× 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 #387 - 2018-09-04 05:09:52 to 05:09:56; Start Time 1536037792.4628184

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 809.599201035 () 0xf666666666E8025c503209ac580a5aA4b39A090c/373 214084 0x67ea39dd33cd97438f45a4df44f0c67d33a12393610dea23785a1999d17c51cd
0.004 333.000000000 (-83.42368883214384) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4183 229212 0x5a1db530db0a1d2a79940be5c8de5b5fd918082921455131f8da085cf15633d2
0.138 69.705990210 (-130.76240045632272) 0x0000bAA8F700aF2476492b19e378d61b90454982/197 229084 0xc504c10026f12fb08d2a4c0f116b62f893c53a153a52a6ddb85a35844e977f01
1.176 841.983169076 (169.4167734693298) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4595 255816 0x14c9be953ce97689abb6ac5358f1a823b33c8c29b9675a0513f295ae8f01fcde
1.476 914.847097169 (8.294930875563447) 0xf666666666E8025c503209ac580a5aA4b39A090c/373 249379 0x24cd39f735dabeeea689b604ea8fb4a1e59e9eb0586ab0919b5256a95fa9602e
1.612 841.983169076 (-8.294930875563447) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4595 255453 0xda340dd15e0ff424e1ccc015c820aef829a6ef86e2024719b28f2102377a0cfd
1.715 845.354469684 (0.39960000068243845) 0x0000bAA8F700aF2476492b19e378d61b90454982/197 269540 0xbc8a15938290349a4f0992a37bcbeab55d450a4280d77c557a3bedc57782c313 6268489 6268489 / 4
1.718 847.045178623 (0.1998001997567547) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4183 269520 0x0f814af30ec2f74b477c8816be4c5230d1089a14494510f47702ae7300356df9
1.793 953.545938978 (11.829533014346449) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4595 255731 0x0de67b542d8d51f99e9e06d6ad3cc899b030cbc54ab71cb9200c141d1d64ccc7
1.870 4461.113919020 (129.55820206733642) 0xf666666666E8025c503209ac580a5aA4b39A090c/373 249379 0xdade1fe84281ae6813439af006ba6169dfe7307342ec1107f6c9a2f7fed6a352
2.057 7553.648852330 (51.47891793060375) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4595 255547 0xa087ad772bd5e97d61cab30cf8f28d8c30819b5a1c1d6f6805bef1ae946524c5 6268489 6268489 / 0
2.097 4639.558475780 (-47.79858651024343) 0x0000F7F39325076881E5fC566E99595542532aE2/15856 240656 0x844082a7012503d71d5e1338d96beac10be6b6b55fa14e2289d2c2fbb105b39d 6268489 6268489 / 1
2.171 4443.322854312 (-4.3209993467130845) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4595 255547 0x84616f6ef0f0da34d35b368ba63748923ad5b1a46cac582357fcebcea9666a87
2.174 1338.608387059 (-107.39368344742945) 0x0000F7F39325076881E5fC566E99595542532aE2/15856 240656 0xad24e33acd6a041401d99ba46aa4913e71f1a27d3241b3e9aef09dc3f9964425
2.204 953.545938978 (-33.598300402988166) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4595 255453 0x8fa2fad128eb9e1707dfbc44f6f0005f3d9ca0f2a1ec6f18dc0813e6d117465e
2.350 787.416698270 (-19.08475657704019) 0x0000F7F39325076881E5fC566E99595542532aE2/15856 240656 0x6e6e4bf0e9367f2f698c20ac7476a4aca4312efd3797d7e3819f3e984171ec38
2.357 953.545938978 (19.08475657704019) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4595 255816 0x1a35e6300a6b982b7fa5f262b4a05f9b8027d6b82e3695fac6a4a3a587d49d54
2.379 4452.209500020 (129.44216957363892) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4183 269520 0x3a118d8808f0a6c7ccc1f47899f8f68dfbe47f5def8856ec70efcd449234391c
2.711 5030.996735022 (12.20657276994117) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4183 269520 0xa202c5547e0f500e70454d20f7c9ffb22a749dced5a2b93d6426b53b7bcd2219
2.995 7583.893662334 (40.474341780203986) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4183 269520 0x8677743eac81c3cffbfa77ac6835fbc9fff1dcce72e86fd494ee81b9fcc7ec16
3.824 841.983169076 (-160.02869797776992) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4595 255731 0xbf332abfcdc69913048a40ccdb3e3ae58c41752d3717791d8b2ab220106ff9a8
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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.