× 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 #1597 - 2018-11-26 13:25:02 to 13:25:14; Start Time 1543238702.429304

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 47.603626882 () 0x66b46b0330c628f6E4AEA5E9F2D2E1eCdfE57884/360 300000 0x231588f4ce58e78288861f703d1bc579da2f8e0cebf77643cc67d516e1b9fc7a
1.134 1378.607511397 (186.64892578543652) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/32506 22000 0x63d7e04726b63f3c42fe8e40308bfe7bacf3214357b99937f51b4fa4b62e02c3
3.951 26.000000000 (-192.59579639464098) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/10737 374681 0x79746a476031662e7f227980978a6d6d83bd38816f611a3b3ac10d0f6db953ff
4.189 29.899999999 (13.953488368764821) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/21572 22000 0x97b7546662f64c1b8878a3ef1c740c314df12c9718e6257c9ad8272e1021671c
4.358 26.000000000 (-13.953488368764821) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/19047 375001 0xa333881dbfce4393833e188b67259ead678eb731a258542eb9c7c4d5b307888a
4.403 29.899999999 (13.953488368764821) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/10737 22000 0x04caf6e6dbdb8279f3b0688a775d713b57da0b00203386f07b1eebf17d024b5e
4.457 29.899999999 (0.0) 0xC9D81352fBdb0294b091e51d774A0652ef776D99/19047 22000 0x3dec9fe57698b623f822de8503d5cd03e213543240d813d6effa53c7cb0ce0dd
4.553 26.000000000 (-13.953488368764821) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/21572 375001 0xdbba1d3e7485c8802d59e646758ee108d1ce74e59fed0c38bf18ed77f3c0f5c9
4.566 26.000000000 (0.0) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/8898 375001 0x496fb61b3f2eb60952ad8a9907c3b4cefea4ff61a6767831890cbc4c3e65e9e6
4.674 29.899999999 (13.953488368764821) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/8898 22000 0x5bcf167f4e81191e6864de3a274be319d43e1a25eefb19cd9ddc997649772403
12.356 34.384999998 (13.953488369633046) 0xA045E11fB1551D7196B5B0526431688EfD49CFEA/8898 22000 0x93ec4340d1a13707ab7857d8445226baea53310f7c30ecd919d006f09bd5db5b
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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.