× 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 #1551 - 2018-11-25 04:10:59 to 04:11:04; Start Time 1543119059.2046707

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 9.000000008 () 0xb314371A82BD900fd70B83902665B2af93dc3294/15 2000000 0x7cf303f289d3b37fbc6b4b38f75cd60066c48b40f7a19ca9178e1cd613337deb
0.588 631.500000000 (194.3793910957767) 0xb1b68a82dfA780E7490E2DfFF0886aFd839fe705/22 750000 0xf8ba77bde09fe7c2ae32c016955b578225788d49f13c35024e2ffcad3ee95e8e
0.728 170.100000004 (-115.11976047746946) 0x36F94220C57E34b6b3a294523De1977602Aa625c/757 2000000 0x268f8f42872d0af60d1b70782d0049c4a5e2032582683ad9e7165ab7c7004412
0.798 21.000300003 (-156.04339710145769) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/383 2000000 0x987430f28e5ebd580aec48a807fa951bf79f68f300eb57afe61424913083b852
1.601 631.500300000 (187.12626470970085) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/383 2000000 0x2b4438db2e8e6fafb934e40f13261a769f34dbca5fcf759ee13b5879a91244d9
1.870 9.000000000 (-194.37939373330505) 0x00d1Ce825DacBCb6789e2D5fB1873A7178312abC/2344 1600000 0x2ddbba1dc3858aa2145aa2247f0dbd564ef62a4a352be5ee6c700156cc9a53ae
2.072 631.500300008 (194.37939373337525) 0xb314371A82BD900fd70B83902665B2af93dc3294/15 2000000 0x7755cf4fda250f20218321b26b7c6e4ed90d2412308b232c1d378609bfcd5599
2.482 695.444820527 (9.63785457731948) 0xe7d97A788E6a0a0B4F27bEBEfBD0F95623e98E2F/383 2000000 0xdd187caf6af9f2275a175aca6064311b660483965d42e197b468bd313e420632
5.415 641.250000000 (-8.108779909184262) 0x5e0337086931BaA32fF51f7Ce25840d9a3C572D0/29 750000 0x3df8bf139b153cd8997170d33578062aa3faa02dbc3146958962b8492203a27c
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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.