× 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 #619 - 2018-09-21 19:09:05 to 19:09:09; Start Time 1537556945.821586

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 1000.000000000 () 0x18a0451Ea56Fd4FF58f59837e9EC30f346ffDCa5/1249 7900000 0xf1d4585fefc90fbe464b787f06db8b46fa6078be47a1dcca8000fcb3e8648116
0.146 1000.000000000 (0.0) 0x18a0451Ea56Fd4FF58f59837e9EC30f346ffDCa5/1250 7900000 0xaee06ddbb71c944375d69dfd26b59370bbd9e7680e04829ac9e32cba9acb20b0
0.438 2000.000000000 (66.66666666666666) 0x18a0451Ea56Fd4FF58f59837e9EC30f346ffDCa5/1249 7900000 0x7f378491e2e8a01a132692fd948b7ba86effe8722a8029db455aafbc4f12cfc6
3.701 100.000000000 (-180.95238095238096) 0x18a0451Ea56Fd4FF58f59837e9EC30f346ffDCa5/1250 7900000 0x0939e1273f7aa5726d2afb191840d12d15a77dcf799729191b76488eb9e83dfd
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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.