× 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 #3 - 2018-06-28 09:26:09 to 09:26:15; Start Time 1530177969.6313713

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 16.010000010 () 0x13303476fec8D6A06Ce236D7badA4e359DBeCA11/3146 1416000 0x6c61099bc8c0c8f07825e4ff273ab06d1784f0e0e6ae848572c70b045219572d
0.919 19.655860986 (20.444542058911132) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x20aa469bad8930d28c334576fd98ff3f084e8b8f660262269de2924d45342aa6
1.928 23.783591794 (19.004524890794446) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x8817e9d49f8191e3624ac2874f2ff562ac420180e60c7a54759e49695100d866
2.388 30.049113769 (23.277752472119417) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0xb9dc79fbbf30ee269a49884dc893b0da481b55932aaef606c65969c293e9e925
2.833 36.359427661 (19.004524888267827) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0xe3a6f90d311259721746577fe327a7fbe3199eb8ac3fb564584576d76e6d3b5f
3.213 45.700945901 (22.767428015525905) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0xf1c3809021c5b3b42cc3133e25c95967e3852452a12d9f707fdcf4c834f90d8a
3.516 55.298144542 (19.004524890085598) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x9803825939e36d5a187f817a5822d52087118c6e7526fad2df842305639c8b30
3.706 66.910754897 (19.004524888625447) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x346fb7dc659cfd84fbda8443eb78dcab076ea59a2c8c6504118bae105f1fe596
3.777 21.755860986 (-101.85320249638066) 0x13303476fec8D6A06Ce236D7badA4e359DBeCA11/3146 1416000 0x2f8ce1372985475877199d77c844312e1a6b5f52b80c3b24b7b8b6246db2de99
4.095 81.899725773 (116.04558262129166) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x92cc014b46bedac0e6df5fb8c492dfa77881630e239b5b360e578a1ed61f0132
4.337 99.098668187 (19.004524888547802) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x2312901691dc60e767bac00e6fc19fe769e5b75a8d0be1089ca01fc013f4326a
4.609 119.909388507 (19.004524887481125) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x6b4e01f341d4a87137cbe4a7a5ecffb448aaf5ea8495caab7952a046c19fb3eb
4.927 145.618537546 (19.364553793764347) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0xa9ab7a17af7d4ffaa52c76e1c34da3adb039bb6fed69285a42696e0ce4422d80
5.114 176.198430432 (19.00452488763147) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x5cf274d49e808ac89b28843943766510a7f6ad40c013a8498da1fd0ea82fdc9c
5.310 213.200100824 (19.004524887472783) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0xb2890ea2b910719ed81bb0f68d4d70088a5cdd9ec884403be68448f705f1eddb
5.508 257.972121998 (19.004524887246603) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x32fbfba2ae534490409b5507eb37e98d7e1b36f7b4033d4cb5f6846ebac7f214
5.697 312.146267618 (19.004524887011165) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0xe3cee0737caf96c2d22c27c8d24705c04a9377b27dcea3ccdcb27fd896519d8e
5.949 343.360894380 (9.523809523867639) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x36775961a09c00d75535cfa6a7db0fea7add8f4e4f6d800e84b43f7749ce264f
6.137 377.696983819 (9.523809524073686) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11278 433172 0x1c8196ddb15873a71caf28fa58d30865c74bcbfc4729eba82ec6c61cf58dfcaf
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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.