× 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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Global Market Overview

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 #520 - 2018-09-17 09:02:26 to 09:02:51; Start Time 1537174946.5433729

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 6.500000001 () 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5615 172720 0x35289c1b568b4ad4633d45f18ea92927980a9806bc76287532bcc1f3ae934aaf
0.145 6.500000000 (-1.5384615383431954e-08) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5616 635134 0xe1b829d807778d4b2a8c525c53460915aaa260d76ee74b423ff63dbdc86b1332
0.663 6.500000001 (1.5384615383431954e-08) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19271 478024 0x3b45ea499e3723e23aed265e57bd53b12488ccd8f8d6d85aa8afcd0121706c39 6347455 6347455 / 115
0.856 134.555887790 (181.56758969003567) 0x41880a6C0BF00b0C159a8154d66B676a995D2383/17868 800000 0x027b6754a38b8d23c2ef25cdf0506120fe1de0dffbfbce793dd31337ad6efc49
1.037 134.555887791 (7.431856133690515e-10) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5615 172720 0xc773984183f9829453b9e632ba008f13af8aa2c6ad283bea1b640734e5c1e9a8
25.376 7.474999999 (-178.94824114582127) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5616 22000 0xbdad5d0f91cbb9de9fcf954419a6d3078894c41c95be2068db45da4ee3854a39
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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.