× 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 #1396 - 2019-01-10 14:33:44 to 14:33:46; Start Time 1547130824.4233317

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 126.000000000 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4411 198604 0x0281d233c389ddad0d14e4d6aaddfd3cc80e3b14bd8e65fd81a4e00e3141bcd2
0.152 1036.521836883 (156.64597567032848) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5337 240910 0x44d386d32514e0822331826f4ada8be62bd8de58c9559217b90597a89602f8a3
0.288 3328.491506688 (105.01547140426143) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5337 240316 0x3e4408bddd6b79aac919f07ca16daefbbaaa5cef74cf5dad6ee5db0e3ebbfdc5
0.358 2218.087371966 (-40.03924433475159) 0x0000F7F39325076881E5fC566E99595542532aE2/16019 240494 0xd0a2c14f48c61b2a5859c4f06d88c9d8948d0806dcfbf88d762061e376830ea3
0.419 1038.594880556 (-72.43522087526911) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4411 233833 0x3e84ac8042b3f0bf3d2878281a25c0e03ee7e62dcd03e5be756c78d7bc134ae2
0.426 3335.148489701 (105.0154714043067) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4411 233833 0xc0442f56f4358bfd0c77b684cc6e81c3aa114fac95227ec99aa6e096c0ca4dd7
0.575 3748.754718092 (11.677354030924418) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5337 240133 0xfa422a8bb8260f81db8332e94a47ed7204ab6456445c030f31b8b4ea18ea69ee
0.608 3755.377199403 (0.1765022625884405) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4411 233833 0x9bb73230cbcdf1c123a24014bd95881ee2e3affa2cc113f47fe03f19b5497b5e
0.611 3744.885794174 (-0.2797609960606588) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5337 240316 0x58b66861c4f674b0ab9801596a664cdf75c03c352ce6fd54744691701c8de604
0.709 3468.554429289 (-7.661569412779855) 0x0000F7F39325076881E5fC566E99595542532aE2/16019 240494 0x6f2aa57bc8233aea58402438cfd3b2cca07bb0d91603b61bf8866f67d108f0fb
0.740 4217.723933325 (19.493686507112592) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5337 240133 0xe17d6dff9ff8778234a48fe47873aaab36562ec1a8245e40c8ed7374933358c1
0.809 40.000000000 (-196.2421236673499) 0x44E05b25115Fb86F0e9861ceA0Bf27E50f2338BF/19590 488182 0x23f3db093c04de86dac40c98ca0f8f426215ce7108a4d25311702a7ccef98f36
0.823 4228.554726527 (196.25165869361643) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4411 233833 0xc7b35c7b22fe4f1541d1e71aa31f41983ce9577e9432fdbe3182d5c26d69af16
0.834 3902.470588393 (-8.020738480192724) 0x0000F7F39325076881E5fC566E99595542532aE2/16019 240494 0xa479edb223ae765ad4d62b7c63b58ac318a4ca563c0a4e1d213c242f608f5fea
1.006 4745.361197383 (19.493686507093972) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5337 240133 0x19f5116635c6135de42a7c6e009e206eb32ea324e9b36b1de40576b25ef9fd4d
1.020 4390.669659000 (-7.764674703023587) 0x0000F7F39325076881E5fC566E99595542532aE2/16019 240494 0x936b5448cc186afbb2f7ffda00a1a6aa887c700ec7844738e0ac8d7fd509a1bd
1.030 4761.352622069 (8.10056950660532) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4411 233833 0x7a467c9789d1be437498bbbf8c755c35d7e3d5a326727ca287e36a7d4348297e
1.058 4740.463720003 (-0.4396822947105057) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5337 240316 0x4998a3292dfdbb6032c8b734f29e11ba0ba5f268e50782677118be3ffc993b34
1.203 4939.942433340 (4.1212880983947695) 0x0000F7F39325076881E5fC566E99595542532aE2/16019 240494 0x41203efbcc4feeeb788a632fa3ceca706fc09a36d81a74db0b2f6558ef815639
1.238 5339.005883175 (7.764674703030308) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5337 240133 0xe432de40e40f60619af576d8e7c64203bb37de2ae63e0a458eb3bcff871e86aa 7042884 7042884 / 94
1.250 5333.495731375 (-0.10325886093074782) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/5337 240316 0xcf868ffc4dc1b1c2c6067896b868164c64be3de7037d3cdacfafd8f00f8ab951
2.376 10.000000001 (-199.25142636927492) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/39503 503502 0x71758465cd66c52fe15996f321ee8bca76699b3fbf67a882042f0503735e2d8d
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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.