× 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 #196 - 2018-08-08 14:07:03 to 14:07:08; Start Time 1533737223.1160593

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 60.000000001 () 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16061 299807 0x02e1acdf3bffec5e3a1a0a7ad6164392e5177c84abe8302d18a5416bf1f9a73d
0.204 72.600000003 (19.004524889321132) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11898 307984 0x89189d19166c12416365b8b474a76bbbdb572b05d565cfd5238809b8240e2003
0.427 73.600000003 (1.3679890560314096) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16061 299807 0xd9ef9c63d59acc5e712cb79f00714a33988261b462456d1208446b323c39907e
1.093 87.846000005 (17.64800614607247) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11898 307984 0x8d13a88ed4d2520a40f1a1d2e884631684362fb5d0742eca196c1d9b9c4a3c36
1.318 88.846000005 (1.1319131595583323) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16061 299807 0x5bd0e1cecb059bb370b4198834dd11958c2e8585a165461df7142fa668a09b11
2.554 106.293660007 (17.8822285545922) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11898 307984 0xfccf03b1b6bcd1d7be5fc65312b2a5c47e32c5c9f89216a5f453f34763da9598
2.844 107.293660007 (0.9363851748638009) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16061 299807 0x95e66b2e8b35390ed2b504d3b9a1070d90ad156c4129c37aca2aed47c17fa7a4
4.145 128.615328609 (18.07618160468338) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11898 307984 0x858603c109b0c4f69f459cdefe0f5754f6e52a618aad706bad61ffe928577a2b
4.450 129.615328609 (0.7745013785530457) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16061 299807 0xe54ca41ea933a7399054621e1b2650ddde7082de46cdbe8d8efdfcbbba6b3b60
4.630 155.624547618 (18.236734185301152) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11898 307984 0x9245c97cec8c65ede4363883e5f95cc8d89eb2e12bd34e98fced4a1e9129875f
4.858 156.624547618 (0.6405142658582842) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/16061 299807 0x67e60208701f0318022a0407828554e7986cd729ef8054fb634f66108d753826
5.783 188.305702619 (18.369600798556824) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11898 307984 0x2cb5a8ce7cbf96f94ede0f990773cc68697f869c9b697c8f3780f6925567b33b 6110865 6110865 / 52
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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.