× 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.

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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 #1570 - 2018-11-26 03:45:41 to 03:45:50; Start Time 1543203941.8802078

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 8.100000000 () 0xfF59364722A4622A8D33623548926375B1B07767/46769 600000 0xb8910b61eb7a484e92fa5351af3b8f15bcb2ed4a51fe7e70f07088e342fa4333
2.426 11.000000000 (30.36649214659686) 0x57bD0069505c4009Ebde6A87Cb92150751f0EbE8/672 500000 0xa1296580a1a735b6ab8d787d9a97ac92eb9bef74b9428897cb5ed5e61b2c834a
3.666 12.429999999 (12.206572761937966) 0x57bD0069505c4009Ebde6A87Cb92150751f0EbE8/672 500000 0x180dd3e7b4a8132c4c4fbdb70a3329860f12a73aaf4990fe04bd38e1284eee79
4.060 37.953903631 (101.317689948908) 0x57bD0069505c4009Ebde6A87Cb92150751f0EbE8/672 500000 0xcc03f2736c797d63b45baafe39b8bd4fe9f9316ea7fadbe87ab2c31f40b8d50d
4.447 42.887911103 (12.206572769883364) 0x57bD0069505c4009Ebde6A87Cb92150751f0EbE8/672 500000 0x6636e8dccb79b7041d6015074542f0fd496f0b913650714bd97fc5fd98b360fe
5.918 48.463339546 (12.206572769151318) 0x57bD0069505c4009Ebde6A87Cb92150751f0EbE8/672 500000 0x71ea94af97244e9fa1b9078dd60f3e22a8575a8ecfc06ed8911eea27824dec92
5.964 134.000000000 (93.75763993669068) 0xa8660c8ffD6D578F657B72c0c811284aef0B735e/56640 121000 0x2e9d88faba6dbdf2560278c0ebcb292fa39437eb399a313a3f5bce9c6504ec1e
7.039 54.763573686 (-83.95308985387864) 0x57bD0069505c4009Ebde6A87Cb92150751f0EbE8/672 42000 0x1e99a2a440574f10951a0abd2b3745ebece0affc0a9e43de4089cd227b1d9f7f
7.638 11.000000000 (-133.09366031401225) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/240 500000 0xa0e266ac01d2cb6f78ac15c8bb14c2e782df8637eeece80dc2584608bb96aa3e
7.683 50.516650377 (128.47464917164794) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/240 500000 0x061087d18bbe310875f229d154917f8e09237f4513bd6258270787d05e716a75
8.670 57.083814926 (12.2065727699356) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/240 42000 0x81d6ac5e61d1f6057fc6d6ef5a8d591624a5da9509343b75396bb05a2d72cead
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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.