× 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 #1125 - 2018-11-08 19:06:41 to 19:06:56; Start Time 1541704001.021574

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 94.621777811 () 0x29e990000000F72253e0f4A4df9c8319C018A2b3/154 199404 0xffe85a41f0dd27009edbac235f1efb775959eace7bac46c1e7eb6e40604ab1b9
0.655 126.000000000 (28.445262748159678) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4231 184276 0x5a7f4f15bc07329ac9aabfa66ebcf5626a31a0a917611a52770b469096edd985
1.081 92.593344233 (-30.565117052595745) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/705 199532 0x3681979c7ed885c67489e026b1d6d8112220f17bb0cee2bee08cc054e8341934
1.368 220.611205583 (81.74712750833751) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4231 214344 0xbabec97e498ef74993b44afa66dddddbb6b575131429982d393cb4dd6b2cbd0e
1.786 248.408217486 (11.853245531330856) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4231 214344 0x3583ff5721ff8cf36346d1dd38ec8694f8176c3ad1b335ad654c632d90358ff3
3.780 375.039049492 (40.62278839389587) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4231 214344 0xb759e1da28226efa18b9373e6f543d9dd21d224c49c7e0c684ee3ebfc0d4565b
4.449 221.494532849 (-51.47891793130548) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/705 234912 0x215e7b96aa0d3b53199db7dcbdf5f69fc7e4e40889ca9027fc28a13396f91c6d
5.125 375.039049492 (51.47891793130548) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/705 234912 0x3e443f39c2126aad6a699231e88b0e45666417fe010a864f209fdbd4e012f111
5.625 422.293969727 (11.853245531280498) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/705 234912 0x11bb24d5e584fd4d1b5636f7a98a610bbd3c8c19b84ca5fba06bd8ce28253778
7.399 422.293969727 (0.0) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4231 214344 0xf1019b9f0933efb7742a4ec85afcc64eac7d994b0949a522e524a15edbbd22ea
7.883 638.841516904 (40.81430692031929) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4231 214344 0xc1cd1ee47006481ebdd834bb727472deba21a4d1ce76c963c66451033d5568c4
10.233 637.566384136 (-0.19980019975762278) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/705 234912 0xb2acaca3b5e2f1f22b300669b4d169472525d14f892bf520aca3a06b7689a936
10.897 221.052427994 (-97.01952723554753) 0x29e990000000F72253e0f4A4df9c8319C018A2b3/154 234762 0x8c80b77c70fc2c693e89091293d4631ea3af46a207fecd7f7e18081c440e9099
11.474 638.841516904 (97.17223650401628) 0x29e990000000F72253e0f4A4df9c8319C018A2b3/154 234762 0xd060552a5674a180e9b29ac73a04c26155a417a3ac0d3980d745cdf943ee2728
12.323 719.335548033 (11.853245531389351) 0x29e990000000F72253e0f4A4df9c8319C018A2b3/154 234762 0x8c6c165d0dad12d8fbb92a53adf2dee21c24c522c71b29fb02c17a134dbaeb87
12.632 717.899748537 (-0.1998001996508955) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/705 234912 0x73cefd19a7e550414cc0c37ce82f035771c73336e995f65626f7133163a98f0f
15.100 719.335548033 (0.1998001996508955) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4231 214344 0x76da92b6599e71e25fd1bc021ca6be0ba7f13f35bfa4b3666c3e2108b1b7f4d2
15.452 1207.954690785 (50.70529937947159) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/705 234912 0x585a81862a05f29f02d7da4966986e24b36b3de413e743eddfb349f49b47b027
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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.