× 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.

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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 #907 - 2018-10-10 10:21:06 to 10:21:13; Start Time 1539166866.235933

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 4.052722203 () 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/13049 206367 0x80b38749d76fba46d4be19eb629810077ccd6843057b9b3f1e8a5670853c8a25
0.429 20.000000000 (132.60268557054187) 0x7E51e8E4d5FE0260B67200bc21c3E9fd4D124288/51 56986 0xa98cb19dfd286afc339d34ca0668211916b92994539a1f8755c2d205ad48550e
0.938 50.000000000 (85.71428571428571) 0x274F3c32C90517975e29Dfc209a23f315c1e5Fc7/89248 58300 0xc1aa22225b760b26a226d4cafb382aaa8e0384a034844c1a02b0fec7cdeb8d69
2.780 10.208206657 (-132.18062969285825) 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/13048 206367 0x864b7b87a2c9fc6e4e73f5758e9dae5863f18d1e54a66190a899378a81ff01a2
4.250 3417.142857142 (198.80861849667832) 0x8A4a0aE920291F260b2fc602D68e72C1965a3Fc2/4707 21000 0x6cbcc669ceeccca14629e89043d5e6e93fa313d23b85919457a68a64491f8527
4.362 3417.142857142 (0.0) 0x8A4a0aE920291F260b2fc602D68e72C1965a3Fc2/4706 21000 0x04eb74b558f9f3776c71e4e6fb1f92ad67dc353c254de493d2578284bdf1eaed
4.877 3417.142857142 (0.0) 0x8A4a0aE920291F260b2fc602D68e72C1965a3Fc2/4711 21000 0x5cedbe5b1966edacebdb98b6edf1895e6c5112e1a9e4cf582e965792be24a152
4.879 751.771428571 (-127.86885245903528) 0x8A4a0aE920291F260b2fc602D68e72C1965a3Fc2/4712 21000 0xb08a4d43eb18126afe591d5819225a862ca6713c0f1b09842afe57f949a5ba4b
6.613 28.303383923 (-185.4868361497224) 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/13048 206367 0x08830d832e9df434e56d94110aa07d758c2b5f3a48fd05222f005929fce2c879
6.701 28.303383923 (0.0) 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/13049 206367 0xf439ec3a5fd3ca02cd1c32b70c7c202396abcf580040e27fbf30da6040b27784
7.202 3417.142857142 (196.71411109705764) 0x8A4a0aE920291F260b2fc602D68e72C1965a3Fc2/4710 21000 0x0d3d297b2346ed3745fadfcb336ceb135b1ca6e552730284f2043ae1996b37ac
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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.