× 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.
*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 #38 - 2018-07-05 04:53:15 to 04:53:22; Start Time 1530766395.6721025

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 61.000000000 () 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/402 250000 0xed57736aeedc88b097cb0ad4b5e0317d634f9e4a68d507352cf398969e3a6df9
0.281 61.000000001 (1.6393442622816448e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11383 339129 0xbb801e22d90a2dec267ab35d0450f5ff958f17b16ffa18d728066cc85e0ed97e
2.308 36.000000000 (-51.546391754107766) 0xf2F7D4B9E10c3d871dA5F8002350A34981BFcF33/328 270544 0x2639107abc5241ab2ce382eb1ff25922da582770d2c82ef9dd433b332d5f53ba
2.904 61.610000000 (52.474131748796225) 0xf2F7D4B9E10c3d871dA5F8002350A34981BFcF33/328 270544 0x321ed6b3c16fe37c3276da72810859c0be09f106d439f1d80373ec171870902c
3.134 73.810000003 (18.01801802204952) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11383 339129 0xda9c74d2b944b1879aa1822e672a0052ea10323159fc8a43fd87805e605cbe6d
3.318 77.012500000 (4.2467138483134805) 0xf2F7D4B9E10c3d871dA5F8002350A34981BFcF33/328 270544 0x34a40aa9df4b480baca7f4cdb7a993b91271bae2c29240c580b3cff696cef208
3.556 89.310100005 (14.787647625314069) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11383 339129 0xc641d105ba170b87cfba2c1936a61ce888333e442c35196d537f0bc11c12c9c5
4.708 77.012500001 (-14.787647624022677) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/402 250000 0x7434a7a70e882990b0360f3082647967a789d15fa529ee92f52adedacabe6e37
4.812 89.310100006 (14.78764762513625) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/402 250000 0xbb9ed2b61864620407aae65bc626c9ed244eeb3978c5608bbee3119b4e0b6c53
5.098 108.065221007 (19.004524886639405) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11383 339129 0xeb6a8272aa539dc4fced78f9f15b7963b459d9d9d2ff401bb172974c91ebe4b7
5.561 96.265625000 (-11.549500467096161) 0xf2F7D4B9E10c3d871dA5F8002350A34981BFcF33/328 270544 0xb8e75a166b0a407ef8b86171e038a548d07aaed868b601dbe6f4df4c7c6d3e06
5.873 108.065221008 (11.54950046801844) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/402 250000 0xd32d0e2959ed2f02ea2b51de4902627fb748dc10cf224673d6d285797d66cf7a
6.058 130.758917419 (19.004524886362482) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11383 339129 0xd81e8e6453b1f94c0fe9a10d5d97af9f164fc9a74dba5b1a8d5d56f826a3affb
6.850 130.758917420 (7.647661970095744e-10) 0xAf4b59e535df18942241f06A4Eb9bCb32F45f43C/402 250000 0xed1bcba3fceaff21973499e29644048bf633ce93e222c9e2f49b2967a92ffc89
6.914 120.332031250 (-8.305266458412795) 0xf2F7D4B9E10c3d871dA5F8002350A34981BFcF33/328 270544 0xfc70047c525c3422f4d41fe888fea1a1c91fc550df978cef44febbaee70109bb
7.136 158.218290078 (27.202452072125222) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11383 339129 0x89d058ba83eb665830d439f6621d38dd2a81f052c6dc2b44eaac471f7ac12403
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This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. .
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.