× 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.
*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 #1401 - 2019-01-11 09:15:44 to 09:15:59; Start Time 1547198144.081652

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 7.225000000 () 0xF3A3fD06A875A09d7Cd5fd18FDBE22493fC86aBD/8856 397815 0xd1e8cec552adba1e4268f12bf503e6701a697195fd5ca40e13441d22e2886abb
0.103 7.225000001 (1.3840830448869148e-08) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/14150 250000 0x5a77157f7605ceda2f10e125156de256786320b502ce9d1eb761b99bcf00636e
0.632 25.000000000 (110.31807601829891) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0x087c2d36b5a3ae11e94a00d17760d779cc14a40bc61fd155babade0aa9f57c7d
1.178 28.750000000 (13.953488372093023) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0x4bd217b1a1418c9d3f525c38e8331e228fc90901af1667e0722b9a017284fd85
3.190 38.021875000 (27.771797631862217) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0x74015015959449b983e84d254b92f77809d8316b3b2f0c808609ce3ba7155fd0
4.758 33.062500000 (-13.953488372093023) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0x649aedff862b73f92e485f2387bc6397b2bfba5f823cec3688983d12b2d00384
4.835 43.725156250 (27.771797631862217) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0x97731e5a535af731fd46c7c45639b7a02ac3cca1e0d014d29e5d801074d67363
4.837 57.826519142 (27.771797634194172) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0x7bcf18912c1dbcde238e84de4dcee908bc10b756dbd2b3674583fbaf06c2a9b8
4.940 50.283929688 (-13.953488373469739) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0xe5a102544e50247bc24f5b30ec42f456bbdde0333549681a08b430e8884d8587
5.110 66.500497014 (27.771797634251318) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0x87a563211f1f9b01c8a1ffb81cc37e2423cbae0cc3b6fefbc16c586574018257
5.575 76.475571567 (13.953488373264141) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0xe38e87820164783bd42605bd99fb15aff483728f1bac1f739e2debc789df02e4
6.078 87.946907303 (13.953488373167962) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0xb9a90234ba9fe6816b0899597cf6bb1fa7ccb7ff821288ef3701ffb5108fb333
6.862 101.138943399 (13.953488372634181) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0xb3965ebbefde77b4b769829b0e2acdcf40d9765a9a11c956a3b6ae52f64de531
8.963 116.309784909 (13.953488372221361) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1842 216264 0x7ac067ac2900cb85ec24a862dacb798eea26d225dd98352468e9e0a0b8bacf3e
9.763 25.000000000 (-129.2334921715453) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0x49ed5de3f1afcadc4e37377c07b840390ef7570f9944bc432d695e4a788643ff
11.051 28.750000000 (13.953488372093023) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0xa63528354404bc0d752321b29b159bcb8931ee8e4f2cb6ba0f2f84258695098d
11.274 33.062500000 (13.953488372093023) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0x62e8d9003a8e1147240e762b3d6fbda962beba4f706e3bdedd930ba0bda333e9
11.704 38.021875000 (13.953488372093023) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0xb64cb5167b0a0aec97c168e75065e48fbab7fd609c876bc8a726574da80539a9
11.887 43.725156250 (13.953488372093023) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0x87d6378ac293c05641e7cd250e3bc310c373e4322e513647ef3022282e18903d
12.345 50.283929688 (13.953488373082537) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0x762a373c0eb7cb5fc579616c7ac3920c262f9c5eec21914f004b47561fe494ed
12.722 57.826519142 (13.953488373469739) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0xe493b87b1df50fbc328a3b5244f967fd367a1ec15a3e324192c8dce42ca3e8c7
13.466 66.500497014 (13.953488373140525) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0x5c9c938d1a7d69f64e4a0e14b0d9adac93ba81507224da69dff5a0045a87ddf9
13.876 76.475571567 (13.953488373264141) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0x0dfe542932dd0ec8843a6e1c386dfea0c048bf70feefb5ec877636a03a10e2e4
14.011 87.946907303 (13.953488373167962) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0x36459e8f425180b001029e42df93e779a4af81345e9b83c155a5b1789a1d542d
14.443 101.138943399 (13.953488372634181) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0x5994dde63c418a7aba1f61d44280dfe8d3730528740394f3325e4ca8e5535f22
14.984 116.309784909 (13.953488372221361) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0x202fb656056f11ad9b60c0d1b7e144e56be297eaf136c668cf6af85b44847f28
15.326 133.756252646 (13.953488372576617) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0x6dafbdc428186eed6c6c5a58a70e8cf345c4df3d07be60f2bd0f4c661194cd12
15.687 153.819690543 (13.953488372157718) 0xb8D76f4BC2518F8eb508bf0Ccca76f8F9DD57a3f/1843 194388 0xa976bcd8ad2a527cf5a7c92342f999496107cda8852fca1e1a3b9f06673778a5
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This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. .
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.