× 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 #529 - 2018-09-17 09:44:29 to 09:44:35; Start Time 1537177469.7116892

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 580.870417317 () 0xccD7BDff63017081B5cF72993d5D84cf2a266330/675 183892 0x8bec5d541c1f01d926eb3e21c34fd68a41e5810b26da55c05340aa8a9a87b800
0.346 604.105234009 (3.9215686273384605) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4693 225256 0x80090bab5177be4ef54c3d6e754fa76338d78f60b143bdc555b36b4933f499a6
0.576 656.383571568 (8.294930875656469) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/675 213959 0xdba4c3d4245c81011176cfa986e3411072b14e607a071028235189aa013aafa2
0.752 1026.978897815 (44.03036576939174) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4693 225256 0x31e8a6680eba02f3263b36192d5e60137b1f118c5023d79eb6992707588aaeee 6347619 6347619 / 16
0.866 1029.032855610 (0.19980019973897734) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/675 213959 0xde42ac27fb1bfed310883a50864c773b591090d27fbdc0e31ad715a14ac0c623
1.571 1026.978897815 (-0.19980019973897734) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4693 225381 0x89a205bf630f7cf2d285c043373c8994e73ec4dce15ef3b0462bf9633fe4b725
1.674 1026.978897815 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4693 225413 0xa464a5a0383e9e69cceb44491669610944d27ab305e48a77b920820d294e9d85
1.899 45.305123000 (-183.09958103616412) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/15249 350958 0xd447fbf4c94add43c44ac1a17f776551869d966515b9b4b5b33fb3320e7da554
1.902 13.000000000 (-110.81401200371363) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/15249 350958 0x1393f26f46da63364c08e8972fc4477b9881f94d86c40d82b99561e4a62f34dc
3.337 527.369161741 (190.37694900418398) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4693 225167 0x8c200215822d3fbbde58ddb32d092cbe41d8c60682fcfe6fa1bdd1f34b998e30
4.712 6.500000001 (-195.12989289001771) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5627 492004 0xb6b52ca302fc9de90f3eee979b66bd28e3b0fdc92123d227903ecae7fb4135a3
4.970 604.105234009 (195.74192971893618) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4693 225381 0x36da1c16ca8910ceafb276d7e76e02ba45504dc8847c1273ad28dd1d4ea69c36
5.561 896.527574959 (38.9732037314447) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4693 225167 0x0fb5d657833fe140980cc3aa1d7cc08174ea26838c1af08591e4423787b21767
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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.