× 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 #553 - 2018-09-17 16:59:57 to 17:00:02; Start Time 1537203597.4324634

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 222.604879880 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4211 198604 0xc2251623c3395eb5be22832ee00fea4d996495f9c48e04964fd67826a4d63f5e
0.192 231.509075075 (3.9215686273646235) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240246 0xf84211d6c331c9148c1a56cf821576ba9575176cb1ef2f30eb5820870a16dc93
0.271 231.509075075 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240168 0x5d3ccc43dc91727dcde26762e7bb6f490bd4f48ac769ed65cdb2dcdf1515713c
0.347 231.509075075 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240320 0x8f6fd396f51767eeebb4466499c22333e60fbb183617a5fef13cb412a2732718
0.371 251.543514264 (8.294930875503534) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4211 233813 0x4271c36df918c9faea9050a8bc23447f36014898798f8f4875941ffaedd93f5a
0.731 393.565427627 (44.03036576944442) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240168 0x3bcb2768d59c67cb578d568a47492820f12a1cae5e79bca9e5be6508e860e026
0.844 393.565427627 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240246 0x36f5c730dc19bbb28949cf0cf7051d11e006b047e5baa1a5af0028637e3c7bd4
0.882 231.509075075 (-51.85185185173334) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240185 0xba42c3fde083bccd2eabefdb5fa159283e300eba1ba974a26e97b62965629133
1.048 394.352558482 (52.03817415089054) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4211 233813 0x25ea537e085dc16ba730478ed51f71d9cd1655f320b1b16504df4382bd9ab4fa
1.196 669.061226965 (51.665433012517845) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240246 0x32706062547fd22771ba33bccea25e1cd635be50350b4f0c6d9f63c57dcda35f
1.254 669.061226965 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240168 0xe6cbef2a36f1b04cdb2c07ad445095194a393b50f628ccba698d5f966b180549
1.279 393.565427627 (-51.85185185172637) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240320 0xdb53919c807115624a66bb232fe639387dc51f64adffbde0580009cbdaeb5b58
1.719 13.000000000 (-187.20993068606242) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/15403 350683 0x8fb7270e3aab4854e093bc1c883746307f0cd1e1a59db9d93532c558bf6d511d
1.817 670.399349418 (192.39097900162116) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4211 233813 0xf107b49849a6c63374211e2671c405c9a00ba2d035d6d3cd3e851fabb6c68f8f
1.945 1137.404085840 (51.66543301267171) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240246 0x3f246be53438579fb9d23692a127fefe01a6c85f7e9f8c6639abbcaeebc2f8ad 6349481 6349481 / 0
2.104 670.399349419 (-51.6654330125325) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/15403 350683 0xf815d2e63d2ab64970798c290e84eb50924c44f6b6b79a7c7f52d1012ba7c3cd
2.717 1137.404085840 (51.6654330125325) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240320 0x8ecc5ff0a4b777de0a27cca375345593d0fd389b3401f6cbe06ddb3bad2aeb59
3.116 669.061226965 (-51.85185185181085) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240320 0xd4cf10d67fd8c18414a7ebd4e56aafb2986b551476935122b6caa6a8d563a8e8
3.495 1137.404085840 (51.85185185181085) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240168 0x7ce4c6bd260ac5e020b2e7536c7fc7eb9cbf742d713664e1362e2311f5457023
4.260 6.500000001 (-197.72708216310943) 0x5a289646BFb958c3158A33b1e4b8a8c254B3B5AA/5674 492704 0xf870cdadf010b36d1bdb4eb98a9288901a32c159ba210bb61e96dcbad3d6e9b5
4.587 697.215323394 (196.30532416452638) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4724 240185 0xacda5fc9dacb5f6614ed7379a6eb912401ea3a04cf7783400bed5bdf460a695c
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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.