× 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 #136 - 2018-07-28 10:01:03 to 10:01:14; Start Time 1532772063.528956

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 15.385990000 () 0x41880a6C0BF00b0C159a8154d66B676a995D2383/16931 300000 0xe4ed9c56cd6b0011f47350997dd97e4cde464be3cb7e6d34615b4a79c7c415fa
0.561 26.169684713 (51.899986163028174) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11104 136274 0xd08091a26bc20ee1b16b92ea6deabb290e9e071a5b3a081fcc13abb42102cd47
1.162 26.243662620 (0.2822865196149101) 0xDd5e4dbcff073A5f12ADb90e156db5Ea96557982/1447 136090 0x9f4febb273cc31f0c849106d0170fb8214f318a105b8b7037d3761c6ed2a4b0a
2.552 26.169684714 (-0.2822865157937024) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11753 416006 0xfdf298da2e67093d8bbd2395811a15a194795f44057d829c9431b6005ead4f71
3.109 31.665318505 (19.004524890195114) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11753 416006 0x3ee406e0f51de9a770aafd336591ecbda0701105db5f3dabbeecf4855fe36611
4.251 44.488464012 (33.67697593783331) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11104 136274 0xe22accee9cb70e17dfd1647f561c51604d873ffd0061ee1a8990e9b53596d1c5
4.812 27.243662620 (-48.08111010138942) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/15458 445877 0x619ebdbcf0ba3fcf77be911437b8875209614bcab9bc974f4f93feb8455f3d71
5.484 48.937310415 (56.952929138968166) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11753 416006 0xa6cda35da7d6b5920a349edbccdf8b60e3fc60943f9f11d819bcd03025670f31
6.024 44.614226454 (-9.242144182096345) 0xDd5e4dbcff073A5f12ADb90e156db5Ea96557982/1447 136090 0x7edda90879cfd4c06f108bb4478341fe26a0afcfe96611dbd6402f3f6f8868f4
6.797 75.998306592 (52.041159148909564) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11104 135958 0xd5864ba91f15b66b0c4a944ee96d70d7656819da8a1a676d4203ea087c019395
6.842 220.109494576 (97.33697485547633) 0xDd5e4dbcff073A5f12ADb90e156db5Ea96557982/1447 135819 0x6f2685d5694a208c93f3854800f26e4e58d06a4d1670a96a502d23c521950e7d
7.381 83.598137253 (-89.89656038664288) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11753 416006 0xb9b535e9e8bdacff0c01e448e94caa15ec77c61483311488c7e4355de36f5a49
7.921 45.614226454 (-58.792997371570024) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/15458 445877 0x0410900a9f6db2a795d50446aaf9a1b6abb301c49eedfb7cf79ed6251f698dae
8.494 75.844184971 (49.778287336924144) 0xDd5e4dbcff073A5f12ADb90e156db5Ea96557982/1447 136090 0x184116e55e5b2ab625872ee1a5eeec1e0b16c7b2c10b620b4c9b62b870aa6242
9.034 128.571660994 (51.588442935121556) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11104 136274 0x422f2b94e3f4ac38dc160a31adc940a493464ea479058592ca678f89b88b8d1f
9.263 218.571823689 (51.851851851510446) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11104 136274 0xc6825bb4ef85f7a708e913a2ae4ea2b12be2cbb7e44a71ad52fc934851eae821
9.620 141.428827095 (-42.85714285571429) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11753 416006 0x3b8ba55f4260c359c258382ea82d32aec75bcb5b07e0c51e3ce012da662c5cee
10.160 76.844184971 (-59.17785392952868) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/15458 445877 0x00cef8de3e873400d85755752c88f0eb499e169fb99371f0e0332c11f813af11
10.736 128.935114450 (50.62795881370764) 0xDd5e4dbcff073A5f12ADb90e156db5Ea96557982/1447 136090 0xbd895dd58febb9aae0ad0db2d5c111e6783156c6fd9d389fc6e9c534f105679e
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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.