× 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 #510 - 2018-09-17 02:29:16 to 02:29:18; Start Time 1537151356.7518919

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 333.000000000 () 0xccD7BDff63017081B5cF72993d5D84cf2a266330/657 198828 0x743c0b76673a7119ebef5194749a2b161ea63884a2e3f47e91e0c86a54e3a782
0.381 10409.769654140 (187.6009628533115) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4675 240170 0xa5cb2f9fcbdc79fc8b8f0b6b4a3a0652770fc2adf587f18cd5650e5ab06bb45a
0.390 10404.962034256 (-0.046194396891315194) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4675 240238 0xfc6c485dc01fe13fbb1276ef139dfdf502d12e26a8a288910c737312d37ce849 6345830 6345830 / 0
0.589 10430.589193448 (0.24599453992774462) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/657 233950 0xbd069aa131706b1653618111927a9249097f3276be342aa4b951b3dacda942df
1.368 10414.298533030 (-0.1563036523080617) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4675 240106 0x2030e4aa2b6986d024a29b3092a9aa6feecb0aeaebbdc82f15f4847528396bcc
1.937 10387.606791244 (-0.25662785566909657) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4675 240484 0xe22ea3cd53da0b16b03151e3aad63860ce5cc61687edb05c6b0b5756d08ca432
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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.