× 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 #1572 - 2018-11-26 05:03:19 to 05:03:25; Start Time 1543208599.2960289

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 11.000000000 () 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/90 1000000 0xb7b441da3541995e735b84a916f658c7e0592a33ebfcd0f9141c029a9652799a
0.824 12.429999999 (12.206572761937966) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/90 1000000 0x7a472bb7b564c99736b5f4b36e6117d67a405733192bef645263c9056396d3ae
0.827 12.429999999 (0.0) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/273 500000 0x9df621e5d35b2ad3843b3890a899f54ee732004fb8c2d3791b13e0c26ffc7455
0.935 11.000000000 (-12.206572761937966) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/273 500000 0xb7e510e97ae47013a57276c12df7d0517ecd44fca33bcde754ffd9a2c7260b69
1.497 38.103500089 (110.39335297840258) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/90 1000000 0xfd413f1b36469d67f36f02c67e6e96941e7af679bf982596aec15f48c847255f
1.502 11.000000000 (-110.39335297840258) 0x57bD0069505c4009Ebde6A87Cb92150751f0EbE8/733 1000000 0x036694648f0981dd500069f1cf9524bc45ab233db31c48b2d44ba1adc820fc8a
1.937 38.103500089 (110.39335297840258) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/273 500000 0x39544aabb8dce7a6d0a8f8104fed4d745a44cc066fd1aa5f5c7e871555383b4f
1.964 38.103500089 (0.0) 0x57bD0069505c4009Ebde6A87Cb92150751f0EbE8/733 1000000 0xe8bc445c1540e41150139f1c57f98a7072face6766ef4f93a2d7e04f10806e2b
2.466 43.056955100 (12.206572768634155) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/90 1000000 0xe8cf1b9c1c1f19eaa243b499cb4e7d21f7f3f206fb726f2feba3c757a0e935c6
2.535 43.056955100 (0.0) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/273 500000 0xe4d6fa906238a092dc2fa52969efd6393469af4a54fbc35ec1a992c537ab370a
2.624 43.056955100 (0.0) 0x57bD0069505c4009Ebde6A87Cb92150751f0EbE8/733 1000000 0x97796b584f8433c7134d1c2067909bd9598be7311336c33331876d68ab1d5ecd
3.253 48.654359262 (12.206572767905394) 0x57bD0069505c4009Ebde6A87Cb92150751f0EbE8/733 1000000 0x22be40f1b57810e5164a1e71da727f59ed969052683f6cd52cbdefaefb2a11d9
3.288 48.654359262 (0.0) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/273 500000 0xf4d8178d0a5574736b0d23fb1ccb27b6ac82dd4cc0785eb1aef360bc96702e0a
3.303 48.654359262 (0.0) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/90 1000000 0x531b50b67c12bf1e013a4c75ad6621fdf1a33883e92869de0fdfff1afaff5049
4.163 54.979425966 (12.206572769844326) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/273 42000 0xaf17a49a3be2806a18c56fcbe4a11cc5e6b31178ceaae570011be56fcfc75185
6.121 134.000000000 (83.62875866520717) 0xa8660c8ffD6D578F657B72c0c811284aef0B735e/56671 121000 0x7b5abb4840ade6b704e5368a667c88aeab575eb01b200f007542ea4d726c5125
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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.