× 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 #211 - 2018-08-10 17:02:15 to 17:02:18; Start Time 1533920535.834266

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 326.000000000 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4058 199148 0xf0f7be43625f934eb57184c7b9d83d72cfa8ecf08b96ec1a5cb4ee66c7f843c0
0.411 1185.642204936 (113.73620055446858) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4406 240850 0xa4eca8c00cd866b9051d2f97f25ab00fbde3baec61f094046b9dba4bb521dc07
0.686 1188.013489345 (0.19980019972680005) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4058 234227 0x389864f4e6751bbb0d80df344a4bbb6849d17f960889b2b6e05df31cd79f7872
0.930 1342.455242959 (12.20657276988997) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4058 234227 0xd30554c2837aaaf1aa5cb89bffb9c8808fbb7c26c372528cc96c8b97f622968c
1.253 2021.400287566 (40.367075128285094) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4058 234227 0x1935011ca37840e7570d3335da27197670114425d74d1df6cf09213ed52d8100
1.265 3429.521445971 (51.66543301260342) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4406 240720 0xe5c9c32df533799084415228820b15adb5681abc90d23016c4331d239b754fd3
1.336 2017.365556454 (-51.85185185183009) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4406 240720 0x3150c683bf977d18c99c42424565cc7520d8be23c9e86b140553f7052ed091e3
1.343 3426.505972264 (51.769789510144605) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4406 240850 0xeffbda1a43b5ce89659e919b71d55edb511ae89b09d2c89890772ca725b5081f
1.443 3433.358984208 (0.1998001997848213) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4058 234227 0x291ec4de58f153cfdd1ab197435b6d607ce43ff8c3026e8dcee9090fd56f3fc8
2.091 5830.186458150 (51.74751910823242) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4406 240720 0x6881181b25057290fb0832a8244de361dfc45ac50ca730b0b2d6dc198a624196
2.317 5841.846831066 (0.19980019979506444) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4058 234227 0xd7a56fbf90762bf9f2480e60a0a6ed228379b6399fe7720e7583540681eb8a58
2.556 9911.316978855 (51.66543301258807) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4406 240720 0xa48751b71bb789ff9267dc034a03ffac76a1d650bfb3c077dee77ef540955df8 6123432 6123432 / 0
3.137 5825.060152848 (-51.933895480614765) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4406 240850 0xb41fca37b7b7b7def24cff16cf6ea0f0b3b661a782d8573fe60d239819e878f3
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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.