× 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 #368 - 2018-09-02 07:06:48 to 07:06:51; Start Time 1535872008.1211634

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 193.589492217 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4168 213636 0x845288df2726803d4221a6a3d51efea9cfc4ff68adf1014f67910693afff1c87
0.595 201.333071905 (3.9215686271133614) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4575 254987 0xb4077d8529bb0b1d18fe3f6928a1e18e31fc58151b5320f75263d968ff656677
0.934 218.756126205 (8.294930875817373) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4168 248651 0xfac20e96b2b6b81397d7943da8874fe0b592c54a6d4bca82dd10fc58d3d00317
1.114 342.950754682 (44.220440483435894) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4168 248651 0x427923d6dc3ce26dbb87b11d873e4a1e4a2c15e069740f89c09a3aeb69cbeac3
1.244 342.266222238 (-0.1998001996614045) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4575 255024 0xfe5605aa32e0990ddcff7c43da6120b625abb78bcd3b9bb5f1a379966714f143
1.307 583.016282959 (52.03817415087566) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4168 248651 0x8fde8bfe538b3d052d9a16240ef0864159a34b584a44c81f3886d3c5b9c28666
1.319 342.266222238 (-52.03817415087566) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4575 255019 0x0157d8facfca76feecfd2531c9486fd4421282cc00bf9f4976b93fb48d79527d
1.392 581.852577804 (51.85185185175566) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4575 255024 0x05360fecb0bc021a28569c63bb2fd8764006bb1107824ce1b359583c9d8590c6
1.415 342.266222238 (-51.85185185175566) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4575 254987 0x9aa2e50b0ba8da4087e77d1a871377c711ee7cdd12da74abf084b950e20627d3
1.623 989.149382266 (97.17223650371548) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4575 255024 0x60a8088a864d6c36fa2384d6a05ad59fe01ce9414d470a3d22818968013e5169
1.835 989.149382266 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4575 254987 0x12e46ece0886bb1db77d5bbeb95614eb15c156f7d078844de6f2f482d56dce15 6257038 6257038 / 0
2.051 581.852577804 (-51.85185185177641) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4575 255019 0x1c1b727366dcb61e2116fc3815e4c7d30909adc3707dccf3eb0417cebe2512ac
3.209 201.333071905 (-97.17223650366566) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4575 255019 0x5b4811153de7dc243f92c2f9e218c700ef86416bcd7bc964d4464de9cd345a85
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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.