× 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 #661 - 2018-09-26 22:35:32 to 22:35:39; Start Time 1538001332.8513901

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 107.325341180 () 0x41880a6C0BF00b0C159a8154d66B676a995D2383/17952 300000 0x72e99138fbc0f210199acefa095ffe6e24d825bb505cc56396b1bf2d81407e0c
0.374 604.208984806 (139.66540347507467) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4773 254093 0xa6c984be7351c0a7b9bea0e53fc369df9f6e5b26cc22e9f8e530d6b18b59b2db
0.414 604.208984806 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4773 254520 0xac257b69335f99b660cd7920cfa7ce5d7a2df98e29f3fd5ae0d5553460b63a70
0.428 604.208984806 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4773 254087 0x42b3569199f11c44cca1c493703f189e9bebf78c42bce1d6b9af02f407c23f22
0.584 656.496300799 (8.294930875602354) 0x0000bAA8F700aF2476492b19e378d61b90454982/240 143404 0x9ab43205096e804eafe0f8014e5cca7d29f66d70f4d5155c9d53f72a55cf3824
0.806 1027.155274170 (44.03036576945259) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4773 254520 0xbab49e1952461f0a153aa657e098db3487c67fccb1a6cb65ee5e23fb771fbab5
1.102 1027.155274170 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4773 254093 0x744d2ac5e5d169a55ef4cede028ef6361a6a7e38b615a11b947a07da22498846 6405539 6405539 / 0
3.444 604.208984806 (-51.851851851833686) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4773 254193 0xa0b3843efab51f2df0af32d496cb1ea7aaefbf4b48411fa2a7d800333b553bd5
4.973 1027.155274170 (51.851851851833686) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4773 254087 0x8751dc019e03b48f86f496939f77cca010e0c14a41fb628d30642b84a7de516e
7.118 1027.155274170 (0.0) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4773 254193 0xbe77eb6d5ff9e04c1bf7d82adbd54283e1479c80d46346bd0910f3968f2a2ca5
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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.