× 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 #856 - 2018-10-10 02:28:00 to 02:28:08; Start Time 1539138480.390474

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 14.000000000 () 0x41FE3738B503cBaFD01C1Fd8DD66b7fE6Ec11b01/3664 66340 0x60cd5f8971b2dda57b204e6a7006b903128fed680685156f1b138a43b6a4b56e
1.699 20.000000001 (35.294117651903115) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6636 22000 0x6a37b1bee14121529241635807a736fb5e59cae157d18c8eea5abb5639e788b0
2.960 6.000000001 (-107.69230768402367) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/19703 344615 0xf38fe96839742972e5aaa095b5307dc5a21a5af187998bce0370ee2e5e955766 6486283 6486283 / 98
3.452 6.000000001 (0.0) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/6637 344615 0x33903b6a7884c337e01d0377f4604951e8c6a4772b5386aff45ae1fb9fcbcb10 6486283 6486283 / 97
3.655 6.000000001 (0.0) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19687 344615 0x64a97d3ab769b2a234b52d65d83fce7d8a47091ba84aaf65280a3d1faf5c5ba2 6486283 6486283 / 95
4.119 6.000000001 (0.0) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/17773 344615 0x21bcaf99393ff581624d609a07d3c9148d82ce904e2e6a3e0fbbae20ac50495a 6486283 6486283 / 96
5.310 10.000000000 (49.999999984375) 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/12804 211696 0xdc3df79bdbe55c0c8b2d6fc3e26e3ef4c61ac55fff0d09142ad04843d5b83e8d
6.731 25.393718619 (86.98559642578144) 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/12804 211696 0x138ef69708f28013a8568185b4864da2cfda77cc8356e6bf4e897e31746e9893
7.628 120.000000000 (130.13805861711674) 0x10E9d62C705181c0964d7FeCC29F06FF0d7596E9/3786 21000 0xc0735bf1f5d5b824c6d82214a3724e9feb550808fe2fd8f3a03a85a28d9b4aad
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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.