× 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 #1231 - 2018-11-23 08:47:17 to 08:47:22; Start Time 1542962837.1888962

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 40.000000000 () 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/536 300000 0x0ede5809b44d81f0b1edc64f062ad0fcc47578abd2f0711908aab346ab7edf45
0.272 44.000000002 (9.523809528344671) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13731 324129 0xb8e5a8b8e1847ee8e622ec2dfb4c7e77e0d8f92bac00333be0cb3ab4b13c13f3
0.416 46.000000000 (4.444444439901234) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/536 300000 0x9e7a64d1fe052de2394d605a8b6c19774f2e17f24d01e93938897338943e40bb
0.659 53.240000004 (14.590890777324027) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13731 324129 0xb66eeabf3d2786137663f629cfdcb20d396a6d85c96ea8418b120e349100a5f2
0.780 53.240000005 (1.878287002095186e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/536 300000 0xde362576e419043f0d882d9115da10ffaa9ad40ba3d7c13fd1b0d1c075bfb5c1
0.971 64.420400006 (19.004524886800915) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13731 324129 0xd369bf7c93fa02c2f7b898bd1cdb9fbf6fe922d9f0e6bb1870cdc96eec2f73c6
1.086 64.420400007 (1.5523033074912608e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/536 300000 0x2c91682ccbc44478f5b36c37fc17e53561607bde89996b2035e25947b94db729
1.295 77.948684008 (19.00452488628031) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13731 324129 0xba261d49e457607f2de85eb3b08bdbbde26df7ff02fc89ef2f686cafb6aa1c00
1.467 77.948684009 (1.2828952954368721e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/536 300000 0x6daa38e0ba143738189c97ff85503646a75b7bc11511d4b00b14d298a0852faa
1.768 94.317907650 (19.00452488594273) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13731 324129 0xe9e45979ce7a1510b67034c8467d1ed3842f095da4a63f80bc5f5869d2896269
1.950 94.317907651 (1.06024404581318e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/536 300000 0xd361b16925e10c3a605bdbec08d6259fac6b4ea0964493b64dd486f796d9542c
2.101 114.124668258 (19.00452488712964) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13731 324129 0x7b2e224afc1ef887e41a10b565a71beb5ff4f343dff2fa849d0a62acbe0a4511
2.293 114.124668259 (8.762347485952233e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/536 300000 0x5cb2d77ecba36c9a0b8efda7e0ff790f7f23e33f737aa865596fe4eb1bf929be
2.464 125.537135084 (9.523809523094231) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13731 324129 0xc1f3c3739c1b5cc8c693d620d0fa059cec656086c4cd70c0d7f2bafe30eccac1
2.698 131.243368498 (4.444444445275245) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/536 300000 0x0fbff0f38d475ae310a51caea2a8dc3e65b9b73458100b0b55bcc33ab33fa8a5
5.643 13.024662000 (-163.8876001702108) 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/218523 104802 0x5ad64c371dbd5b2a54891d3f2c36bf4488d6d31fad49dbe9dccba8f55072d3fe
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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.