× 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 #1342 - 2018-12-10 22:30:28 to 22:30:35; Start Time 1544481028.6583865

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 8.946507000 () 0x8bC3da587DeF887B5C822105729ee1D6aF05A5ca/235391 104802 0xcbc0e37f19c4ee6a3785a54a730976533da3e290c3c057e2377a44306f3f0581
2.999 405.735627256 (191.3702508394278) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226330 0x6b04c04df6573d68b24cc0061c845bb71dea963aef0441009797fe81dfffbce9
3.252 53.040000000 (-153.7551719412476) 0x0000F7F39325076881E5fC566E99595542532aE2/15993 225889 0xc62dc51fe7c870fe5732e63d5346ac4a0ac2fb51ff51dd5dfafc8cca73d31785
3.338 405.790285840 (153.76068089934608) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226308 0xb01857cb10341f263eac6b8acb66da4b2a184e0fcbc44c9ca1fab0051b3d639f
3.360 28.653827845 (-173.6179389317026) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/12775 241573 0x86e90fe03ad8f41d00b193777def20147116b18f1a3aabad974020621e96a06f 6863408 6863408 / 10
4.210 456.493154225 (176.37513668724367) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226330 0xc4a6fc6e8836e04b72f0adca0e9b6d2b5a9cc9b4e6dd6da5bf2947864886fced
4.237 456.554650598 (0.013470570253859043) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226308 0x178882a6f990a55caa1fef190fe20107623e89065243297d4f447735999aa681
4.254 426.904863099 (-6.712200624774524) 0x0000F7F39325076881E5fC566E99595542532aE2/15993 225889 0x10905780119aad7313c92fff948e86f1b6121d04e2e3d52cdc7f84bfe8170167 6863408 6863408 / 5
4.554 513.808072461 (18.47603154521674) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226264 0xd17b56737cf5604d03693151401ada93169ad9928a71cd2f8f4875f3032aba78
4.589 512.285835719 (-0.2967051514222547) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226014 0xaa3842521a903d61ca74c8cefee89ba546e15b45e2fd6ee33b58b2af2b884607
4.641 513.669637387 (0.26975862096834446) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226308 0x226e1f25386e4fd0b1d503680911c8e60aa09256e8172dc319f022caa2938fd6
4.941 614.743002864 (17.914256163333587) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226308 0x42b27312f9e9e8c698a471ab945d48c00b45f04f7488a34e209e19c205f828d3
4.965 614.743002864 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226014 0x85df30a0b7e523a28ecfd3e573f5042d69d2f8f6659e6f75d2207eff8f4dc524
5.348 737.691603438 (18.181818181979505) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226308 0xe793741921df4d8999cb71d5c530e15c4d1503e361fe570c169e466bef13ab7d
5.359 737.691603438 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226014 0x5d92a49e82db6a33838b7207fa616826ede98b90a1d4c58de0b2a06ac309b3da
5.750 885.229924126 (18.181818181862994) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226308 0x2e36f3fcfbba946826bb8ac0f88309432c4158db3f4a12dfd7b9c4fb9391e75e
5.763 737.691603438 (-18.181818181862994) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226330 0xe07f08afd9a8384e9180c6be9a4e8912859520154ae0a0d1aafe1e3f59fe1ef4
6.147 1062.275908951 (36.065573770517304) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226308 0x5b44a932ca6f194cafc55066da7b50d61493d29a0db00474fc169b8ffdca31f1
6.200 1062.275908951 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226014 0xe00446ddd1c4636483141ef5225211cc8dda9618a7d2186337f52f6538f60d95
6.419 885.229924126 (-18.18181818179951) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226014 0xa045a575d065c05f928e34bcc1d92c52ffedf74760ef941d6ccbb7cc9856cf8b
6.628 1274.731090742 (36.06557377053431) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226264 0x6277420b54f60fc67ef0e494d4aacec0e1803d6601363fc56979b937d2e8204b
6.648 1274.731090742 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226308 0xb02d7a6f23dabe8e34503685c97f915f1481e928e8ea2992c9d4bbbb4e0c4e38
6.784 1274.731090742 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5194 226014 0xcbb89cf6ca719a331114ab1587b6098f254cfcd69a6a02206493d8f74dcd8253 6863408 6863408 / 0
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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.