× 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 #4 - 2018-06-28 11:00:48 to 11:00:54; Start Time 1530183648.5675428

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 42.714462193 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/3813 199020 0x52bfd93b40ebd42bc784d1ed5c27ce941fdcad26ed9abcecd275fa1d6795a6b1
0.413 54.348591549 (23.972312651370487) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238680 0xcf37788b7a2bf165d16ff3ee7797abd89efec5139773409014c8a0354c2908b1
0.604 54.457288732 (0.19980019962024245) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3813 234273 0x67561046959c452af87e13388691c7c799eee564c70224d5f2be55bc4ad690da
0.873 54.312182379 (-0.2668144866713895) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238779 0xe228d296c32ce47fb16aa2427e2fb08733ea323ea20730518d0d7a1171eac0f5
0.884 92.515371464 (52.03817415067742) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3813 234273 0x26290b39ef490fbeb87ba98b5f045b2613dbbe75b32e3ecd80fec63e4244fb20
1.124 92.330710044 (-0.19980019970508056) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238779 0xe2856b11aa75cf2204e8193e3bd3dc49a254693ce319e4aeb327a03951f6fcad
1.504 156.962207074 (51.85185185137643) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238779 0x050d4b9380253815f6ede3aec052a54559592d51d78d7a339b8b55dbb8d77158
1.513 157.276131488 (0.19980019970609791) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3813 234273 0xeaceb8ab2992dd23ffbf53932b537a77d8b54b3161f0766739947cc203c0764e
1.879 266.835752025 (51.66543301239129) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238779 0x961b926c31acc150dd4dc787749d61267bef9fc959c6eb54339825ee2a248f22
1.886 267.369423529 (0.1998001997814991) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3813 234273 0x142fb66edd79c0c15da825bc54ebd1c8cb1445972c57952945136c0b84092345
2.252 453.268050217 (51.59282814468871) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238894 0x215efb8db12a79a55a37420145e9e00d423cb730a5ea04423dbe55e13fcbd05d
2.254 453.620778442 (0.07778863601651656) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238779 0x057097b013684c394ac288f9c9d9cdd8eb21d7d9ade3badba9ba0fac37ce23f1
2.439 454.528019998 (0.19980019960571255) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3813 234273 0x5b5019561006fb9935e0ad71c1254c2e1b23a962fd5cfcd60bdc1cac70075811
2.625 514.352719003 (12.34923899234171) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3813 234273 0x546a3269857c5d76eaf30539d7630a959c06942399aaa79235879622d415d04f
2.809 513.326066870 (-0.1998001996563298) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238894 0xb5910bdd12806b2cc9ffa002f9cc9c7a9ff7335f6f3c19ea825bef1a3086b95e
2.995 583.348549300 (12.769965019258828) 0x7E77777772d74Cba60638F3C19C60A3387172a06/3813 234273 0x3d5fbf1de7acfa703598d104496dbc878d1033a36da82e90400b1186dc7a7637
3.104 582.184180939 (-0.1998001996496896) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238680 0x0ecc1f0d7fa6194f7bb6309eb546f673b538789ed0ece1069c221fa99a7dde0b
3.191 581.794164520 (-0.0670143771181932) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238779 0x659aed2cabc93fb646ef9d0402289a690834fb6d7c29f01ed356a0fe2fc948a5
3.367 659.323584913 (12.493483463340851) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4052 238680 0x6306e56ecaea9edaabd9713a92d29a089531f85207fa2d049c870f60429ab75b 5868720 5868720 / 0
5.352 16.010000010 (-190.51727894632967) 0x13303476fec8D6A06Ce236D7badA4e359DBeCA11/3147 631200 0x22c1a6c88e9c1f2d1932d4eb68b900a4199a3f11623e1f233cd1a756b658aac9
6.401 5.000000000 (-104.8072346954749) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/5133 185880 0x4f12462ff1c3f3518fb3a56d66b5e0ffcb9f79d9681aefa9f4dbf5f9ff5d0c6e
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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.