× 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 #1047 - 2018-10-17 07:35:23 to 07:36:38; Start Time 1539761723.6698923

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 7.000000000 () 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/22664 700000 0x0425ec0075dbf45773eb6be5e4f456ad1dab5e17d04393415ae65a21806fe055
64.108 134.000000000 (180.1418439716312) 0xa8660c8ffD6D578F657B72c0c811284aef0B735e/52293 121000 0x3f305469131281235cc150fe09bd156f82bea13f776d6a602a35a9b8795c66fd
66.868 10.576355000 (-170.7383548298752) 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/182457 98352 0x94708c9ed00ec8579d62b82593cf8f8457263b9095e6d6f38379416f65930c76
67.641 10.576354999 (-9.455053277308442e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/22663 22000 0x4317fc288c2191136f8fbd9e4247aa95011aec3f2969780677f90a8d5082255a
67.818 8.049999999 (-27.126670787400613) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/22664 22000 0xef1ba332d88a18dc99cc2da91cb7554818a4ce2d5f24eddf268910788fa5f846
70.707 0.000000000 (-200.0) 0xB7605ddc0327406A7aC225B9dE87865E22aC5927/9534 60000 0x0a408b669f917416df29fdb12b379d12818a26a6d72cbdc82e315f0cabc772fc
70.851 0.000000000 (0.0) 0xB7605ddc0327406A7aC225B9dE87865E22aC5927/9535 60000 0xe988af2e3e316ed8cbc57d1ac897917fb72e29e79d742a492eca87101b6413cf
72.612 12.162808248 (200.0) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/22663 22000 0x33ef3c90c1aa6192d1b43c88d24ce602b27d2b950050a6d429e54bc34b7bc4cb
72.697 9.257499998 (-27.126670789553494) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/22664 22000 0x04e350eac8980acd6f88839d7ea5e8516c1a1881d6d2ed3885a42ec6613c17e9
74.016 0.000000000 (-200.0) 0x00a329c0648769A73afAc7F9381E08FB43dBEA72/7608 60000 0x66600cb2564364531a46ee51bf19a30ff038d38021e9650b584135d2077a51c4
74.602 7.000000001 (200.0) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/7631 274947 0x1f64cccc5bce0cc5e3088609c20fc8b55953a3bc783de3edc10e9cd1ff7259c7
74.669 7.000000000 (-1.4285714284693878e-08) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/7632 582262 0x921b93f834511daa8ccb434c52101299c3cbff5ea1e389b8a9b552b061b2fdf5 6530645 6530645 / 118
74.669 7.000000000 (-1.4285714284693878e-08) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/7632 582262 0x921b93f834511daa8ccb434c52101299c3cbff5ea1e389b8a9b552b061b2fdf5 6530645 6530645 / 118
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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.