× 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 #441 - 2018-09-11 20:18:15 to 20:18:22; Start Time 1536697095.6206317

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 87.584704839 () 0xccD7BDff63017081B5cF72993d5D84cf2a266330/630 199596 0xbc2c6620b0f3925012a49402dc84653af644d993efa7d7a4197a27910ea5afef
0.400 91.088093032 (3.9215686268364274) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240847 0x7546d409a441547645b2c0e190c6071305bf416221c09c695f3d2f81ebc70af3
0.581 98.970716468 (8.294930876119162) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/630 235020 0xe47d7c363343bd13ec0361cee4078638c071e7cf4a584502aadfd2eeccb49289
0.827 154.849758154 (44.030365768732715) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240847 0xeb9a9cf6d8e7e7419ca9bbc56e81654df22a8a2418f210718d97faba784e4daf
0.943 155.159457670 (0.19980019960169454) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/630 235020 0x00aa2cb41b3801ff1942723804f1c8567a9b2d810becc4d9fa9ccb8cbc14cc54
1.086 263.244588861 (51.665433012484904) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240847 0x164ee31104de0cd4f8d94d7cf05f590409eabb2085a9315348f4be3fbfb4e0d9
1.270 263.771078038 (0.19980019952647787) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/630 235020 0xae4d714e6b3ba8b001b7d4be912cc0ff1a52b3d5870d4e8566b2da4ab2c6b7ea
1.363 91.088093032 (-97.32479760086929) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240897 0x732c4e797a33710ec9626ab5bfd35034fc71b29972dff561d9f6e1492a59fe50
1.442 448.410832665 (132.4646714250119) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/630 235020 0x8169e0b2179ed0e3018e5e3bc7491c5299782fc686c7d95b029650759b3806a7
1.626 760.776861807 (51.66543301259723) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240847 0x6c2ec534d4ef42ae1f03af223baa657d7be918927b0b625467548cc95183276d
1.741 762.298415530 (0.199800199719654) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/630 235020 0x1cec7f383845a4421e16e36d0a60109b3d0a180a7c696b2b6d756cef114c200c
1.879 447.515801063 (-52.038174150981675) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240847 0x5a921c558e9058c543ae2a91da1beabf71d383ee46893fb843ad39f90ce78d56
1.997 861.579795996 (63.25955046571568) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240847 0x71b7fc24f41fa15f9a783498337d1a19f0c8ad6336ff78c814aeca6db63d0213 6313978 6313978 / 0
2.113 154.849758154 (-139.0612925325672) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240897 0x1110408a5d62950c6fce88ce044b6fd671fbfdccec583e6a89591080bea46a23
2.422 263.244588861 (51.85185185156838) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240897 0x97dd3ba23871e6181728626998d1108a12e9dac45283f5cca0a37e47b60ab4d3
2.892 792.790352150 (100.28943981380709) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240897 0xfa53da6ea5aeffc68d9429f33e58c4dbc3f70789b1f18f52c578208f53a0a59c
4.894 13.000000000 (-193.54670853761723) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13419 722241 0xf888a73de026ee258d8022a2fa11a762dcd79e801dd8378ae3504ff45d902fa1
6.965 792.790352151 (193.54670853762522) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4643 240963 0x37ab5e34bae8e0fe6ee23901b54b9747c6932ffbcfae8c3d9ce9d4dfd124cfd8
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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.