× 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 #120 - 2018-07-24 05:38:24 to 05:38:26; Start Time 1532410704.7059307

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 5.000000000 () 0x4fCc2FF6c75923D33B4F5aF4C524461014B2EE1C/5273 780000 0xc6e559acd93b74128083eaa84c4c6d20c3862705b11f16952b33b2bd95ff022a
0.346 53.040000000 (165.5410062026189) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4237 225943 0x43b03f6e34dafa92061379b3d39646eb2596ad1f8b968f46393892693f5ad248 6019967 6019967 / 16
0.563 21.840000000 (-83.33333333333334) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11019 240622 0x62af4200e60fbe8664a5924162573830c8b4a7d5fe6dd901ba7a504642b95104
0.877 53.071827431 (83.3829009438252) 0x44dba507b909A6F92F3a708A844d4C4F23622BEE/464 271000 0xed720cdba7e5b4b0f2d9beefd770f80abcbc4744c40917a76ad8687f14d647c8
1.502 53.040000000 (-0.05998847022156134) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4237 225922 0x54a622a21f07b03afd38d29cb12024c88c30417b4d55f3e3b205937396ea85de
1.662 22.783042243 (-79.80940057781268) 0xDd5e4dbcff073A5f12ADb90e156db5Ea96557982/1439 226178 0xc0c4cf04b84b4c1b2be1de638f66c3281c4ce4eb8095eea18803b8f81fb7ea44
1.816 153.285600000 (148.24054538557493) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4237 225886 0x8bc996c5af75974c86865d9d87b4f0c0db31e546dda55de9990c88b6afa5988e
1.823 53.337186568 (-96.74481221760772) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11019 240622 0x7d9ebea4c3693f9f684b3ab289f83f6310ccfd4ae9c2554a89aa3d428081874b
2.000 93.980196143 (55.17747984259462) 0xDd5e4dbcff073A5f12ADb90e156db5Ea96557982/1439 226178 0x58244a33de5414c8988b4579450bc6f8e12fb5569446bec122ebe08c6bae76d0
2.183 90.365573215 (-3.9215686268127934) 0x44dba507b909A6F92F3a708A844d4C4F23622BEE/464 271000 0x840754a102c8f2beeea90d4df5283a721409da8fc220c1cda7ea6904278a745b
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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.