× 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 #501 - 2018-09-16 13:35:27 to 13:35:35; Start Time 1537104927.6107829

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 11.500000000 () 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0x785a8f6b7c51544fcff53eaee4c10cecece8a838ef7927c1a0dbdaa5efa9da1a
0.265 20.667902334 (57.00031191844267) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0xa73d2f862448f5ade244ae3ae7ab43068af9db6cbad7e60e14dd8d1edc082b79
0.435 20.667902335 (4.838420386430532e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0xb6303e30c6816afb4635a337762b30f284ff085044345c8fb91f00d94a312d8c
0.811 25.008161825 (19.004524885490923) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0x6c2d4cfceacc0f565c33325a0b59e03eb7ccdfd816cf99481da271535f4aaaf3
0.835 25.008161826 (3.998694534119389e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0x44378d22e054dbeecbbd84c2de1cd8a5a18848e951da23d50f62981b6d5b52ea
1.236 30.259875809 (19.004524885371392) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0xb3ffb227168ef1a22beacd453843008784c36dd2e2a5934eabb5b35a96c45b4b
1.402 30.259875810 (3.3047062264745085e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0x383b7b85220538b9d6c1db97bf74ce6bb9a5ae5b4b4a3ab8ff8d72d260fc0ae5
1.625 36.614449731 (19.00452488931368) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0xc13ffacb42693100db3a52c089f33ac2f06a74c07126743970fb297f08ca14b1 6342515 6342515 / 31
1.683 36.614449730 (-2.731162170565124e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0x31b48111ffd99bb219b7f933e0d9d042b0a265770bd3692151d6695b56272d10
2.168 44.303484175 (19.00452489068035) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0x5c8af1b9ef3078057c01e3d8ffead1788ae3490e231cb5af17786164d6b75844
2.310 44.303484176 (2.2571588185676013e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0x5eb9b6e0bd51bc47a28751208de4d4e332f16373c01394385cf886660053d50f
2.597 53.607215853 (19.00452488695177) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0x7c09c4e893165b96a17969fc9f503426aab4119c2244175452b8487f865e5c18
4.542 53.607215854 (1.86542051117305e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0x2792e47cfde2cfeb24063ca6bb60aa5317f4973c689d7168261ceb82d1a6b5f2
4.953 64.864731183 (19.004524886358393) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0x5cfab060ee47aaf310b8f744539410a85345876b949c3c24dedc822d3a8bd6f4
5.292 64.864731184 (1.5416698439264872e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0xd5fe79cce30bc2b922888b346effa08a1cfe9c0981cddc16c0098bdb4f13681c
5.475 78.486324734 (19.00452488859497) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0x72ce95d8ec22332461be86788eaae93c84125f728f64cd38a72c6219f2a00321
5.551 78.486324733 (-1.2741073090063727e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0x591aa17ea5ff2a5ee5c40f7713dc46be2ca7b9174f963f26b55bdb63a7314c8c
5.955 94.968452929 (19.004524889037818) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0xc28fde6349cc8dfd831cbfa691034bd617f8b151558dfdb523cc1e487ab29e88
5.956 94.968452928 (-1.0529812471020052e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0x585d5d94da519757c7ff475e9937eaa9d7661003f27523007fab1ba0bde47dd7
6.380 114.911828045 (19.00452488870606) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0x8711206d107f52280079abd4695beac3b4a3084b8bd3eba4f86de1961f72a2d1
6.396 114.911828044 (-8.702324356138052e-10) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0xd7da3cff48d06ffa0986e243c69411cebbfaa3b0cec7b16bf4b37773a8151e06
6.978 139.043311934 (19.004524887419485) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0x95ea7ce8bcac9f719667b9015d92ae7aa9b494cb28db747551c77c67f4c00c7b
7.146 139.043311935 (7.192003600080213e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14895 327008 0x5c6d6b953bec3cab989a0de5cd32385505541ec27a3f40a9e10598ed21f144ce
7.844 168.242407441 (19.00452488667167) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12691 322581 0xc76d6843057de728a1dcbdd0141d1200ca7f313b5f8852ce5a704ab4871fae15
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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.