× 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 #621 - 2018-09-24 01:45:47 to 01:45:53; Start Time 1537753547.7498004

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 40.000000000 () 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/472 300000 0x6e73bb40ab33e81104b2ce5fa48fa5aaa578a652d2eac0fcbd94bd80b87e4467
0.215 40.000000001 (2.49999999996875e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12834 339129 0x54c89109b7dc037c9fdf56c1e55ed09ea3154e587c52d93f5696f39210330da1
0.638 46.000000000 (13.953488369605191) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/472 300000 0xa389ea38767e850fcf3b2d4bf5174a400ac321659406dcc5890600fc0cc62b37
0.861 50.600000002 (9.52380952775313) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12834 339129 0xb55c1645e9a285bbd9847108ba45674274c2a7514bed47c75d1d7ac6c2905731
1.052 52.900000000 (4.444444440493827) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/472 300000 0x1bf6fcc47344be92e1cde12fc5e5f4125cb58489ccd2d4ad1a5b800ca1d0b622
1.089 5.000000000 (-165.45768566493956) 0xECaB1fccD7c737CB8239FeB314D83C542de997fA/29008 800000 0xe388f9b7a6005b66494f8aef66ad8f11dfe8e70c68c5fc753f245b60fdc0c284
1.261 61.226000004 (169.80038051702954) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12834 339129 0x6fab36808906e74a56ac8a4493ef3154ea89b9152f4aa55903a56e5e7e7a2135
1.448 61.226000005 (1.6332930453181685e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/472 300000 0x5840eaa6c8049d59ac9011b7bd08bcda2f9398c1ee24bb19b417fca3a1b60e0d
1.607 74.083460006 (19.004524886810948) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12834 339129 0x4656e694e933e57a6dab2bc6398834e12546e7589249acfbbd33293aacc69d49
1.779 74.083460007 (1.349828963053644e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/472 300000 0xa208eee7ec397c750d07d123c6e713e95d95e8299c9b7adfb6424b8d5de7248d
1.922 89.640986608 (19.004524886358247) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12834 339129 0x702278cbc1d255bdf35579b6c9451ac848080697b22d13ab0f17c33e661ec83e
2.136 89.640986609 (1.1155611264827125e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/472 300000 0xe289bb8b27dd311169ec6da1e607f10e16474c710609ff57bc89f0529e8146ab
2.286 108.465593796 (19.0045248860647) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12834 339129 0xa961ca7765d16b5770a408fecbe9f8d1bceb905f4b3628130c46f287812c85d8
2.468 108.465593797 (9.219513441987613e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/472 300000 0xf858d7f4b4f6fae083675ef9aa831e01dc919f278dd862065354daaf2b509a35
2.625 131.243368494 (19.004524886598453) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12834 339129 0x8be2c161ad308c44a7ebbbd9042b29d300c51493feac70f222ee16c88ccff44d
2.816 131.243368495 (7.619432596641307e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/472 300000 0xde9d6d673c60684f935cc17b5e284c8f87df35d229c3c04516571ef454605a0f
2.962 158.804475879 (19.00452488690903) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12834 339129 0xd9ce540f2e13d7d1a31f0df3d98ef9150a3846363e417b643b21f48c10efbe63
3.145 158.804475880 (6.297051732715611e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/472 300000 0x1ad8e391aa5c8ea33f170a8cb33f2201df6394d01fa1700e4b75e32e5aaf77fd
3.321 174.684923467 (9.523809523238363) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12834 339129 0x9f591142aaf1175a068109da212a57797724ff101ab9d5818b06b5fb269188ac
5.828 5.000000000 (-188.869405616174) 0xECaB1fccD7c737CB8239FeB314D83C542de997fA/29009 800000 0x33da403a4c9b5312e67b8e5069ffa4f1fcc0127f66eb1049b5eb5f11447be680
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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.