× 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 #759 - 2018-10-05 07:07:35 to 07:07:37; Start Time 1538723255.3672504

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 134.000000000 () 0xa8660c8ffD6D578F657B72c0c811284aef0B735e/50617 121000 0x8fb99cce8ada3be7e51906224fdade43ae6e471b25120e5422e08da3c7470433
0.915 24.000600000 (-139.23921807891867) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/18678 429853 0x611da5c2317396638c5bd0c3349c4bc4d067b562e424628313f4b511b133f44b
1.246 60.000000002 (85.71224491525746) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12998 442984 0x37662d7ea6ae02a261f2a369dc562cb7edfe54cd7d9f618ab604d5c6e685dc5a 6456592 6456592 / 7
1.246 60.000000002 (85.71224491525746) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12998 442984 0x37662d7ea6ae02a261f2a369dc562cb7edfe54cd7d9f618ab604d5c6e685dc5a 6456592 6456592 / 7
1.275 60.000000002 (0.0) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12998 442984 0x625e82334f89c1893b9c25fafa4a5405c7587c3478e1ecfad7968171ab509b42
1.733 12.000300001 (-133.33194444745376) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6403 415365 0x5391cd5c407976b906d85aebd42c41508e9ff8ec7c2bf8ef278d443a56bdb9f6
2.414 15.585000001 (25.989929417045314) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6403 415365 0x4734d9004a1d4b352cdd263fb7f114f47b292ecfc9fc62c9226ed9027deff83a 6456592 6456592 / 50
2.414 15.585000001 (25.989929417045314) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6403 415365 0x4734d9004a1d4b352cdd263fb7f114f47b292ecfc9fc62c9226ed9027deff83a 6456592 6456592 / 50
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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.