× 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 #500 - 2018-09-15 11:10:38 to 11:10:40; Start Time 1537009838.5794694

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 333.000000000 () 0xccD7BDff63017081B5cF72993d5D84cf2a266330/653 184212 0x1208097e53b2ff2b98eb0b50cb8e984f390c9c88f7b3de3484d6b238e9c09ab1
0.089 1154.066336566 (110.42766773431816) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4669 225687 0xefeca09508f439185627da090298db964b739fbdfa66fb43efa30e6ec8b017ff
0.331 1156.374469239 (0.19980019978878485) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/653 214235 0x3d8cf7a65f95b7e192f6ff0ec85ec0e2254d3791fab523ff0b16bca6279f7f6e
0.570 15600.000000000 (172.39559258211023) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4669 225841 0xa9e8d1edc3e00816da7e55fad2d3aaa38a57d17441857a2bf0a7574c7236948a 6335886 6335886 / 0
0.574 1965.836597706 (-155.23500206161026) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/653 214235 0xc115a6151c00597516f22933f6e0205f0b214ca551070753e9a84279cb8c9aed
0.659 15631.200000000 (155.31437155816857) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/653 214235 0x6d0c4bf0f517b723a5d3b09b8a04afa788abe79b318d130ea571623617047eab
0.696 1152.902026034 (-172.52395095678705) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4669 225821 0xe00ef0cda09c4f49ae5bcccd479b51d78adde031c9cd2038b962f3ad052b0806
0.699 1961.912772162 (51.94599348870133) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4669 225687 0x29aba040193da1286bce537f51c3548467da36b7762b0d4e4c3382595494eff5
0.779 1153.831547537 (-51.87083031916211) 0x0000F7F39325076881E5fC566E99595542532aE2/15862 225714 0xb2151819e8ab8ff37f6f84c9d2e190e7f1f3845554404907787b880c7ce0c498
0.802 3335.251712675 (97.18777927210826) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4669 225687 0xa07fce6f0e4bc6199815a4fe12c71052d65c65dd34d4d07b22329664804e7c1d
0.911 15600.000000000 (129.54407444306796) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4669 225816 0x9d5e4532aa59446056563daae4adb30da085ebafe04965b173be1c5e0b323f31
0.927 472.109603938 (-188.25021442555808) 0xCC4A5831dd286b3De8820f4D562Eccc4af635B43/115 225404 0x76b7ff2a48924468a0f138638dfd17185f5569d4a42df13283f7daffeef054fa
1.283 5.750000001 (-195.18687082682638) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/14629 409196 0x59ae1d87b871594151727af339dc4302ab04de913a5e227d65178b734bfe7549
1.841 2044.470061614 (198.878169205608) 0x0000F7F39325076881E5fC566E99595542532aE2/15862 225714 0x13ef2959731202d00cacd458887f99f4c2ab96d8c2f010b8b79e69e7c164a61a
1.879 2044.470061614 (0.0) 0xCC4A5831dd286b3De8820f4D562Eccc4af635B43/115 225404 0xf50cf064329f3e6e5d5a7ac9b9cc1fc657aed9e81eefb804ef4089c1b917ffd8
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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.