× 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 #787 - 2018-10-06 02:39:25 to 02:39:27; Start Time 1538793565.0471525

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 151.620802559 () 0x9CC7D6FCE44eff82fe561c9587C65346AE6130a1/188 200000 0x4f3c2e698265571ccd1ee3330214caaa15a7d28f265fa773f17e9a1d351cfb5c
0.271 73.119600000 (-69.8594482034813) 0x9CC7D6FCE44eff82fe561c9587C65346AE6130a1/189 200000 0x19ea1be7eb409c54bf07f5f6b65e5acf2c491a37e5a24c243b502a39d53e2fa4
0.297 46.180800000 (-45.16129032258064) 0x9CC7D6FCE44eff82fe561c9587C65346AE6130a1/188 200000 0xbd6d8cb9f7ec072853cbe2d3405b97c4a6abe620f2396133a4760e8bfdeb5080
0.376 92.361600000 (66.66666666666666) 0x9CC7D6FCE44eff82fe561c9587C65346AE6130a1/189 200000 0x5f80d0ea8c5b9518a2e22e5ecea3a61aa67f692b3a82914133ca302b5f1bddb7
0.426 159.600844799 (53.37243401701337) 0x9CC7D6FCE44eff82fe561c9587C65346AE6130a1/189 200000 0x08b8c313d30dfff32156d135e7e8263167253bc485d44652a23380c7a91a7ca9
0.505 44.333568000 (-113.04347826044317) 0x9CC7D6FCE44eff82fe561c9587C65346AE6130a1/188 200000 0xa03c47af662960dd89b6dec232f0b96b79989cbe9b6fb4f64f16ad6577266f24
0.609 55.416960000 (22.22222222222222) 0x9CC7D6FCE44eff82fe561c9587C65346AE6130a1/188 200000 0x047b090c27e9ec22659f56f6a2802f467a0d9b499b1f8d014cd2f6c6d01e66cf
0.827 126.350668800 (78.04878048780488) 0x9CC7D6FCE44eff82fe561c9587C65346AE6130a1/188 200000 0x3dfcf419b43de8da130bf08eb9294e1a2292834b122b15112a06e7fbe0b9403a
2.400 133.000704000 (5.128205128205128) 0x9CC7D6FCE44eff82fe561c9587C65346AE6130a1/189 200000 0xe5e3e7f146b38d9e6d2ab98da81f850055527221dfa61b88d6ea6b79abcd4ed2
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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.