× 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 #1247 - 2018-10-29 07:09:26 to 07:09:49; Start Time 1540796966.1744242

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 1256.646862825 () 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/26762 22000 0xdded51d0bed52dade5d7f34b7a5b752ef767b46046c1b12899dd74c842103950
2.821 19.800000000 (-193.79527637956534) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/9015 399507 0xbad7e90c276b6995f6cfc36da5013168e846d3ec1f40b8a774fb1caa16b4c128
3.085 22.770000000 (13.953488372093023) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/9015 22000 0x6ac22ef14246ae1e1d9d2aa45de0f4ad1ad3aa23d5a24ed0b79163b1a249e099
3.167 19.800000000 (-13.953488372093023) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/20871 384507 0xeb90e85411b370e6e41b48539bc7e52c4bbc767b5b32a36cca4322f0de9d76ee
4.201 22.770000000 (13.953488372093023) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/20871 22000 0x83633eaf80ea35eeaa7d40871a79c3db6d09eb086bd9badd332eeae9c1b85566
7.161 9.000000000 (-86.68555240793201) 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/193780 98096 0x8f4f48f4f01852d02ce8184c69cfdb3af37d8bdd4bfbe681eba2f8f67ee9a023
9.190 19.800000000 (75.0) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/18619 399699 0x0649d4b1e995ead78ed1a5945b6cba02e0123136bd345f4acbdbb11b69cde85f
9.351 22.770000000 (13.953488372093023) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/18619 22000 0x17ceb443e0e2d2711003c5457e32b45a7aadcdbe9b7a77e1046a1e5d366cc2a7
22.827 26.185499999 (13.953488368292705) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/18619 22000 0x4124374f7c3b46b6ef3f4d81c4c9bd303001a1276b67da96fe2d0a8b876bc140
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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.