× 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 #14 - 2018-06-29 19:35:56 to 19:35:57; Start Time 1530300956.0624058

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 153.820419685 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/3824 184020 0x9cb3ceab14428e0cc4a1d0ed266d982b490ec6f9b36f0c0d91976a8ea37bd722
0.368 178.120245331 (14.641065833153474) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 238881 0xd53e3d4e864d4e6d6f79625b8af44ae0c5f2cd6ba2200a81ceb0ed89a9d32674
0.497 178.476485821 (0.19980019942928295) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3824 214218 0x6adc48ab38695cc9dbe6e82dd5f1c6c90abb300ec1326ba7a647296ac03d1dbc
0.629 201.678428977 (12.206572769592437) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3824 214218 0x979b2600fd49cf019afb7891e61cd8209f63c2e7e90ce5ff011b3d4c89b71e9f
0.700 198.817640262 (-1.4286226181624748) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 223447 0x82bc3ae1edde8b7bf113dcca816bc7cb6a83785806d944d2193078d9fff7468c
0.967 302.804417062 (41.46020904851657) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 238881 0x03cae2609bfef920a9af15a1a75c7c739d6c029b0912dabb64357bd8ea9f8d36
0.980 303.410025896 (0.19980019975933105) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3824 214218 0xc10107e902384fdfc3b122c5b2bda0f4ec215fbc6081158537f0649ad43d2645
1.045 337.734992115 (10.707395442449213) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 223547 0x65e46600856491034d3cb9679f45b78f8196f98dcef11c72549b2d4a87d8f467
1.057 342.853329262 (1.5040919705011473) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3824 214218 0xec0611556b8cacf028cb1670a8277f91d2f4d165c9259ce4b03d3fea44985ff2
1.112 337.989988445 (-1.4286226186016362) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 223447 0xa11b9a8837dc58cc9ce8becec59b183bdf0e4e451a9e40f80e28a311dba0eb02
1.316 178.113018723 (-61.95544978483623) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 238887 0x9d377f3da3d8615c4587166e7dfdf831f37903d015fa66787999ca848e71ce11
1.334 514.767509005 (97.17533595175833) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 238881 0x79a2ba158617e63b03d100b75568a8b913224ce452faf5683ca346a53cdc5f33
1.351 515.797044023 (0.19980019979826108) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3824 214218 0xfa9a6bef7c541039b2a3508afefe4f0b2a353873c466703dae072add91d5fe5a
1.417 582.850659745 (12.206572769783829) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3824 214218 0x8f21a37a176b003a5b67ac764368a578b0333e8bbdef9b4b3ce2623b004ad1e4
1.451 574.149486595 (-1.5040919705196034) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 223547 0x91c38ca0233efed0fd69a06461db982336a45ab7df8dda9305ff16c8c2991fe4
1.506 5.800000000 (-195.9996516013469) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/5145 185816 0xa1bfeb3b8691bad84dd39f16b87c75774ece99004834425ec1e7a400d2c30018
1.788 875.104765308 (197.36634413688427) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 238881 0x1bae2bc27adff6a2b0db8616270e4075ab161ca860bc5fc9a4737ce04085e9bc 5876563 5876563 / 0
1.831 976.791066605 (10.981859729330296) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 223447 0x127023b3ce5d07f94075c90ff9952baf0471b5e527bfff1734d74c6035954cb1
1.838 583.850659745 (-50.356260533800004) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/5145 185816 0x20790a609da2131a127d42edad87a0cf4a5de4a24838c50332e7e045e8a51afe
1.870 976.054127211 (50.28556495827496) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4069 223547 0xf36fbaaaec124b14dccdb089c87195eea47a2e90155e849da02d45f2e6158310
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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.