× 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 #215 - 2018-08-10 19:30:45 to 19:30:55; Start Time 1533929445.6992078

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 30.700356931 () 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x5a7c8b4766d30f0bc5127795ce85fa77b63c6bd451c9759d9854b7f74ddb2f3d
1.936 56.932090443 (59.86762734138312) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 186517 0x09188d1755fcdfd5439c23b780872eba34dc7715733d5ba7bf500e74026a4ad9
2.240 62.625299489 (9.523809526517926) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x0baeaa3ac3f7f987814fd9c0208bb90569f88b44bcb24a76770cce56e398136c
2.463 64.333262200 (2.6905829560102554) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x86d90ae897aac3edf399e7926e06b7af9dd4d2115d4a1c651f4763461355ff3e
2.676 75.928165606 (16.533274453811032) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0xb6097d84ba1b2882d1ef3e11a6610697d139dbf8c25b1b8426381846562a3095
2.785 75.776612382 (-0.19980019879398658) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0xc38f390c87d80fa49948047f9b969242250b1de5d7ad5354eee8e2b4a10a6dcd
3.169 85.798827134 (12.405616573931772) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x6d099ccff6bf7804d315e891c03e2d7da1ff821c8f915bc60ab100666046b605
3.474 96.952674661 (12.206572769521465) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x28f1bac26a14d44236c3338c7a51af9f94e63f40917fc0c72e26280b1dc53c3a
3.777 91.689700984 (-5.579842449507973) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x7cd0d74844fbc382d7720d7b95a49641f52e6c54355cb28a8bc904cf52fc7a8b
4.120 109.556522366 (17.75618054797151) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x30b6dc2f75e1a49fa13d7346cd4462371c11f7dc54e2c0fb51c86a9457ae22a9
4.370 123.798870273 (12.206572769486295) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0xfae330548ad00891d2e32aaf90e31b325dfe99de4011bf4b2dae1894a455898b
4.515 110.944538192 (-10.951815145784225) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x2ad2e5ccd0d05675e83105a68f437902ebaa4714d18758da7e66e6129760e57b
4.603 139.892723408 (23.08124800227049) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0xb5cb8ac86f14ddfaf5b2971b8abad814fe543d695ff7413d001de5c69c72ba40
4.864 158.078777451 (12.206572769927842) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x52f90b2909fbb5fd4cb8482e517210b44bd33ccbec4cfc8f23848704dce2350f
5.112 134.242891214 (-16.307984519831045) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x29ac49264c7bbd678f2e63ea0784fd49c0098f7c8240bf752b5eae4cd0f33967
5.133 178.629018519 (28.37335403033045) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x5f4b963f49b1315febff5e6e8c622646bb480fd3f3757ae17b9b021056f0a1df
5.172 162.433898370 (-9.496851957242102) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x6405bf1791d4a5f090939eb304e8e32198217cdb0d124e0b26648e5a847bb8a5
5.257 424.387851007 (89.27888337986917) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x900b659247459a284df781957b864abbc56bf3334b088c67584dce1f8da8fa24
5.493 423.540769469 (-0.19980019957917577) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0xa67f32a545e4fa6e7220553cde0b76ba20519d7521490b0292ba4322c6830563
5.648 202.374370869 (-70.66977113880584) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x18b66179730616469710d93caa4d23842d2c331102c6fb0ff64ff0ffdf4b8225
5.928 232.730526500 (13.953488372370956) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0xedcd21dd5338effce04ef6fe0c56fbb67bc6167593bd13d58f31d9e9d8a44ca4
5.936 196.545017029 (-16.858873055532204) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x4b978cd82a687e4b53e5e8f21bffd1b26c30be4a11f4efee382eeb1cdbaf08dc
6.682 237.819470606 (19.004524887257016) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0xe0d23a0d62dc51b7c1c213eafda97dd677979957ec831ac98f00099302c65d7d
6.822 262.985494945 (10.05022955845161) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x055fd09aefa487435496e1294582da18a4451a945c6fd2c88a6bee6bf2213c41
7.167 297.173609287 (12.206572769668089) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x8e6203a781fdd6643a5a3e40bd8e8c6b22d545c20f71856da0f018f9002ed763
7.392 289.284044441 (-2.6905829588368517) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x85f94fe75f3c2618d07dc3e539c8b06695f2ddd89be3709de06bc3d928af18fc
7.544 620.106040581 (72.75689532770674) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x222e5c8730608b5402c739d4e299271c8ad35075558f687b0d15aa3e606307ad
7.599 350.033693775 (-55.67699935211496) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x80f6984ea028bb3933e55bba26f2b5bf17ad51a9c37efc2d9e6f04cbdabbf574
7.635 513.509299720 (37.861602068790695) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x969dc4c9c8e6922bfd80f19ae15f36801a724a0e750df95ce214511716b48c0f
7.647 350.733761162 (-37.66892577462642) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x72c6ace466f7fd3399e0cbba734a6fc43d6a7a159793247c438fffd8ae951190
7.832 512.484331058 (37.47617696010389) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0x9753831f9acfec907b927d2d59e425dd8d9db8bfd02a2df53d3d52d8880667ae
8.050 621.346252662 (19.20250223747422) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0xe3b0b9bb3adc4125e50d05e79ee796d4e519c49822119ae14b7e33cea9f2eb14
8.928 702.121265508 (12.206572769944538) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/598 216911 0x2ecefb4c1ac95542ff3e93b0ecdd6afd0635718a4508d3d50f5ee233ce810cce 6124068 6124068 / 0
9.378 682.116644640 (-2.8903443145638374) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11919 362815 0xd005346de7676951efd6b2e60b8407a6f601e2e7c914bf1672e4bbfa4e8ec610
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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.