× 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 #487 - 2018-09-14 08:53:57 to 08:54:12; Start Time 1536915237.1437316

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 29.498516761 () 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0x537dd0b49a7ab67ef55aac00848644bc7c53d019c5ccf67167df8b026029ef66
0.243 29.498516762 (3.3900009552519277e-09) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19198 299026 0xe8212c56568f10ce3b576718d00a2154bd95e5046b4f93333df6077b825e2f53
0.498 35.693205282 (19.004524886822303) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0x00948df6e221162eb9636a27fef060001ed648cebbf86956ac5492a0f207f1b4
0.694 35.693205283 (2.801653681941222e-09) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19198 299026 0xc300d912276c3c706879d347060bfef391f9354619d77c446bf21bde42cace81
1.255 43.188778393 (19.0045248881857) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0x76ae66b79c093fb316995537de6477a645a2813ee2e3a77e518a4ab555d134df
1.389 43.188778394 (2.3154162659773264e-09) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19198 299026 0x655c72016185c84059373d06dd45d25f12575aa1bc059166656b4c0b07b2a9ae
1.716 52.258421857 (19.004524887370863) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0xe9a83b961d24c33f129148dbb74e42e81bbbb400ff855b460ec529f350e9c262
1.927 52.258421858 (1.9135671619147496e-09) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19198 299026 0x92e2d05fc4748417229de0e4b5b24613e66c7243a8b55bde75c369390f17902e
2.215 63.232690448 (19.004524886595735) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0x41b599b879ef6c7561b19b074a20ec62d3f11829d5158360f4e0e2f81c12811c
2.421 63.232690449 (1.5814604643692207e-09) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19198 299026 0x41567392b1d8f0a88c4823576a4aef68000cc263f6938471b5517d4b0f6471b2
2.688 76.511555443 (19.00452488650222) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0x5a972a9d6759e5f08ed2c0e060cb0e6fb6184dd0d1d35dc145bdd38c7092b265
2.900 76.511555444 (1.3069921192994835e-09) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19198 299026 0x7c972a79b195f5fdfbee3cd46694a6f51f0a36fd092af274d6529ba2e2456c0d
3.152 92.578982087 (19.00452488662093) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0x1d80c9280efe3475da301834450a0314d437b40723fbdb069c01142c283b5083
3.344 92.578982088 (1.0801587762704724e-09) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19198 299026 0xdd01526506d68bec8ac358e69e31e7c180ea45b7b2ce2bd192ee38ccbef9ab14
3.627 112.020568326 (19.004524886453204) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0xcee4a767a33dc2f64525ba79b5fa1f87d371c93e8fc402267398f6bb29280480
3.781 112.020568327 (8.926932035243356e-10) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19198 299026 0x6b4c323c4ff1e7ccb050493b5e2667813a3eac784ed50b76de3a0132b3e283ef
4.156 135.544887675 (19.00452488638799) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0x71062f2cc7ed7aaf00fba2b6eb2c8711540523ab6d5c6e09ed46b9b319a4b313 6329253 6329253 / 0
4.306 135.544887676 (7.377629781169178e-10) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19198 299026 0xe52becad3ff28cdd2956f5faa2722d4a25488ea4194da1ce4679ba473926fcf9
4.877 164.009314088 (19.004524886901997) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0x602d0d83248389eca123b6091b0f6ff70b77a59f408d5b80fc2a5c49f61a0361
5.765 155.876620827 (-5.084745762992685) 0xC533a4e3350deecaA0bf0fcba92D4a6138013b18/19198 22000 0x422f948e9a4013f26463f66d3246928da55431987f9a74517ac8e80aa9d49d90
6.131 5.750000000 (-185.76967093519917) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5408 604222 0xd34c812e4c8d39a93f4cc026f995eb032be779c32e28a4c1701e67ea6e652402
8.407 198.451270047 (188.73660286505262) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0xfd27ba9c79e24a8d7ea3a9a67f958896de3097a987320bea0d2535c1eb1077e0
9.672 240.126036758 (19.004524887344164) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12639 322581 0xb8d8b22fda3133eb908bf7d74b6e752ae60581e74d9fc5072b1224c449f6356f
15.795 6.612499999 (-189.28015042009864) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5408 22000 0xb28201dfa99f102427b848e41decda0f29284bec58b56373549b77a53bae00d0
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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.