× 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 #85 - 2018-07-15 05:38:39 to 05:38:57; Start Time 1531633119.565246

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 61.000000001 () 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11458 339129 0x2b1c68477bcd4e940db49186a571e3565af73c3eab3c703bc2d83dd121753db9
7.071 70.150000000 (13.953488370461658) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/419 300000 0x2ce8dd20f7ee3adf2fa738661016ce089b7382cb0359d7caad483339069e991c
7.356 77.165000002 (9.523809526395494) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11458 339129 0xd8e136b6d2d67e0cc97398a52cffbc2f4ac6e2f97ccd67dd230fff863db8e1c2
9.020 80.672500000 (4.444444441853876) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/419 300000 0xcbd237f8c58f9d571eb18787b67332546fbd24057e2b22e2cdc4a567e9f1178b
10.125 93.369650004 (14.590890774112111) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11458 339129 0x86e17c055f89cce625916c63c616be9c6ebec3517edcb59259088bb5bc9f5a5f
10.815 93.369650005 (1.0710118330226198e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/419 300000 0x102d72f99395d8cadc5243c19c72ed136ce6ae9d832b6e8669527b29d23eec91
13.214 112.977276506 (19.00452488683397) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11458 339129 0x55522623dde7bdfb0b48ad714674c502f67eac0532cd56f727f2fe9acc2551e5
15.905 112.977276507 (8.851337462914203e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/419 300000 0xf765c2a6394ffb179ca78937fe2488c2e1197dd5c6e659926a86c02c2a8ca95a
17.200 136.702504573 (19.00452488653712) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11458 339129 0x3c6d201b2a7f80cda90bf3c3cc49ddcbc85f8bf2174544506db4f826ac30278c
17.894 136.702504574 (7.315154927994286e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/419 300000 0x56f21bc89a55ffd5bba6dd10a5ae66dc05e342e37d07dce2d33664e921a06336
18.319 165.410030535 (19.004524887153416) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11458 339129 0xe297c9d064df2d6d8301223744ff9dfdb9ab26b75f8f58a655bc0680e742df66
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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.