× 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 #1144 - 2018-10-22 13:27:55 to 13:28:05; Start Time 1540214875.7269459

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 48.150279838 () 0x521dB06bF657Ed1D6C98553A70319a8DdBAc75A3/28216 210000 0x53cc8cc406f7e68da7d36bb7c643b7d8726017124963a1e338f02c1ecfecb166
0.649 163.210624560 (108.87571194844752) 0xf666666666E8025c503209ac580a5aA4b39A090c/476 129272 0xc890a6262f508589f81a5f52c161e3c64807aaad9e3735c416abd24d0ca731db
1.324 186.060111998 (13.084112149318647) 0xf666666666E8025c503209ac580a5aA4b39A090c/476 144330 0x99a5c0ccdc9f9f6d4abc3016ba83cc74dee3a295fc6790ae3505a4f6be485b7f
1.448 169.739049542 (-9.174311926626133) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4893 151689 0x479f62cd462d129a140417301681aafb13d37674534d4a7796cf9f43a44be3ba
2.421 1417.677515674 (157.22885768956215) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4893 151689 0x0b6f15273fadf1bacf8468896c1f914059c71d65ef83355c4f3695162d26c758
2.624 835.595806298 (-51.66543301250102) 0xf666666666E8025c503209ac580a5aA4b39A090c/476 144330 0xce899d1be6752d7d3b6f0cbffb665633b72c8800b6c62365161707843a33bba4
3.026 289.133496990 (-97.17223650357263) 0xf666666666E8025c503209ac580a5aA4b39A090c/476 144330 0x5d4d097b6630df55e2660f03a341e8035057ce1fbcabf43c1d13bb67c6e41fd0
3.178 6.200000000 (-191.60271345690268) 0xC31D1da4C9Ca879cF3245b821593761c784E15B2/877 250000 0xbc4ba873c9478813b5d4ce4669ed3809de79d930596e38f450d581b1a53f1d22
3.685 288.556384221 (191.58627214621902) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4893 151689 0x136ffcdfcfe5c30f990e01c7904a16f80daf341f23afa069302f14477eb8704a
3.789 491.526944882 (52.03817415105928) 0xf666666666E8025c503209ac580a5aA4b39A090c/476 144330 0xd4ad91951957e56e9b6c44e3718338580a93acd4071290904f6c5078c5e1f71c
4.757 288.556384221 (-52.03817415105928) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4893 151966 0xfe2650260a6e68c0c2b27626e7e77065349247114712bf8613b1732c9ffb1e50
4.909 490.545853175 (51.85185185171874) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4893 151966 0x21dcefc85fde53719ba333913ae9dd6aab64b90f717d1e86fe2169ef04994d57
4.985 289.133496991 (-51.6654330119472) 0xBdfecdF3bb2a93e8e105B438B67c4825dc7A1151/1 250117 0x5a194ba9e88296b998e571d29c99d8fa1c128f4f131663d881d15420aa796941
5.201 490.545853175 (51.6654330119472) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4893 151689 0x90348601450e0637f6aef895fd264b75741b30b971c537a88abae51c329686f7
5.284 490.545853175 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4893 151954 0x4c5bebdbfc6d0b42ff0c5101d722e6a68a166124e4e1aca12fc6de53e9766f5a
5.408 233.925851091 (-70.84334711015252) 0xBdfecdF3bb2a93e8e105B438B67c4825dc7A1151/1 250117 0x8edd1a10cec1182de15346bce90c7a68658aec870d14af1c78868850eba50039
5.673 10.000000000 (-183.6015740762641) 0x483871dda926d6715386441363B60EfC8A6715CB/304 173128 0x706df65f5ae5c2540bbd1b501d25904cdf1b5629a687a724b5a6ebdea0854b06
6.073 1417.677515674 (197.19824683369646) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4893 151954 0x973f0d758d6e93eaf0bf6af9923962eccb085745afe2044ca89c1bc48a0e5168
7.778 833.927950397 (-51.85185185179263) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4893 151689 0x3bb843bf7bd4e0126362144c6329759e1ff3e6382e102d65836bdb27a60a5483
8.290 30.302386815 (-185.9748562343899) 0x483871dda926d6715386441363B60EfC8A6715CB/304 173128 0x18562e780ce0e62787945170a43a7aa7d757ea927da3442e8afabb6c347d5fca
9.409 200.000000000 (147.36939163493489) 0x652C6444535f8e7d65D88Ea2E42f0660f55545D4/3 21000 0x9f1206a7e1b8a093c17fdda5e23d99ea56b1a9d6c3ded77bf726b4aa0e82a1d6
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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.