199a157dcca1905912ec78e71be86e49a8aee9
2.136 81.001057503 (0.0) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/384 2000000 0x66428769e05692f89092b1285ce5386ec79a2cd8acc2a7a7811eae8927195d14
2.464 170.100000004 (70.96660076671813) 0x36F94220C57E34b6b3a294523De1977602Aa625c/758 2000000 0xcac960b5f21b5abcd5d0b6a21f0760d4ea18a8bf087cc7d8713bd12c45e34405
2.929 642.500300000 (116.2687978317691) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/384 2000000 0x3457a4acfafbe79285106f7e7569f342023228551ac9bac4323d9b3240140744
2.942 642.500300000 (0.0) 0x042EABCc257ff6df43dB036Fd6Ef2FF5Dbae1512/108 2000000 0x0a54f118fac95f7d598d43e483ffd13b3a96e047712d907c88d717e58adc23cd
2.969 31.401000000 (-181.36166230870901) 0x36F94220C57E34b6b3a294523De1977602Aa625c/759 2000000 0xc164baecea56fd1458078404d5c0feb00178e2f44e92327f24f957cf570b0d8f
4.582 8.000000000 (-118.7837872135225) 0x3825c8BA07166f34cE9a2cD1e08A68b105c82cB9/2023 279255 0xa8b819b61d23362153dacfe57bcdb63a63e70e5fc741392b3657a5e8349bdad7
4.988 642.500300008 (195.08070941710457) 0xc6e705e559518293a4dC4d294114Df502720B4cf/12 2000000 0xe3cd6b13e00c4ef17bb9b5a75c6620afcfc48b98a5cc2e6bcbdc932f64d674b0
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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.