× 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 #1595 - 2018-11-26 12:59:53 to 13:00:03; Start Time 1543237193.4507034

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 14.700000000 () 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/10734 628757 0xebdf47b46df315ecb3a1017245f9f6ad70aecb1f1e5d81dea410437a64685bc4
2.217 14.700000000 (0.0) 0x91BbA529a4e469758CD3832305586fD1e8161eDd/5518 1300000 0x4d10c9e046acb9d25db779c2ffb6b85a343c027f9ddc5fb8fb45390d71aa5caf
2.400 33.100000000 (76.98744769874477) 0xEcC996953e976A305ee585A9C7BBbcc85D1C467b/6960 150000 0x7113524e22b6077745442f6aff69780814fe7a54aa7de92a303a77e739a943ca
2.432 16.904999999 (-64.77352265303017) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/10734 22000 0x545809401a51c61905d9b6a3c9fa6514dcd1e66046acea3c05ab627a37ebb8e2
3.525 37.280622509 (75.20674882711454) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/538 500000 0xa8d92ff4c9a4f990e2fb2eff0448dae9ba37cce18ea4dd4845a329d69418ba7c
3.719 11.000000000 (-108.86612948746061) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/538 500000 0xc6bacc801ee700b82805ff41f2eb36c999304b5c758d99fc9d7f03aee3f4aefc
4.046 42.127103435 (117.17974977906869) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/538 500000 0xd7bd267f064eeb82273208ce197968c11158b797c320c71fb65e7c0fb8ca0ac7
4.225 12.429999999 (-108.86612949283798) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/538 500000 0x0b34f2d326ce63c2991316306abda909f66530f30d79ba1302fb12a596e83e3d
4.620 47.603626881 (117.1797497835933) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/538 500000 0xf6762e4915c98e0466677f2474501dcf01ad089227f42e225c1f48d6f76aa31f
5.461 53.792098375 (12.206572768971446) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/538 42000 0xff91de9b18eec1b6daef2b0d864371e626981273476720857d28258568ce2e60
5.707 110.000000000 (68.63322734447507) 0x699D53Cd35d253faEe82985019F54bC259860eAE/947 70000 0x5814a695a00e7b7e231a91bb9dcf85a6e3d86ef96492f09cf899cbed208dbc9c
8.649 10.000000000 (-166.66666666666669) 0x682Af04763857057C1dC962711d5Cc06085CE06d/17007 90000 0x4f461978f4c143a3bc94721166878d96827e84525baa7c450010820f5465a64d
9.567 3.000000000 (-107.6923076923077) 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/221838 104802 0x7894f6c2a6e30fed1028587b0658c32a792ae971f8b424d3e205654846b2da4e
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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.