× 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 #278 - 2018-08-19 08:44:34 to 08:44:45; Start Time 1534668274.8235464

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 40.000000001 () 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12059 354129 0x4d6f640de8e2774acffa6a110c49bcaef9b4b95fcebaae5da8ff6f7a52dab428
0.980 50.600000002 (23.399558500328933) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12059 354129 0xb4ed32ba786ed8691fd72358b55abc36c2b3f9b77e9b7c58a0acf5f7e9197eb1
4.316 61.226000005 (19.004524891053677) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/443 300000 0xa919efe573524fe2ae68ff621112d1f0701ecc86a18ba5b766ef73ce5f6e718d
4.766 52.900000000 (-14.590890777973867) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/443 300000 0x9bcf0cb3931196009ea17c8bc4f59e7719c469ae3d718857735987987b27bd45
5.043 61.226000004 (14.590890776349266) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12059 354129 0xc2c2f644473ab5febf7d1f24995d5440e817694bf8af8f54635194427eb33c96
5.827 74.083460006 (19.00452488842949) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12059 354129 0xa2eed2dbf12d06fb11e97ae11740b19577fa42ca84f0f26ba3a44f7c9c402221
6.144 74.083460007 (1.349828963053644e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/443 300000 0x146ac50af23cf71ce4f936f0334730efe2295c73e4c090e06067e0802196fca6
6.428 89.640986608 (19.004524886358247) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12059 354129 0xa40cd17d445557981d5a6907ee52131e517913d6d4ce636a49b182558a46d029
6.732 89.640986609 (1.1155611264827125e-09) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/443 300000 0x4f7741094b9d1e956e1697b794981291cc36d89212fbd22861b34e2e1e19a2d0
6.774 108.465593797 (19.004524886978327) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/443 300000 0x54f3036ab1ffa37984eb6ddc487aaad46639d01a099822315a890363d6256280
7.002 108.465593796 (-9.219513441987613e-10) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12059 354129 0x8f6b7e47e2d8004749401811beed0ce21b3cbfa531e561e9b20548bce408a56b
9.511 158.804475879 (37.66892577549892) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12059 354129 0xac7d78224ff8400879cbb9decaa7c449bba28d82e2506f3af26c0b2db7a19537
9.620 131.243368494 (-19.004524887664093) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12059 354129 0xcb24be013d90b7bba200d2b7a772e2c98692359136a37daaeeebdbc5270550f4
9.927 131.243368495 (7.619432596641307e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/443 300000 0xd98b2de3af1d28eab30f6e4568a320b7a8b366d45b99316f15550dee22fbbdfb
9.969 150.929873770 (13.953488372587525) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/443 300000 0xb5e598025074bc120dd720f03a4335636ed1154aa044ca2dedc95a9b41b1a66a
10.216 144.367705344 (-4.444444445287286) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12059 354129 0x7ea3d842020575fcaaedb3f402297955c8ba5428ed2c2734832c51a4f7812511
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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.