× 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. Read our full paper!
*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 #534 - 2018-09-17 11:49:32 to 11:49:52; Start Time 1537184972.0687466

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 172.639275908 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4187 198892 0xc41654fe1de56f506b2a09bd7de4ba2c54d21d070a15eaefd597a7b1f98a571d
0.563 195.082381776 (12.206572769932624) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4187 234189 0xebba806f7d8591393b18a1ce5c5e4074eda16d212a9b85669d48f5d1cfe86330
0.805 305.226239804 (44.030365769096726) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240197 0x47c0b63612ada52afe5f5b5931660bd760ee329c318e042396240ca16f8918f4
0.838 179.544846944 (-51.851851851607364) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240505 0x13c1286ed3fce8f66b0ed2671e43ec7dc99a68a9986eceabe221f3915572fe01
0.933 518.884607666 (97.17223650353803) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240450 0x739bcae9680aba2345cb7da24018561c2a793d84d556acd557118d3b47e92aec
1.037 519.922376881 (0.1998001997363442) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4187 234189 0x9506c44515a3e50891e7c1ec8e9f632e80e2de5b46949a7806e67806bb393e7b
1.234 305.836692283 (-51.851851851833906) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4187 234189 0xaf6f8341f78c784955ba83d8b4ae0f437b5bc51b01e375e2606b8733c8324296
1.790 882.103833032 (97.01952723537136) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240450 0xaa64aa050c9e734156bb15837045be930aa105f990796bc43be923c60b4f6538 6348150 6348150 / 0
1.821 518.884607666 (-51.8518518518307) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240505 0xe848e351ddb2005b68eaf8aa730082269ad407cdb77af818549d64c530ac9bec
2.292 882.103833032 (51.8518518518307) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240197 0x83cb8a2da01cf0b27f7f3ac10e34fb2901b0f88243e61c03b3abad2c34ac4140
2.382 179.544846944 (-132.35244376772215) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240491 0x639e7cf15077d7a88e239594bce62fa4293c371ce7129ea417da05c935761e52
2.974 6.500000001 (-186.02487495303416) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/15270 492836 0x3f1d52b2f59b1a3938cb6cae679c8410a2fe481072da9a4cb1e7d5586e968b27
3.272 6.500000001 (0.0) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19279 492836 0xc84801e18f5e9b716545762605afd0a6a7f9bfc2805421468514a8f2ec6e99c8
3.394 6.500000001 (0.0) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5632 492836 0x4607e977a2987f32f8367f9616419b9270151bd2406f27e6a70289d4fb249b45
5.377 6.500000001 (0.0) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/7218 492132 0x1954728318f5c1968d7328be5e93419db1e09e165dd9f849e9b725eaf0e44117
7.576 179.544846944 (186.02487495303416) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240450 0x72e83ffa6a2866b0ddc65f939dfde4666846f73e9fdf3d5240dc76d3fef319e7
17.265 305.226239804 (51.851851851607364) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240450 0x87fa46a02d9a9ea1c758703464f1727e2624c8fee69aa7aa2a26dc1ceef77901
18.969 882.103833032 (97.17223650372094) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240505 0x1e30afb75eeeb5cf58058105e76f46c7869dd038f3811a5d71ea8071d605a823
20.069 305.226239804 (-97.17223650372094) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4698 240505 0x485ed4f6d239f93088bf0559b6f400cf52cbbe699958be9f9c1f3d2ae3e382a1
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This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1650441.
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.