× 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 #6 - 2018-06-28 15:11:37 to 15:11:39; Start Time 1530198697.2175584

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 3.842470000 () 0x41880a6C0BF00b0C159a8154d66B676a995D2383/16294 1800000 0xab04b4900ca2b76548d3af4b242eff562f80659a807398052b9e75b15191fc40 5869702 5869702 / 81
0.205 13.035015489 (108.93264278012617) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11280 273884 0x3f32741e4680dcea9995bffcf7c296b8e069d44bebb1b7a04746566ab1103dbb
0.970 22.788582334 (54.4533069692842) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10603 193683 0x3044d73dd45051ae2d551910201d238ee1ea4161a17402782fbe388464f0e233
1.171 25.067440569 (9.523809530177832) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11280 273884 0xcf990a88102b67ac97f9616a9b967cd662886e32522800ccbbdc455fc704bbfb
1.469 38.740589967 (42.85714284908297) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10603 193683 0x80c441456f90708b520ae9fbbb120793cb19d39c6a96182198a997fb043d89bc
1.655 22.876415530 (-51.49284457769501) 0x44dba507b909A6F92F3a708A844d4C4F23622BEE/452 271000 0xf337835db00a783e739ba145dbd2e284f7c9c74d06c43c6b243afa3fe0b0b346
1.852 38.871913080 (51.808681822068195) 0x44dba507b909A6F92F3a708A844d4C4F23622BEE/452 271000 0x059aed7db824a6a5f2533b614c1f3d58b0a56317409269d13764cb9796a49b7d
2.140 65.823745838 (51.48605593878401) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10603 193738 0xe73474c83985646308684ae46fbe1178406762fb4b1f5bb5ecf12179bf4f2e3e 5869699 5869699 / 0
2.320 44.319234924 (-39.0483547207925) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10603 194088 0xde228671db2752c6966113f0bbcda113198ace9d47f6d7226d9a8d850c9009d3
2.323 66.715599799 (40.34115047025106) 0x44dba507b909A6F92F3a708A844d4C4F23622BEE/452 271000 0x035f7cb6ecbac8072957be81ac7884b7776f2bc7e46cc2ca87a535dbb3b28ea5
2.511 111.960305003 (50.64443944373809) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10603 193683 0x8ebf6d0aed3af4b708e65ae31880d6df09d8ae7cf26ce40b86cf6974b9d349a8
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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.