× 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 #462 - 2018-09-12 15:37:42 to 15:37:46; Start Time 1536766662.3585205

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 943.710903159 () 0xccD7BDff63017081B5cF72993d5D84cf2a266330/635 199148 0xfe88ce52b0c8bb1a71ea750b9af4d40335148451be62d7245f8c0c7461f293c9
0.354 981.459339285 (3.9215686274143144) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240980 0x0900a51a4290a0adc5e632be3c8c19d457cb5c2178d0834d1abd107d6580a55f
0.364 981.459339285 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240761 0x5e2819205b05b2860899487f0cd843f71335f8086f4cb19bd29148928b49d37c
0.543 1066.393320569 (8.294930875549934) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/635 234528 0x50d11d73f2ea2c8e56bc57409b8ba875e8891f1e21b0c5c5295cf5a7fee8192d
0.573 981.459339285 (-8.294930875549934) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240896 0xb6a951bcafa92ce88e52fdbb7688e9a5a92718d5123d04f07e64b2aa8ed90d51
0.696 1668.480876784 (51.851851851823895) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240761 0xa9766a5aa6aef3fc2d7014aaa135d1c0e6a73b215de92ebe3807b2b6a3d7f056
0.774 1671.817838537 (0.19980019976622485) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/635 234528 0x4b21459d6a0a3c2380a6b3c92066865ed23a0b5285b89ce23c65b069320b6cae
1.013 1668.480876784 (-0.19980019976622485) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240980 0xeffd1ff543b6d117b4565b7f7f4f0a88d2e2be950ff92314ab7b128fdf5b74c2
1.021 2836.417490532 (51.85185185182555) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240761 0x5182db38ef0a4bcaef6c06831844965d8fee10a34ed0dadbc7deaa15aceb5178
1.045 2842.090325513 (0.19980019979794794) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/635 234528 0xb4726c3e12e44b682e003f5adb014e273353270de97a060c181c3e4aa2db5d35
1.114 2836.417490532 (-0.19980019979794794) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240896 0xa885c422a43efaf1623e4d803d6313b129fc7b5661f8967dbb72a84844d367ef
1.243 2836.417490532 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240980 0x05175f6ceee9acb08ab2681d50a53e97921a8a17970bcb862a24907ff9dad11b
1.311 4821.909733904 (51.85185185184411) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240761 0xf08497824a38730c3f6322f53d4a2e6345d7d5464fc879989b929ec4a462466c 6318872 6318872 / 0
1.375 4821.909733904 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240980 0x0655d4c78886e2168f46472fd600c73692ae0e114a581296dcfb5a0485b2eee1
1.634 1668.480876784 (-97.17223650382816) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240896 0xb50b9ca6336f5c453c8ad5cd1b03f18a0523a9120d8462c8780be3264d199835
3.900 2955.773938533 (55.675697519309566) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4651 240750 0xcac72525c59d068212e340dd4297267183ac0c70a405c32f345490e937bd8cb7
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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.