× 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.
*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 #1474 - 2019-01-29 16:19:37 to 16:19:39; Start Time 1548778777.4662297

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 15.725000000 () 0xfF1b9745f68F84F036E5e92c920038d895FB701A/55334 147785 0x364fc60884c3d4d9a6f21f2074cbf06059eed52c04e69dff04e22996eb70ff36
0.760 149.770456989 (161.9929144011604) 0xf666666666E8025c503209ac580a5aA4b39A090c/550 199340 0xec969c55ca1dcce3a5f454856c50419c128f7d8cf3f6a614d1cbe117d75e6e32
0.784 149.770456989 (0.0) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/750 199340 0x0311f6ce01dfecf283f29df2e6ac72d429787d3270e4eb023342c3e9ec8415f9
0.841 132.521528332 (-12.220629386545204) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4476 199404 0x828cea564e63f8ad2d3a7f251b0b0f64c4bd6597d3b5c74f7422cc613b7c21dd
0.856 149.770456989 (12.220629386545204) 0x29e990000000F72253e0f4A4df9c8319C018A2b3/187 199340 0x03453bafa8c640b877510c33cae401d43357312a9e6113351b802204c919d5f2
0.856 149.770456989 (0.0) 0x0000bAA8F700aF2476492b19e378d61b90454982/408 199340 0x35f70825a019369fd0f4216f5e3f8140bb80e3b496e826369b2916501dc47ce0
0.920 400.000000001 (91.03055278088597) 0xfF1b9745f68F84F036E5e92c920038d895FB701A/55334 147785 0x9216961d33724db04200288af79fa71a6a624ee949c3a65a6840d36a307d018e
1.324 54.080932560 (-152.36009382293548) 0x41880a6C0BF00b0C159a8154d66B676a995D2383/18920 1050000 0xf04fc1dc834f17ed5b5fba6a956c12789effe58b2df5e253029586d90cb5595d
1.603 1110.837543744 (181.43013999345757) 0x0000F7F39325076881E5fC566E99595542532aE2/16027 240734 0x95efb051745ea6ce66f585ab3e7c2c7683d52aadace19c7644625087f49c1704
1.625 1108.747732620 (-0.18830645042153202) 0x0000F7F39325076881E5fC566E99595542532aE2/16027 241069 0x05bc2f7b609cc2b897831a658395440d9ec66a4c038b7c9dea38c380bc3feaf0 7144722 7144722 / 0
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This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. .
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.