× 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 #1579 - 2018-11-26 08:41:03 to 08:41:05; Start Time 1543221663.357949

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 7.265750125 () 0xd1BdA2FDc2DefbF44827A9e1E6dC95D0BEd9504f/6074 160000 0x2b68f2985743f134f21655aa95733ce85bb3d55847f4600715d1e296190fb3bd
0.429 110.000000000 (175.21612195460298) 0x77521132FAD812cedB7dd5b4f34835E71821B4EB/526 150000 0xdf0d7531ae83f748e735c9cc67faa389641d59b71deb27f5a85c1ceb44948006
1.160 12.429999999 (-159.3890386372571) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/368 500000 0xe5f2888b23d0fd2dcc48c43c0929b50b6abe482f4b93e37f03d5560297530c5b
1.225 11.000000000 (-12.206572761937966) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/368 500000 0xf555c01852069a8c13645f840912a5a1cd47772ba8af4c609a4ff6edab2c2b48
1.418 38.139974464 (110.45986392965173) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/368 500000 0x816860ce5e0f77ab3f289707556cfd1feeb0e73b89bf52b54d504fad1388c196
1.470 110.100000000 (97.08585797614995) 0xEcC996953e976A305ee585A9C7BBbcc85D1C467b/6455 150000 0x0d308d0be0208461c3761e02549ff93cdc1377c6c9e1a7084858fa1ff42c03ef
1.504 14.045899998 (-154.74389408518113) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/368 500000 0x0cea81ff5221f2e6ef63e2e89e7ac348cfcfac48e91eb4baaae7e7adcd101354
2.448 48.700933392 (110.4598639380039) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/368 42000 0xbf62724305043ef3ada8c647b9875aa9973564593989860f7ddcfbbea16e0302
2.459 43.098171144 (-12.206572768480148) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/368 500000 0xea6914d330a92e1f2f91b67d6de357e9b32e1475fb0ae0cd61104327103d0b1f
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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.