× 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 #570 - 2018-09-18 21:20:27 to 21:20:32; Start Time 1537305627.7835143

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 72.449068232 () 0xf666666666E8025c503209ac580a5aA4b39A090c/377 168028 0x10991cd29e768fc1a8e88a0d3d2f2f9472f89f1fee11b0ce3c4b669473478805
0.578 75.347030961 (3.9215686270795094) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4732 209623 0xfb181b9421e99b602f5c33c74bc6deb9def8f91f8595b4fa8f12e236a0bf83e0
0.583 75.347030961 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4732 209572 0xa43e2b21f352ae413a7dd3254975c02c483977a3df12a30a3f3b397c194e8cd1
0.780 81.867447102 (8.294930875751911) 0xf666666666E8025c503209ac580a5aA4b39A090c/377 197942 0xc5c8b1d18cbc8dc0a067107aaee37d3a82cf87e6d83d42f1aa1592bc23c04c6e
0.927 118.951908956 (36.9331548332317) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4732 136376 0xfc0cb095af665920285ccd99aaf5eb59f52ce22f771895af98294d9b75fa971d
1.410 128.346132538 (7.597491290466143) 0xf666666666E8025c503209ac580a5aA4b39A090c/377 197942 0x925833f01c6e079c171f3a56164c1f9f3883f455cfb3238594da88b18b2fcf08
1.569 202.218245225 (44.69453919197732) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4732 136376 0x150b391f2721baeea45a3475a3e77f035aefe1729f3bb673aec49070fceb10cd
1.784 217.752919476 (7.397971840309545) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4732 209623 0x9e980806c816245c92da5b2e495099b03ecb705cd6a33539e8e52981b3b93c53
2.286 218.188425314 (0.1998001993638801) 0xf666666666E8025c503209ac580a5aA4b39A090c/377 197942 0x7a6e4eec4ecc0e79416eb2fed63f41a04e38db714954e6adb2c9fbaa634b84d8
2.485 128.089952633 (-52.03817415061943) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4732 209623 0x664618798694efabb1329d0c528c0ee3aabf41108d90b90125d7b5ce10aaf0b2
2.505 343.771016882 (91.41720895910791) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4732 136376 0x4167fd049ecc8d1e8ed346428b960e799f6859d6f63201e654d4c239ae9d82d8
3.181 370.920323035 (7.597491290758597) 0xf666666666E8025c503209ac580a5aA4b39A090c/377 197942 0x81c42bdbb634f61323242a450b5ec49750af2c3c74152ef289be92689983d963
3.391 584.410728699 (44.694539191728005) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4732 136376 0x2bb1d44954d37761af7f90a0c5bb80e695a53554e22e2afc0e8f1d1d32a5228b
4.232 630.564549159 (7.597491290747764) 0xf666666666E8025c503209ac580a5aA4b39A090c/377 197942 0xb3a174a6615a1301dee6d4900e483ffa9a40ff1e247eb144939791093397b824
4.494 993.498238788 (44.69453919177465) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4732 136376 0xd58d28dab268a97efc4b14fe3ace8da4e6d565428b630c1b75438eb6877ab6de 6356598 6356598 / 0
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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.