× 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 #448 - 2018-09-12 00:46:25 to 00:46:28; Start Time 1536713185.5842574

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 135.081339806 () 0xccD7BDff63017081B5cF72993d5D84cf2a266330/632 198732 0xef0c023062853391b987dfe6e56dfc23ce8d804b5c5768941d1b00ae567d51ed
0.269 204.164153467 (40.72732875210649) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240886 0x3afe40134bd4b8c1ba355c34b27bdd63482e8a7678453dcec06426179b4b7adf
0.288 120.096560863 (-51.85185185180616) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240886 0x5ab49d6fcda0e81112f3fbfa51570627a3e194f5832771d7075bb6220c9b4274
0.358 140.484593398 (15.648125124642895) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240679 0xe4dd1d3a139bccbcda5822fa81591fbe950df6aec4026155e582f5f37e664c6e
0.413 152.641913980 (8.294930875236458) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/632 234024 0x13a3166af8e2247ffca62335318351971f189a8314740695ee0216f955dd5727
0.491 204.572481773 (29.07529394694831) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/632 234024 0xbe6bf09a74b1db84e176d450a41c3863163e222156536d1e2ede55dacca3d233
0.572 347.079060893 (51.66543301276736) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240886 0x2291c26be27a3fdf416e852f5cd44c9c1f74ad86708e35e701da43eab01c2173
0.749 590.034403518 (51.85185185183604) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240886 0x5d900eb3585ea16e9d4ffebbb471dc01f091d51ae45fd8272368f72bae8401cd
0.776 347.773219014 (-51.66543301277839) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/632 234024 0x909e6e7fe260c8bd7d26a1d28b86843db26169ff8eec56f39d5c86fbf6b4d854
0.795 238.823808776 (-37.146253757359155) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240679 0xf9e0804d08b9f60cc1b859cfae0dfc1ea816d3d7a77bd66bce5ba062b9d54eba
0.818 140.484593398 (-51.8518518516175) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240762 0xcf0fcefc16c2daedffe0009bb8eec4475fca3b3cc23d0ca8a062c0804dcfbe2c
1.045 406.000474919 (97.17223650362648) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240679 0xf401be02b6619e7f45391265a8004e0a2c4e1ccb0237724d928c5975719ef21f
1.092 140.484593398 (-97.17223650362648) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240769 0x7c55a54e42e2b83d0ad352efd9348a88929a5899eb3a72ad5752f809f105018a
1.102 591.214472325 (123.20088955741082) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/632 234024 0x17a4b62ada601cb7dbf91cd7a738c77b5a1fc9803911c3d52a19bfdeead0fd73
1.129 1003.058485980 (51.66543301253312) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240886 0xe5cbe37108d09c4c3711249a25241dde8cf288efd1061400965279024b281bc7
1.320 691.581208976 (-36.76029517437773) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/632 234024 0xf86bb98612dcedeb2e0e55c484ca988d9a0c65976889fbfbf681acc2bfbf3a4a
1.352 690.200807362 (-0.19980019969551227) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240679 0xef948dadc3bb1aca3f9f6ce47870bdd55c759c08fa707dc5227b101cac5f7837
1.367 1173.341372515 (51.85185185182005) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240679 0xc00fd25c0a54196ed1b73ff9281cb27ab0fee7f41aa947a22b4af1144123ce22 6315124 6315124 / 0
1.432 238.823808776 (-132.3524437678976) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240769 0x0304361b2adebf4b05f2eb65b127013a5ef3cb2c3e7eda7129c1f448accce4bf
1.631 406.000474919 (51.8518518518059) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240769 0x5f6531d767129031f734a408e33c655ae51fae66047a7ba9b777f206cbdb4489
2.099 1173.341372515 (97.1722365037968) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240769 0x5e7dd6c015a30e7d93c399f85d1f3dcb877ad0f2e0e7c3c1e3b1ac045672ae42
3.366 690.200807362 (-51.85185185182005) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4645 240769 0x16ac1e6638a7111e17194ebb91eed6c49208b19d5eba0569bb7f6f7d86b9e545
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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.