× 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 #841 - 2018-10-09 10:38:25 to 10:38:33; Start Time 1539081505.5492902

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 121.489788406 () 0xf666666666E8025c503209ac580a5aA4b39A090c/430 128712 0xff8d318dfafc1aea81e0ec5f0889948544b4a5989545b5073406497942ed923f
0.259 126.349379942 (3.9215686272611037) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151244 0x426a004b113775873bb63ea084ecd2cb48b4da9afe53ffb28b12c110dfa74569
0.376 137.283460898 (8.29493087519847) 0xf666666666E8025c503209ac580a5aA4b39A090c/430 143618 0x09e0250dd9b24a2057c6d361fd7c4c7c2483b7a74d86bae0c689b97475da150c
0.398 126.349379942 (-8.29493087519847) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151432 0xe4b03ea15d5a2ccfd2af4cac8f71244e3448e79f3cd79f9142f2852779928856
0.575 214.793945901 (51.85185185167814) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151244 0xa2982b69520216d389a53203e5344f01c829eed43113fa8604baf95ec3a242ad
0.801 149.508449915 (-35.84137614015257) 0x8e56785Ad6231A19B3326A10Aa8a6fd3dB5668a9/1 250030 0x0196b8dd83209625d2b12155bf067a238ff093d0f258f02bad46ac370f91a9b7
0.873 214.793945902 (35.84137614060318) 0x8e56785Ad6231A19B3326A10Aa8a6fd3dB5668a9/1 250030 0xf684e717e888c27a7832758199b3163aa11aee8a20ec1f8819485f9082255b4c
0.972 215.223533792 (0.19980019896200232) 0xf666666666E8025c503209ac580a5aA4b39A090c/430 143618 0x7c2aaf2baca16e6c0c65fe1a16c4a82d4e79a8ce03b7ec0a32fb11d9b68648e7
1.063 365.149708031 (51.665433012752125) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151244 0x8fb02336316853ab22a7b262f387328b12e406196aaad58a6c6824bd25099e4e
1.091 365.149708031 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151432 0xd63d438f09dfd3d6ebadc4ebf752101e6ee786c68a84a7d6aa009dc96d91552e
1.148 257.752735083 (-34.482758619826065) 0x8e56785Ad6231A19B3326A10Aa8a6fd3dB5668a9/1 250030 0x89f4b784d43f38e5b4fefd31e5592e43e575f374645d5830617c22185ed6c44a
1.199 365.149708032 (34.482758620091786) 0x8e56785Ad6231A19B3326A10Aa8a6fd3dB5668a9/1 250030 0x7e9106171368514981b04c205314ff8ce57c09d8be9bb78f176381a6b5c124ec
1.325 412.619170072 (12.206572768948613) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151041 0xc895e02fec51dcc3c25173604612fe98babb39dcb97e2e9b1b420b1da25a3c1c
1.358 620.754503652 (40.282685512963845) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151244 0x0791397b607e5d1ee6a5f6ef66e9a30f470beef077e8fb8f98fbe5e48a9e7129
1.629 621.996012659 (0.19980019975132493) 0xf666666666E8025c503209ac580a5aA4b39A090c/430 143618 0xb8f5a866695c8c2300025037cf3566ec50b16a58a608b7605352b3bcdd77f6f5
1.639 124.590374929 (-133.2479793361812) 0x8e56785Ad6231A19B3326A10Aa8a6fd3dB5668a9/1 250030 0xb07e0f03b31c8b146299575faecab8acbd7fb1a29a651736be245c68e3e5b930
1.752 1055.282656208 (157.76142969928318) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151244 0x16820317372e6ea1e90f7befbf2fb600ef22f8da075d44456abadd7b7f16e3a2 6482260 6482260 / 0
1.959 365.149708031 (-97.17223650374093) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151229 0xfec3b9f861888e57a9e33ae2ad87e355b3ad81b9bba290de0fdb5cd43db58d71
2.116 701.452589122 (63.06059568569607) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151041 0x49aa83ef8fb38990ce4d22ec22aaad7af038c79524bd817d0ad6d42c59d048dc
3.149 214.793945901 (-106.22875495158814) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151432 0x26cbc9e32ef276808fe6a11985611f8dd407e1adffe42cbb6612e866c4a49f0b
3.974 126.349379942 (-51.85185185167814) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151229 0xc75f19973496264c9b0ef71f682445d6f54495638dece250cf026340bd559840
4.476 620.754503652 (132.35244376769307) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151432 0xff2855172d8679660edf78fff3c97b613d3be26c1e1913426b34fb722c6ddc82
4.975 1055.282656208 (51.8518518518165) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4818 151432 0x6a96eb051fa763bfedfa06c687a2fe3a10969be6032aac86157c2318b3c445ae
7.972 83.879240000 (-170.547034524517) 0x41880a6C0BF00b0C159a8154d66B676a995D2383/18034 300000 0xd5051e948f2fd4ad09c7f30e5efc30eaec436c0bb3dc0d4cfb72688d57802c49
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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.