× 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 #1049 - 2018-10-17 09:18:41 to 09:18:48; Start Time 1539767921.9594479

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 3878.445528778 () 0x0000F7F39325076881E5fC566E99595542532aE2/15882 151337 0xcbe08f9a2375dbaed0f648c8d2992e47b0acea0b8f468e43b3115711004c840d
0.207 3878.797476246 (0.00907403487997115) 0xCC4A5831dd286b3De8820f4D562Eccc4af635B43/124 151198 0x5e8f2fe2ba16f4f233e90165dfc2c3d14ba1e0c641c0c7542ddf926b47b2a993 6531069 6531069 / 0
0.260 3868.237572626 (-0.27261793843407395) 0x0000F7F39325076881E5fC566E99595542532aE2/15882 151548 0xd9992fb8ce826877c2104530ffc834000fca549db89c7d6402831a5e76404e59
0.414 3870.449390592 (0.05716261625551665) 0xee634c2b0553aA8e123595c5B6b70a42BDCB5cA1/1664 151242 0x1c5b954bbf7b9fc4589ce52f8bdc9c8700fca6ba3f3667c093b324b614270a0b
0.497 3852.397727554 (-0.4674872559780416) 0xee634c2b0553aA8e123595c5B6b70a42BDCB5cA1/1664 151619 0xe9a142989610d1b22def27d557ce83c242334bab1be0fa16a753a68367a0aead
0.881 3879.604542284 (0.7037456477769511) 0x0000F7F39325076881E5fC566E99595542532aE2/15882 151313 0x6bf6dfbde609a82a2b710a378755e357c48d219bf294cb21f4beeb056a1a3da0
1.787 3878.604024836 (-0.025792486483033852) 0xCC4A5831dd286b3De8820f4D562Eccc4af635B43/124 151203 0x639649d3d13ec7ca721877d26be7b72436bea9a55a9da63b59396a8e2d0505f5
1.956 3867.320602714 (-0.29133828857224225) 0xCC4A5831dd286b3De8820f4D562Eccc4af635B43/124 151436 0x4d8af29de93176471eb2120e0876769822dad643bb2600af2613b1ad70ff927e
2.942 3862.651111884 (-0.12081521129454324) 0xee634c2b0553aA8e123595c5B6b70a42BDCB5cA1/1664 151404 0xd5e19b68cfeb767c7721f52a063671fa23de905c2fdff804ba7b86109c733f2c
3.992 6.000000000 (-199.37962873089603) 0x7D69c7A72ACC68BC9e4D1E13c37d346F6F5DB411/4100 463286 0x3996c14cd1dfda5ed40963df2cf2e034edddaccdd783c638200ea4c6f3185478
6.730 84.000251715 (173.33340791534698) 0xe0Fca959877F8E328DA4694C7833EA4831b828Ab/1656 550000 0xb68e999f6a614a3f740f98ec3c553f8d70ceea959aec724fb1bb0d5fefc5b99b
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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.