× 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 #295 - 2018-08-22 08:37:08 to 08:37:13; Start Time 1534927028.6311033

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 23.708960000 () 0x41880a6C0BF00b0C159a8154d66B676a995D2383/17527 300000 0xa26f53d9b9b4c775fc41c53d75a628d4bacc9f7bc5520106a9cb0de95622ea16
0.572 24.657318400 (3.9215686274509802) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11584 255309 0x26c492f47cd259b5f58c5c7cd1079affffd0eb1c423c39d498ed994e3d47073b
1.160 24.657318401 (4.055591057216189e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12134 430717 0x6602620f526b8a847c3a676da1e6975ea71aaa508b23683abea84ef6f5a1d171
1.586 41.917441280 (51.85185184806886) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11584 255309 0x95d08297713d3ce3c2ac9a8ba7053a00c1d0795e79dd285e87794476e9567202
1.648 41.917441280 (0.0) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11584 255457 0x8c6a426fcc4b43a9b899322d7e93a44f6f16dd23393ef6413bbbb13424e38993
2.042 46.109185410 (9.52380952813722) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12134 430717 0xb6f32f8c08562e4d7849ee02c52f0beed9bcf991396fd1c9c8888f3a3eb8f530
2.301 71.259650176 (42.8571428530045) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11584 255457 0x660d72bc744465b5e7fa115efa1257028a02e49fab0929463cfed480de66c40e
2.817 78.385615195 (9.523809525591515) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12134 430717 0x7c4d3604941e2fc5f6f37d4c61b73c5a2d86497c85a33ac39ffde53a9e038f7b
3.054 121.141405299 (42.85714285528131) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11584 255457 0x732a713bb9642194f77fbbbddc47ccbd5c70d725785007f52131ca8d35b7f253
3.367 121.141405299 (0.0) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11584 255309 0xd915be1e17e82b5631a8f5f791bbbaa40088cbe2c70bca5f31d316512aa20e17
3.694 133.255545831 (9.52380952538187) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12134 430717 0x1bbd529379675fc094d4fd069b634b124078ed2f00bedf208aaf055e304a73db
3.921 205.940389008 (42.85714285550032) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11584 255457 0x94140f77cb885ab40c741cc0e52bfea83790ac6ca865a138f0fa2cca6261e151
4.474 205.940389009 (4.855774065565768e-10) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12134 430717 0x07702c71131d8fc2521953741cf6d88a848f3c2e6173866cc4d264629b51175a
4.917 233.227490551 (12.426729190367384) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11584 255457 0x63e6e10fbe9c6587ae9b502acb8e968f0af51617ef0efd0b47a304f9e4ca3595 6192358 6192358 / 1
5.040 233.227490551 (0.0) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/11584 255309 0x92f8f30b56c85faa8a49fcce88edbfcb1b0d9a3dfd1895d7770b5ba2e6fc3385
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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.