× 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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Global Market Overview

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 #1057 - 2018-10-18 05:03:48 to 05:03:54; Start Time 1539839028.1535106

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 2206.756335945 () 0x44c2e195AB76797Bf16f417D13f914e1dcA94FfD/132 280000 0x5c339fd558dbb99f85dc0b87a74622fd6f2548e0f54d6e31d7a2739d8c9e9eff
0.359 2295.026589382 (3.921568627416136) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4866 226130 0xd5800644c9d5b6c4f9758e17c51089623daa4e579791f34c0e439fab5363853e
0.408 2295.026589382 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4866 226175 0xb4ff9823a2052c5b6d7515e4b5174032460dc1d83d224beb91c7aa07db42f5d9
0.668 2295.026589382 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4866 226208 0x88c2beb148254a7d07eda7f49b8a47cd81cc5720c18fe4402a62cc93c0006d94
1.116 2295.026589382 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4866 226098 0xe977324248028fed6a866f6446e61877b3d223a09353c881f08a5950e958417a
1.825 285.520591723 (-155.74262794904777) 0xf666666666E8025c503209ac580a5aA4b39A090c/460 184532 0x0a5512dac0fcca1783a026f2b1317f2561e56fc3a72db61e5d6a63b9c184688d
1.943 85.198897488 (-108.0718441112138) 0x0000bAA8F700aF2476492b19e378d61b90454982/252 184532 0xfc8ee280a4fd7cdc6b8ba5462728aa4628b837110f77cff9c30297aff1e87d50 6536135 6536135 / 3
1.965 44.665620564 (-62.42394386397334) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/687 199724 0xbe0e182d40729d6da40a25a94e15d054d5884b519b2f0eda63784cc4a5ce66ff 6536135 6536135 / 16
6.540 97.126743136 (73.99710563115465) 0x0000bAA8F700aF2476492b19e378d61b90454982/252 214684 0x62fe3723dfb8e2d43820024c14435331abe99dd917f46323f4dda95d6b0eae90
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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.