× 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 #474 - 2018-09-13 13:46:43 to 13:46:56; Start Time 1536846403.2117076

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 6.999999999 () 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 259308 0x4bebc4cd681011ed178c80a1091f9b4ffe049f6230f19bb023a7b7871c041581
0.646 7.500000000 (6.896551738406659) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14015 653353 0x77b4d4f28bc944e02b93f0af43c27e68a0e9e6e97ec8874e0673c53486f7cd7b
1.978 7.000000000 (-6.896551724137931) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 259308 0xf49398a6939fd09b74609185d66f93472145694bc0880ccb799628a0d2e14eea
2.876 7.500000000 (6.896551724137931) 0x3bd189a9b1c11684b08f6464866dFa431362A06e/709 1300000 0x3d575edd018fae8dcf0c60845d90dc6311593367844eb60223fda79478881971
4.228 15.000000000 (66.66666666666666) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0x2f9e3db5d7aa53d4a404b2eb25a7f78cb857b708cc5887ebd3cfb294659af3e2
5.156 37.766522341 (86.29153990430873) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0x60764b992123374c3c9e8ddc74888da40f6b9d21096896bbfc9a37c9242f5dc2
5.721 37.766522342 (2.647847718033448e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0xc92aa50a81196d916d6f0470cc96a14992868b1b82ea61caa64ba1363832cea0
5.948 45.697492034 (19.004524887268165) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0xe936d7975879b0f61533e15b825c6bb9d3c11fef487e0c94db3785d00a9015c6
6.611 45.697492035 (2.188303899139662e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0xb4050d521d32a05a117ddb8556b6dee69395957e0ef7a29259811f03c47cd610
6.889 55.293965362 (19.00452488625056) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0x78e70793b154d121d321829e6475b8b9b08263f139d36aac365a18365244f92e
7.284 55.293965363 (1.8085156190989937e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0xbd970816cb2d23e323830b24d0190332a19d875dc39dbb27bda0282adc4c274a
7.605 66.905698089 (19.004524886537162) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0x451edaf7c7170c375ea7924ff2a7561fb496c76b15f81d207673b892f7565958
7.881 66.905698090 (1.4946410075002824e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0x61cfb557cc507d612607df812d06df8721af328d536f256e630f739e0dc99608
8.237 80.955894688 (19.00452488577615) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0x7549d863b89b2ce540860c5aa34c90e08a93e66befcd176acec561432aebb61c
8.558 80.955894689 (1.235240502063221e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0x4a871188fd92ebf5e1e13c881b9a427e45d55c93fe589dc8a268bee2071d48e4
8.905 97.956632573 (19.004524886179794) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0x5ff626cb71f6da78095c8de53ca2cec3465994496a8aecad1aac169591fd519a
9.245 97.956632574 (1.0208599190561884e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0x2ab16ec29e3343dc00df3552b91cfff689556027f4430832dbeb43102eb634e9
9.574 118.527525415 (19.00452488726242) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0xfabbc172fa358055b62b6f72b4d48ecbb87cbcc1471ed139927909a776f12fc3
9.934 118.527525416 (8.436858835063712e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0xd8e982b860871dfa0c5d213268e86c177c4186ae153a62ebb4f46f0165e709ee
10.228 143.418305753 (19.00452488662908) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0x593b73809760df0300908889216cb1785982cd8f263e161b85f79cf8faca18da
10.580 143.418305754 (6.972610607454452e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0xac5d4e52746e7aa530cfce604b1b8a6735edd8a7c3c0f2780220b627fcd6972b
10.908 173.536149962 (19.004524886683672) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0x98488d281a95309450f7819f5075b6843150b918f5c75cbff6221c0cfe63d06d
11.230 173.536149963 (5.762488105308856e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0x2a14d351dcaa59b2394ceb3938cdeaa8bc693334675327074153004ae0349c97
11.594 209.978741455 (19.004524886769282) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0x97a230b1f4f3aee885e6f69342aa8edbaede460b0586347b406b47fd1873049f
12.107 209.978741456 (4.762386863871771e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0xf701f49e1adf3aa632521d112c18b119f4c252c7c47058b7b1b2dca40b833509
12.490 254.074277162 (19.004524886971435) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0xd72c93df0a805c7dfdd2e3cee8d66777996297ef53e362a7cd29d0314c65219e
12.872 254.074277163 (3.9358569122698845e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14014 313627 0xc941b5c3c93b567f3b6c4876608b1c3ebd0f62fa74cb98d48044e9bae5441fbc
13.206 307.429875367 (19.00452488680369) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12605 307994 0xdada982e91272968afa52ead24dcb08955a5dc990a5f7142baf718a3fa4df16a
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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.