× 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 #571 - 2018-09-20 11:41:39 to 11:41:49; Start Time 1537443699.9939227

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 61.046699578 () 0x0000bAA8F700aF2476492b19e378d61b90454982/227 184468 0x79ee447fab4c24a0822930b5d4136e0485521869eb2289f79ea4ddc67203e2b0
0.085 160.991350428 (90.02479606292638) 0xf666666666E8025c503209ac580a5aA4b39A090c/383 184404 0x37a341df724da9b5d898bea32b68aba3f344cb60fdf3bc929c44b758ff76cb24
0.841 209.788764381 (26.321483814274675) 0x0000bAA8F700aF2476492b19e378d61b90454982/227 214512 0x7bbbb87ea7b94cdc2da4021634900384145e9ae8daccbded7c11c64ef0c96758
1.276 356.132319343 (51.71871455963348) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4744 226072 0xc64224e7d74858d42d35fbf2dd7a9d5cae26337ddad6fb3b5ca3aaa020d86705
1.670 356.844583981 (0.19980019960795944) 0x0000bAA8F700aF2476492b19e378d61b90454982/227 214512 0x21ce888ebf3a1c2bf3a8051adb24fa34ddacc1e2b6b7307654eb516a7edc61a6
1.774 355.929041366 (-0.2568957611343394) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4744 226148 0x5c3bd8bb94cffe8e5d7a9a871827b8efdaa501498195c7c1fd98213095d31126
2.080 605.424942883 (51.90510584130021) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4744 226072 0x9dfad2b0e022913cb80c4630e31344465efb997ee4a8d8124862b47ce8480ff4
2.593 606.635792768 (0.19980019967392976) 0x0000bAA8F700aF2476492b19e378d61b90454982/227 214512 0x8714cfeb0b54a521879dc19544dee33534e8e01f4314855194cf92f46c5ea5e9
2.691 605.079370322 (-0.2568957612168458) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4744 226148 0x50156429b6f8866b6f8aaa29d21832e407cd28038e15c07378627baa7de0b928
2.761 1028.634929547 (51.85185185181558) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4744 226148 0x90b77b89973e67968815dbb74a0a91dbadd71fcdbff31e8347e1471f2866808e 6366320 6366320 / 0
3.181 605.374901372 (-51.806301304435856) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4744 226083 0xf8c12ef286e058a53da3d8642437b48d05b8e5450fb10b80d911c042a334a4d5
3.417 1029.222402901 (51.85956203659708) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4744 226072 0x5121b15e5465d14f9eb2740d36fe722bc942b0fd582bf4da37a0a74f446211b2
3.947 604.359960934 (-52.01604172189916) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4744 226120 0xfa352400441b8ecaac3fa84a42999cc8430cad9c8877c91c01f9024b21269954
6.752 356.102883160 (-51.69530071893197) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4744 226083 0xdbe659189e62b49c88a9d074cce4459997c77542aed5ef2c9b3c43ffe80cdbb1
9.408 1029.137332332 (97.17223650382635) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4744 226083 0x30073c961d44f64aac8df43ec2bf618af79c6bdf46767ee9a916b6996a50734e
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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.