× 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 #451 - 2018-09-12 08:20:41 to 08:20:47; Start Time 1536740441.7976935

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 15.000000000 () 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5211 310962 0x8b3877e7a7759a0252e607fc0a86b5d0daf65c32118b9c47afa0374a7ed7e71f
1.543 60.000000003 (120.00000000319999) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5211 310962 0xa6f7e2ec4a4575c0b5b0b148cd9ce5b406e2677a80c37f7392ed4ff864167e1e
1.962 72.600000004 (19.004524887382868) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12543 307268 0xd71454fd294cde22840636e94f0446fac55c4e5cccbb0f46cb862752662539bb
2.811 72.600000005 (1.3774104682341825e-09) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5211 310962 0x6fb28f7e326e5b0c44d91b895c56979ed4318be9715c58384f1f3c2feaf8af39
3.068 87.846000006 (19.004524886821425) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12543 307268 0xcf97f8568af02e29e7a39d102a51bf0e7ad0176f2be49c92e11710dc788c2dbb
3.966 87.846000007 (1.1383557588575539e-09) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5211 310962 0x65360da135edcf84b314ceb742aced733fbbfb73f353df2021d6700c4540a57c
4.176 106.293660008 (19.00452488643965) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12543 307268 0x7b91f192a6a9c4b0d3d793daf4d0de13918cb66ac6da645a9ccf7dcd4cee8252
4.951 106.293660009 (9.407898833477301e-10) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5211 310962 0xdf999fa29a38ec636afc8d230e6cb61084a6956833f79ed8789a13bddef83bdf
5.239 128.615328610 (19.00452488619209) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12543 307268 0x7a4b8fa1079201753e95bd50b722d77abcc1bee780fccb3769a4359f28a2c3c9
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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.