× 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 #519 - 2018-09-17 09:02:13 to 09:02:15; Start Time 1537174933.440856

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 444.740003323 () 0xccD7BDff63017081B5cF72993d5D84cf2a266330/665 198956 0xbbcc5d9016adcb0729b1b6b8df92be93bdf375a3babc3c539c229eff7bae6208
0.362 462.529603455 (3.9215686272521504) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4683 240269 0x70bc066d07c18ad1f9aca403459c15ad52bc9fae7f4d69cb163c54f07246905d
0.362 462.529603455 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4683 240191 0x38cfc3160b530cb7ef2b3d3df1e60b1252e5fdc23a2e1797348a80945b02d3b8
0.459 6.500000001 (-194.45663987679637) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/15227 492960 0xe4ff23599a704d0dc5c6adf5480769d4cab5af94fc562f348d6153cf44489749
0.521 502.556203754 (194.89250895830094) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/665 234316 0x8240371bfe1178f0469c4455ef10cbef46bd3ff4942d065f978307b88c2893c7
0.661 786.300325873 (44.03036576943388) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4683 240269 0x4dd658c80960db293cd33e3c081db972694e0c351081748223e46f39ec4ae170
0.691 100.000000000 (-154.86857125929603) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/15227 492960 0x1ab21d475d64dff176b13ddb1e8d4ef55c975798adfad7f77ed1a4bce41c07b8
0.764 787.872926524 (154.94850805216126) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/665 234316 0xd38deb2844f8dbcdf11a6cd50a5f76954ac9d83f583fefe86ef7fcaeb5cc7735
0.929 1339.383975091 (51.85185185186578) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/665 234316 0x195958b80c351320a4e08900abcf4e696ee05ffd5f4b496d794597127d51e078
0.965 1336.710553984 (-0.19980019972792784) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4683 240269 0xbc50b49275abe9fae65ebbf452325bf2f9f74ed4fe8492fc0244d43d1021436b
1.092 2272.407941772 (51.851851851819006) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4683 240269 0x9393a1b9933e8022c4403bbdb12edbb51450602c32fe78001169b77be21ff6e5
1.141 2272.407941772 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4683 240191 0xb6d0c3e57109e8608ca62541bd4e44ed590624e4152ff6f4409f7e40eab73512
1.249 2272.407941772 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4683 240462 0xdc525b0fd459d50413e3d2ecd0e293d9a7f72901b14be42968166114618aab9f 6347454 6347454 / 0
1.396 2276.952757655 (0.19980019977630822) 0xccD7BDff63017081B5cF72993d5D84cf2a266330/665 234316 0x44f7ef454f190cab432e4ea4728079ae9324f5873063c02f91d3d5d0217f99e9
1.633 1392.959334094 (-48.17518248180752) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4683 240523 0x744d88a92701a7e5f26a199f1901159e42456beabc05bab6cf2baecd75ccbc7a
1.685 1336.710553984 (-4.121288098291298) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4683 240462 0xf80950a861ea429e494188a6dd1d21cc4134b264096dcee29397051e5e0df3cb
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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.