× 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 #1591 - 2018-11-26 11:26:58 to 11:27:07; Start Time 1543231618.9005415

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 10.000000000 () 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/32499 1150000 0xecf68ab073d37ac749ed544de0d84c924cda5bd2851626489538b1c91f063118
1.346 10.000000000 (0.0) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/10732 1150000 0xeca5679588af8513dbfc7257b530d3f1e8c46c2b417a2027eb933970814082be
2.765 10.000000000 (0.0) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/21570 1150000 0xb513acaf82aae38c3ec57c9ba782be25644306f0872a11fb52a20912252dee82
2.978 11.000000000 (9.523809523809524) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/452 500000 0x49afae762424ed4b0c38fa37c993d47024379a571e490a1ec565778a6d2bdc7f
3.398 38.139974464 (110.45986392965173) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/452 500000 0xc91a00141c98c2596dfa315c188d1a55a4c515151ed307b63bd8e5c9c4bb4561
4.013 48.700933392 (24.32254380737758) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/452 42000 0x20eae53195478b74b5a6b94faf63b5f7d8998775f254a4c831833000f773fe68
4.038 43.098171144 (-12.206572768480148) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/452 500000 0x73be8829da060c2291a3beb80da1f01bfb714f2e63e24522df536d1ae8b557d3
4.346 12.429999999 (-110.45986393472676) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/452 500000 0xf4799f75e4b3cda1c576337ffa6451cd3fe0392c280f5545f69306612c2db230
4.694 11.100000000 (-11.304717374046099) 0xEcC996953e976A305ee585A9C7BBbcc85D1C467b/6770 150000 0x6b1a9881e6b348f69d09f3731ae5426949c7f2050372db544be54e9807ce7973
5.919 8.000000000 (-32.460732984293195) 0x9734146F6D1454B5bBe4f6eFBb435421e27F682E/103 80000 0x2d2c56e1cb72749d141e37e6f58c29cce66e903e00f7468525ed7990c299a4b5
8.431 110.000000000 (172.8813559322034) 0x699D53Cd35d253faEe82985019F54bC259860eAE/941 70000 0x1486580a0ee679ad8006211ee7a53c52d76ff028a77537881ae9ce2bff35feeb
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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.