× 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 #290 - 2018-08-22 05:17:58 to 05:18:07; Start Time 1534915078.9809196

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 25.001000000 () 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 186727 0x6c01b618b8569733acda8d8cbca16ec4cb8fa2d418eff85d1979d8f41c45401e
0.157 53.518842277 (72.63856230478811) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 217121 0x8e13da94be090cb512c34245edcb6a240c724a04fa50cfaa626e76c277d0d875
0.494 60.476291773 (12.206572769936578) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 217121 0x321caa248374c21255f17946824df346c2cfe0fe73da6cc120a8e64f97d5e6ca
0.612 53.518842278 (-12.206572768075038) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12130 332815 0x6824febbe8333ffc3123e81d9bdc10fd9bef955244d21e7320fbf6a3f97c5803
0.847 68.338209703 (24.322543807002063) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 217121 0x473886e4347a0d67bfa599520d3c877f2db6e90793353ac28c1d9b5bd1514b5f
1.392 66.523920952 (-2.6905829563693544) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12130 332815 0xe7e0dccec42e0e90677830b487f72d40a93445f4ee19e720fac854399d188ca9
2.241 80.654932241 (19.20250223783112) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 217121 0xd96fc3019d24ee9031ae1e2cd1d3e9a9135cdd0463d56ffef8a5064a5498221b
2.451 80.493944353 (-0.19980019892486675) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12130 332815 0x0f0424afae73c97f5c5b89b4a82f8eaf7986d639d5b8e0bbd6a6347fe2a1cbc9
2.683 97.592468013 (19.20250223791293) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 217121 0x8eeb3819bba291ce20f56b474bfb09e6c5adbbb9a1bf612dc239979c95745296
2.965 97.397672668 (-0.19980019945591126) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12130 332815 0xf1d05ad95a0d11a9315bafc995f7dac2d2e4c9ee76f278452e6dce24d12a1493
3.051 118.086886296 (19.202502237254457) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 217121 0x00cab986c4dd6cb5b0ce97491ebbf21daba44b0a247ed9a181326ff7ed9755a3 6191534 6191534 / 0
3.241 117.851183929 (-0.1998001990736169) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12130 332815 0x37d3b33cf72697384f8968f974d22bde9bf9b275a3a1c786e30c894e1397d55a
4.453 189.800510233 (46.773235882857634) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12130 332815 0x0cd4616c960dfdd4108fa52b5609ab91d84164adbc7acd021a9101448a01f3f0
4.581 142.599932555 (-28.39982840101318) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12130 332815 0xdedc215d427f7254bd0e1c79a47c62f6d53250d040dfa321fbc719fa83b15ebc
4.642 142.885132420 (0.19980019972321494) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 217121 0x5a84701e296839c798ecdf102d008e916027b48854628b8cb46f48b8e57bbcac
5.292 172.891010229 (19.00452488733637) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 217121 0x7245e3010e6396b5b2b3416cd802397611fb7cf6010c7c62be7983e151e8d537
5.552 172.545918393 (-0.19980019934557858) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12130 332815 0x708dbb4ead43daa8e2a89ba4a6423c6a1b38f93d95049fcf5a8f4b437ccc84d3
6.858 220.764530960 (24.519365120514923) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 217121 0x67fe4357aaf29ece720cb894b8abe434882a30b3b4bb59b84768836d8f1f98c7
7.247 195.366841558 (-12.206572769709357) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/614 217121 0x1448eef66fbfaa2ef97a26620d81d3a5d1a7fa3d194cd2a889c39225430a3723
8.563 208.780561257 (6.638033353954365) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12130 332815 0x72bc78a49163b2a8ccc6d4621e396ff7467c0845409c46986da4bbe9b8f9448f
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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.