× 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 #311 - 2018-08-24 10:56:48 to 10:56:54; Start Time 1535108208.6138365

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 333.000000000 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4133 213508 0x50ec4562ca3824598cc41ad7ac90fa4adf07d9c9ed1c33646ffb1a0fbb470447
0.390 4346.951704262 (171.53816782367738) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4518 151505 0x1260a6896b990569b3780d1604c62eec765d74fc3c79de53a60b2ae587d6d0a9
0.590 4355.645607670 (0.19980019978816946) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4133 248761 0x3e33ab4bde914eaeaf6b6338bada31ad78c7b30fac772963cbb18d9f467c138b
0.884 4921.879536667 (12.206572769951027) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4133 248761 0xf978668e9b4e4eef35a995862b720c4144df145e4cdf12164fac2a12893e0e4f
1.009 7375.342788423 (39.90272253190387) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4518 151663 0xd203eca04820cc36e844e5776ae5af3101a68622d0c835fcfa52f95da7e08605
1.029 7390.093473999 (0.19980019978875205) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4133 248761 0x8088cd8fb77dde790791fb6a0db3dbbf76af3605c59f4653d97f258a1e09b4a9
1.170 12563.158905799 (51.85185185185704) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4133 248761 0x9efd824233e06615ebadde175502e7d83b551d9642e53197139b5e9399798810
1.306 12538.082740319 (-0.19980019979512148) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4518 151663 0xf14449c82efc2806a774a49157a9ce37e35ce64475094ee5a881ee956518c9f6
1.459 21356.573723037 (52.034697517892226) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4518 151505 0x20998ae7956e6b8a331709dece8ff5930899c1e1b1f6a4477aeeed960fb521f6 6204674 6204674 / 273
2.393 4338.436934367 (-132.46257816800116) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4518 151663 0x7a2d8b7d41c8e719833612a755e7385ef67c919dd723fe1e742d49a2904e3adc
6.289 21314.740658542 (132.35244376796078) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4518 151663 0x2008755880c14c41ab1c3d4326be9b971f44c4744f4f22ec6c47479efeb6b67e
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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.