× 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 #819 - 2018-10-08 06:53:12 to 06:53:28; Start Time 1538981592.351427

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 10.268211289 () 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/11504 206367 0x6365cdff3da78ff590047aa2b92130c2c1decc6f26b92febfd5c753c0b6f184a
0.234 11.000000001 (6.881525691293806) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/19220 455859 0xff648ea742b7a449f5798782642eb4fe95c829918f203c29953735f53ec694d9
0.415 11.000000000 (-9.090909090495868e-09) 0x9D22a13c36E10B9630dDa6A3A3C0aF2076AB88D5/2880 850000 0x2c1b784404e012d11b0e91d13528fa13d098303f9a27d654d7ea78f6e2877d6f
1.502 11.000000000 (0.0) 0x3bd189a9b1c11684b08f6464866dFa431362A06e/1318 1300000 0xeac6b9e187c5875845679b57e4d0067fdda07b50e0c49ef1eb27f80de0ef9772
2.698 11.000000000 (0.0) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6545 588082 0x1b06f1eeb9c8c7e0680bc5b7c7fc84444273107b1dc940876148c32f21caed7a
2.788 26.000000000 (81.08108108108108) 0x2CA860aD6B4D2C79A88fb5B1628810f2BF487287/1827 600000 0xaa7892dd7e73bee54289d9f8649def04fba6363b0c60b88a8ef803a01b4ccc15
2.980 26.000000001 (3.8461538460798815e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/19220 455859 0xb4012a5386c4b1fc21db7b106e51203db1cd761fa5ae9ae0f50914e4bcb2f84c
3.939 220.000000000 (157.7235772343182) 0x2D2ca04B65A8c1D007237698d215FD12C7dA4b3C/50 250000 0x15e37f3aecfe254ca61cd97d652ef900176f4b018e872d1353454868d7e961b1
4.070 220.000000001 (4.545454545444215e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/19220 22000 0x3dc9f209825124eb391344880ae0dcc52ec8a02537c291e6328b41da8491b4fc
4.877 253.000000001 (13.953488372034023) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/19220 22000 0xf00c35a78a402e6d89faf6e74faff66875ec4cb960e0420f69cd00831e83c87a
7.073 22.000000000 (-168.00000000011636) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19644 455795 0x77e04b9423e5eb5cbe70d0ea670bb161a270433a62e5a5ccea0d70f63c5353ec
7.315 220.000000001 (163.6363636365139) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19644 455795 0x2a28113b21137c2ccfda4862999422cd47ddef2436b398f368ef9f6060dd462b
8.469 9.113733000 (-184.08871806918668) 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/174090 98032 0x212b5f1a6035e302b0470ea3af16769a4a3891d0094b9bbdd16db27bc79547f0
9.316 6.000000000 (-41.204022857886926) 0x18a0451Ea56Fd4FF58f59837e9EC30f346ffDCa5/1978 300000 0xc5d75f5b9edb18aff72e911c520231905cb55c056bd5e961107f4188e50de8ac
15.664 7.000000000 (15.384615384615385) 0x18a0451Ea56Fd4FF58f59837e9EC30f346ffDCa5/1978 300000 0x67fecd18ecfd9c9c87bdc78527be663dba46f10642d81462b4a8c43bb515ba95
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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.