× 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 #416 - 2018-09-07 20:01:57 to 20:02:03; Start Time 1536350517.4407907

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 21.841000000 () 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 176847 0x0c7d4f87d1dbd5d9644a96619ce8f98b414970c7ce5f5ad7c6709e07a9248080
0.339 7.000000001 (-102.91598764595832) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/11502 351378 0x59abff31f31261383aca6ec239f328d07d34bb784b3904195d5121a25a9332bb
0.534 25.050000000 (112.63650545046376) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0x39b3ab21cab89d77bc26c5db347e768b8861cc7bbde2832818b11c5893cdc88b
0.709 28.306500000 (12.206572769953052) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0xbf2cd96814ef38a3e5bdc1c9fc188d078fa0b92e3b879226e42d7fbf50193d3d
0.715 25.050000001 (-12.206572765975906) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/11502 351378 0x0ede641ac13204401a9d59206cf1d31f1d9d4a0f3f65c25b54750987918a07fd
0.859 31.986345000 (24.322543805632662) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0xf8d8257fce154ed52ad1e9979b3d9a661576a78c3d6c98cd3fa9e470b7b1f235
0.875 28.807500001 (-10.457785649016643) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/11502 351378 0x448856161efd0fb2b0a1462c4b36bc4296b0bd1174f33a4862a8ab633b427048
0.899 21.841000001 (-27.509205602238595) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12431 457716 0xc2304349c3b8fcd18110cc9749c60297c5cef976ae4f5621cd9609dd3626655e
1.031 36.144569850 (49.33492896855036) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0xe0e882f51cf961241c699c92a7ca23baaf7e702a1cdfb235d71981256dfecaa3
1.049 33.128625001 (-8.707393546629422) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/11502 351378 0xd54577a14dc10f36cd07438b171016a72f3046330e91e6ea3193dd9a69764e7f
1.200 40.843363930 (20.8585412951278) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0xd31f1223368bd62819d43edc3d2377b4f17ac4aa143bc4fdb606cc4465d78d86
1.353 38.097918751 (-6.955663971395763) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/11502 351378 0x5def37c356e9f94d2c281fe3b8ebf396af1ebb951b91929af4eb7336a5ef5609
1.368 46.153001240 (19.121648736560918) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0x2b42261f51e6677e12a922cad7b96ffbde469eb237f27ffa18a4bf0ea88c4225
1.459 43.812606563 (-5.202865259633041) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/11502 351378 0xf371f006b34dd5b98ec0296c796fdfe7ad64d2da7aeec75b353a8fe6f0ae0df3
1.508 27.500000002 (-45.74957317296035) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12431 457716 0xe6d67bd111764b9d4f7482387bbaac553447d52f243bd4e87ceca2512dc1a72b
1.561 52.152891401 (61.90080727708897) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0x4d2e7ef592e2be6a95931747feee372adfc1fd15c7cff36c08b2e712e5cdba3f
1.725 50.384497547 (-3.4492664034907485) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/11502 351378 0xc0ed325074687d6ef2655f8c17c792343f7c42847c1db7bedd80da66b276be37
1.770 58.932767283 (15.639377273651094) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0xb688b337dd9971ea147553bd014250190f7a3b72457512e1de10bea34daedd11
1.979 66.766765001 (12.464640998504608) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0x2740061db94114b19cf3c9b3c39a95f69a184c58a206d7c350a41219c5eb4c5a 6290104 6290104 / 0
2.046 57.942172179 (-14.152302187072491) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/11502 351378 0xec37a4bcf6c08152a845caf004ea59b72bad4c8aefb0ce063c28b2fb0e89e531
2.200 66.633498005 (13.953488370823596) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/11502 351378 0xec7b6f0f52fac4a9b62b7b320750ec245672741a0966730b429c396e11d32110
2.264 33.275000004 (-66.7780992924045) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12431 457716 0x9046caf2a0aa8a85b2a4bb2a4759e0ca9d44920b0527def5172c559d1c2016f7 6290104 6290104 / 8
2.264 33.275000004 (-66.7780992924045) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12431 457716 0x9046caf2a0aa8a85b2a4bb2a4759e0ca9d44920b0527def5172c559d1c2016f7 6290104 6290104 / 8
3.092 76.628522710 (78.89378181046682) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0x04900460bf2986afe35cb48897a33f0f0fadd1be6d449253ad940faab094760f
4.127 40.262750006 (-62.221536063440055) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12431 457716 0x82069428eaffae6efe30629b09159737a55bc449b498ddc40489e4696f534fdd
4.390 88.122801117 (74.55675610279165) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0x1b348173e1084e028f74433b6eab52b0ce164683009db25e0602a764835ce74e
4.531 99.578765262 (12.206572769742948) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0x12ab00c258ab38d14f43b9938723a2b96e54192561ecceda978937ec6b04b73f
4.735 48.717927508 (-68.5933540444929) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12431 457716 0x76f0cb0dda0e8cef1271c4bd415778581bcd4ee789882d16e672ab3fd76fab3c
4.837 112.524004746 (79.14328034408325) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0x347019a6450a000dd7f779919cb04050c4b1dfad06765a59d594433e14947da1
5.143 73.443441503 (-42.02946701830095) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12431 457716 0xf76a4bc603dd7c90c00ff7af73335143c47a5bacc05f2fe7b175d0225a650cf4
5.198 88.866564220 (19.004524888405545) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12431 457716 0xa573ad81d6727414eceb17d7aba976631ace5f6ea5334315290c9d122d4f7227
5.265 127.152125362 (35.446526609418136) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0x1e0423d46e77aaa3cb3ea44a5be17d34f648b7f2aa54e5acf35c4e023e01443e
5.744 143.681901659 (12.206572769911448) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/704 207241 0x97a6bbde5a9c694ec83a21149bfdba1696e830e72c9da006854c66b1c194c212
6.439 99.578765263 (-36.25998148738233) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12431 457716 0x62824ca0f8d73e3e60883aebf6771520d1f2d6a6132713eae6dcdb19bb5383ce
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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.