× 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 #1573 - 2018-11-26 05:35:56 to 05:36:03; Start Time 1543210556.6654544

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 10.000000000 () 0x682Af04763857057C1dC962711d5Cc06085CE06d/16882 90000 0xb1870649514a6a3a38345b4a5a8b842f7ab89543dcd43ed443a874f74667bcc1
0.032 12.430000000 (21.66740971912617) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/130 500000 0x494464d223f0218ea9be8ff19306e40e1ea2313249e46b00ff977ba681bc26a0
1.046 12.429999999 (-8.045052293163518e-09) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/296 500000 0xd3714894626cb613252e044757eff31f3ea014ac2102bf84ef21897cbb3e9310
2.179 39.070893398 (103.45798545138199) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/130 500000 0x21549ea4cfe8969c907568e02e7331b708038d29c2c67b7e8c03893b1bc1b450
2.220 39.070893398 (0.0) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/296 500000 0x1be4bb5b04f43b73801ccfa2cda3e4c8fe58ef928fa69754cde109ab799eecc2
4.879 44.150109539 (12.206572768283195) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/296 500000 0x8c66ff4c9adc3e31b612682d97a01032838eb77a59c0bf943843c09e34c855c2
5.792 120.000000000 (92.41527852039479) 0xFADD4dCdb7b092c7C0531ce903f5054aE4514100/2087 21000 0x429631d3bc42243c95859d28c74ccc55310af533f55a1623adb30ded088a5250
5.796 120.000000000 (0.0) 0xFADD4dCdb7b092c7C0531ce903f5054aE4514100/2088 21000 0xab6da71bddcad4d280707930dd402fb3724e7d729f520bdb5c89dd762d00d09b
5.901 44.150109539 (-92.41527852039479) 0xC81064916D8c164BDC747C06b47Bc8D3Bd133152/130 500000 0xe3bc533aea64eec850d5469838333a94643abbcb2bed042218e5cae5c7885cc6
6.810 5.000000000 (-159.30833076957794) 0xfe5d8128B077EeEC7FCfaB9c44cec07f726913e9/451 119977 0x862eccd5a52ac4e4e7e9a3956cf3c127234b33fa16692a4484dd63ba22bd7ae0
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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.