× 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 #922 - 2018-10-10 15:12:30 to 15:12:35; Start Time 1539184350.468729

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 21.841000000 () 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 192213 0x805e63c7e3a684e7cf3f71fdda4370aaf70f953672259e1ddc79bed0d33f3441
0.248 24.025100002 (9.523809532115274) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0xad60c84238cac00b93eeac9bc2071fc901f33ad9685eacd094909906575aff56
0.398 24.680330000 (2.690582951318135) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0xc59be80686c3615743681ed38831a7f6cf0abdcb3dd86935052b610ff8999a1e
0.482 5.170382049 (-130.71680112001604) 0xaDA1ED8Dea59b7B082937460C0863AbFFbB0484F/13136 231858 0x009a7c5c81223fd3d6dba2cd412aaab247f13e9a0e7d90d1ee5fd3dba938a7e1
0.766 29.070371004 (139.59966895591396) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0xcb6c4a765ccc9e59a78a0c9e48d6619b88131aa5f16693a02a68016d7b5c2e5e
0.855 29.128511746 (0.1998001997727353) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0xffcaebb2eaa5aa7c93e73d2558fcd26c46aecbb8608c08b9c4c4ddc01e710713
1.229 35.175148916 (18.806509949046298) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0xb1a5c0e4d031b30e4157052fb97c1fe85a0b66d4e6d79f5659e9072ec137bd12
1.316 35.245499213 (0.19980019743961708) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0xda0707f0f531740f0289bc9f9228f1a92547cb8b0e87f084247b826fae92b3c9
1.736 42.561930189 (18.806509949580562) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0x9dffb313637e55a7c6d704df3c754273312e47c66cb4f72969de636535780dbf
1.821 42.647054049 (0.19980019891385575) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0x9022d7d058aee2b4492268ae1736b1c8a4b8ad4656eb44891a37361e9d6ac1e9
2.272 51.602935400 (19.004524888241296) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0xdddd46627e3e2367722536100c8f0896abf318b3cb44a2d9434b9e7cd5f1fdb8
2.275 51.499935529 (-0.19980019968780321) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0xf80c199f0cf27293ae3196c9b21b9586f67099fcea52c4a2a50e0eae6c10306b
2.735 62.314921991 (19.004524888324966) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0x19c5ff47c6cce1c768f5528b1059b6c38e9bf2a7007156622f794c559afae484
2.757 62.439551834 (0.1998001982274803) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0xcb14e3c62eddc6701cf5249476a67cf6d94ef06bd78da5cc0729d2d66ac0fe91
3.273 75.401055611 (18.8065099497937) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0x6e0b1cb1c8fc6f4cf93a980f7a7f63dff11fd6231ae00dd9bc41d5ab55bca9e7
3.312 75.551857722 (0.19980019950636219) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0x6dc44e1939014892aa4a7417a8a7d9a41f454d37c21a063f7181256de9eca5ea
3.761 91.235277291 (18.806509947877668) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0xa18ca34bc2d469abd61db4cf071736a644ed21663aff85f9509692f248c20f96
3.869 91.417747845 (0.19980019916356256) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0x7d83b1dbfbf39804483dbe57199f31b67c10a5fbadad5f0197dde003edc2f86b
4.381 110.394685524 (18.80650994807836) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0xfb290ceb57778e2deb732f1299c4ccf822eff1419a78ef3db0d39a9da2e4f456
4.480 110.615474895 (0.19980019975680627) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0xbc75edcdebac2f89cecf81fe08a98e15ba1598098dc78143fe8cf8f455943a89
4.751 121.434154077 (9.324452902534418) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0xb67c471ebc75601fc7506273984200cb65f6749b92322b4b9553f784490a7d87
4.851 124.995486631 (2.890344313913035) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0x98797e77a96734aa3e0ab56183dff909a1cbf7d34c0137b3f297cd32599d04b4
5.256 133.577569485 (6.6380333534441744) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13150 362815 0xbb793305380322b8bc6216ec4483670b57da7df713dfca4dede0e4aaef189bca
5.339 141.244899893 (5.579842452731984) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/968 227662 0x8436ee626345a7cd3d264b50eb3724650bc9a578507b7259431cf61802c65d83 6489559 6489559 / 1
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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.