× 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 #1235 - 2018-11-24 05:29:47 to 05:29:53; Start Time 1543037387.2595885

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 6.086822721 () 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13736 324129 0x3b74d011ca05fa652302740c175ccb4f4845a42cc361af6784835e304a674d3d
1.693 10.000000000 (48.65071676200763) 0x5e01605697EA13F7F3f961F05b0d19df9B725f23/2435 150000 0x4761ce2ec2c0486eb3a3b198862d76813c2db6ad9bfbcc0253d2ffb641c3efa2
4.624 40.000000000 (120.0) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/541 300000 0x9820b464fbabbd34f952387e12e65a3259a87cab705857d5ac6e4f5d8e5d3aee
4.813 44.000000002 (9.523809528344671) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13736 324129 0x73addd8ccf95957280575cecedbfc0d1b7dd5652ab9aa08b6ee1c8781f958367
5.012 46.000000000 (4.444444439901234) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/541 300000 0x74a5e3f71affc606fc3582a2d883ef51177794ef5f58613606d1bb7539f635cd
5.128 53.240000004 (14.590890777324027) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13736 324129 0xc3a8734853a115c657faca587752fd7108be2375c196e0343b8bb0815ad7dd3e
5.378 53.240000005 (1.878287002095186e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/541 300000 0x18e7fe1404e64402dc27c7bf216126316a7ea86fefbab054f56b0ba7c80d08f0
5.572 64.420400006 (19.004524886800915) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13736 324129 0x5bfc9a0d8227e3f5a2016499d0d861e819f0f53c67cdb97688b26284e37b9e97
5.829 64.420400007 (1.5523033074912608e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/541 300000 0xa1bb9cba146d66e302e7cee6c292ac057b45b5eb4d2f37b4da36be74430b0ecb
5.916 77.948684009 (19.004524887551625) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/541 300000 0x88b51a37f9ad75cf0372b59cca27d0f72cdaec9db75e5decf24ec9dca22e1270
5.964 94.317907650 (19.00452488594273) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13736 324129 0x868b8745b94868baaca8d7ccf91bda5e10ce838532b09b7b294e0a90c0d10537
6.093 94.317907651 (1.06024404581318e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/541 300000 0x4290811cbd4eb08e2812a60dc584debd1526be2fd2439e80c1d0243695cc94f4
6.160 77.948684008 (-19.00452488826471) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13736 324129 0xceb8246e9744a5bdc8a19df7de9bde86d90b99f47dcfa0eb835329733c20b686
6.454 114.124668258 (37.66892577571128) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13736 324129 0x7b9df1e4bed2b2b881c15804059ae1e54ce9d868fb83eba94016ab6739843d44
6.509 114.124668259 (8.762347485952233e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/541 300000 0x34caa6b52cfba4aa46a43f512d11205c8a67ad1dba8b4ee699e339df69c954d4
6.604 138.090848593 (19.004524886597956) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13736 324129 0x469da14d15069387750d11a3fd1a5c2068bc5b711292cf0831c9ad1cb8723b52
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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.