× 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 #1611 - 2018-11-26 19:45:16 to 19:45:25; Start Time 1543261516.5279713

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 40.000000000 () 0xfC624f8F58dB41BDb95aedee1dE3c1cF047105f1/21760 119881 0xcf4adedf479b3d4713ef9c7388a705a9a50e6ddb1b3fd479b0fd541e188da528
0.261 11.150000000 (-112.80547409579668) 0xEcC996953e976A305ee585A9C7BBbcc85D1C467b/7580 150000 0x44d10577387320292b9f3eed84cfb3894453eafd1f32538e8e1481b5aee77549
1.409 10.580000001 (-5.246203395984988) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/10809 22000 0x112355b5169390d171d7b911638850162807a8921dcf62fa9af479215bcf6c35
1.805 8.000000000 (-27.77179764113177) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/32641 695991 0xcc09aff0acef7a83a45a51bad0103bb9c234bb0e5b01cca1a37f52e76969f55a
3.268 9.200000000 (13.953488372093023) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/32641 22000 0xe1e44bc11ee609aa4088378929e14605c4fdf0975537b824e8ee03d4c5099a5a
5.979 11.000000000 (17.82178217821782) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/624 500000 0xae7d66f14d4757486e2f55d7287262d69495691576d01b3dff4d19abcdf22027
6.599 52.009688746 (130.16946936943373) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/624 500000 0x9025471a7687624d6ffd060a13fe50b72325e455be0c50103b02d4e259d7b9ae
6.947 58.770948282 (12.206572768291773) 0x2152d20E8E66E65aaF336B7b53E04433F0967939/624 42000 0x3cec55201a4d60c7183c7cde8210a8302baec3483f68dba02887f3cfbb0dc80b
8.498 125.000000000 (72.07782550740312) 0x62677A0b1d3fA1e2EA0223a8a55d9A5A8CA26426/1096 150000 0x19b7b1b3dd6389a0c8097ca863df3f1cb32d747553af4f8adca0e89d540a467d
9.171 8.000000000 (-175.93984962406014) 0xEca0f4Bd861713aF4f248CED18C15AF76440b00a/1812 506238 0x7d90dd4ba78a4b9152288b57151172337c8f6c1491b4211996e2eaf2514fd481
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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.