× 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 #153 - 2018-07-31 13:18:35 to 13:18:45; Start Time 1533043115.7950346

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 82.412385041 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/3985 198284 0x5d419140ded2f23732c7b47ca2324505141ae39b229320295c197f40b9888343
0.952 105.294592021 (24.380774053424727) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3985 232973 0x986e1fa4f708a515d23d6db0b607dbb9702ef2475df1c897be2966077e96981a
1.425 105.004482842 (-0.27590152661298445) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4284 240228 0xc5789b24a7da68d1c1d6eb0616fdef07ca85f35ebd4ad091ec37def4ad92a025
1.699 178.864636072 (52.03817415051506) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3985 232973 0xd720716c7bec29c40075b258de264c725e5976b589f469c0cd521d518bf62138
1.984 105.084423175 (-51.96721770634252) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4284 240116 0x818845772fddb825b0e8b31c90adbd02765a1694e202c374bb313b5902545e1e
2.271 202.117038761 (63.17197514262809) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3985 232973 0xae97e99522e2a7f7ba980e2a9c69fabb194f4beb0f0da49675377bbfec4b21b3
2.822 304.069881322 (40.28268551241217) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3985 232973 0x45943c19eccf124ad52967c8e06480ac781d3f4fababdac9f9e875063870f87b
3.381 343.598965893 (12.206572769703692) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3985 232973 0xb9304b1b16c107520126a3c3fc9a4576a2315a20a4106f6679ce0884f9a0f659
3.394 877.007941140 (87.40061557468786) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4284 240228 0x2bb8f8a3b67446ddb842d88bd31161a4a9fa9fd1bca9ba14c3d538df05386868 6063309 6063309 / 0
3.646 178.507620831 (-132.35244376779565) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4284 240228 0xafa7430ab4badee2dcaf5849826e89f8f12e2d5387ef935ed25cbf2c7934ee6f
4.517 516.918798248 (97.32479760121299) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3985 232973 0xb8bbe3a842426fc919008251ec2502ae92b28bc9a2ab00c861aee0d73a5d4d2a
5.306 303.497999466 (-52.027408355526916) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4284 240211 0x49470f735c05159eda49f0e31394489e16ae86b701f3544ea000505528fcc0b7
6.958 515.887024200 (51.84108046880159) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4284 240228 0x68aeb9fdf8db959662db12fe5dab6de0e665d673f01d79b8feed451a1ae773de
8.655 295.113101400 (-54.4448553905378) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4283 240862 0xce6c44643444599280417b9c2e35ee194d87754ce24dff94660944da93258f61
9.237 353.875327767 (18.108867192724354) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4283 241022 0x543baeb7e3932ca0a225b57aed7fec60b9f997fac5c592681a1cfca5b687f5b8
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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.