× 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 #1576 - 2018-11-26 07:41:46 to 07:41:48; Start Time 1543218106.478092

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 11.000000000 () 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/238 500000 0x2849d80d3fef14fa75480e0a700fd369a196474252e0e94e2b0af1657b7a38fb
0.275 11.000000000 (0.0) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/345 500000 0xf12ac40d4219af4cacba2f331169803ca518ca845cc462c451915d2f87c84e8e
0.708 12.429999999 (12.206572761937966) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/238 500000 0x62344aae1def20c57c5f47d2195008658f976e41d68afaa7348d36942af225a5
0.748 12.429999999 (0.0) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/345 500000 0x63f128030bd432718e1f069f1a9a29f824e50043b7ec1534902c6ec47e7e1f0d
0.841 38.139974464 (101.68078880012466) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/238 500000 0x1786f40cb92a8d302337b6da6c275e5ce779001e39bd16c6102bcd711dba73ab
0.896 38.139974464 (0.0) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/345 500000 0x7dd57ca981509a9e0091ec2b94cfe04f321f3387d7f1d1148163485a530e50f5
1.050 43.098171144 (12.206572769213327) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/238 500000 0xd1b69f462f87f7cc1904412f88b362b1a5b05c5c91a5f0d13897eda6904b7988
1.131 43.098171144 (0.0) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/345 500000 0x3b1b0292eb7ee82a7fc92fdeda635532c487893b2430c7f89a41c8277cd6025a
1.350 48.700933392 (12.206572768480148) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/345 42000 0xd4e3bd90f650d8498157e51e31134696e7e2df27493c70c49f3fdc3b0c025a15
1.454 48.700933392 (0.0) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/238 42000 0x1bd0f46b801400f4752d7ee154ddc6bdf982ffeb5f9bcb52d096845166a00b52
1.601 110.000000000 (77.251047360368) 0x77521132FAD812cedB7dd5b4f34835E71821B4EB/482 150000 0x2836b15e9afb23d84c92654b10b16b91ad6fb907267ff0c2a5a619ff8eafe8f2
2.092 9.550000000 (-168.04684232538688) 0x0CE34F2d35B9553499A75bb5100f72326201747A/1587 52500 0xcbcd64a2a925fedd76d21251b343b1df6dc2ec1e16efbb34d6c542d6b4958946
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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.