× 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 #536 - 2018-09-17 12:32:08 to 12:32:13; Start Time 1537187528.8315408

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 240.372559510 () 0x7E77777772d74Cba60638F3C19C60A3387172a06/4189 183828 0xda4801317c59afee4f2f88de4c0f72da9207a20e15de3bdb68592ba26d306273
0.310 263.618950325 (9.224913658807687) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 210465 0x30d964c64c02da6371f891f47426fddae5bbc563419707175d6c419dd7316617
0.499 271.620992246 (2.990076518789897) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4189 213832 0x10104926d224cb26f719a65babfe4f70c26173abf829fbd1140e5a8bf76ff7e1
0.530 249.987461890 (-8.29493087562551) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 225523 0x5656d16204caa95015f74bcf345a4fbbc6e255007f406d7b5adc2c05675afda6
0.716 448.152215552 (56.76937153553004) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 210465 0x7ce0e8fb650f46d59b56223bb806b167f2293f47a17bc04e0f3abd91d8b37daf
0.729 425.828642583 (-5.108480983585061) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4189 213832 0xdbcac16812881d645b7ca77fac083e6c510b17815db59c6aeb01ca4e7c1ea9f5
0.820 761.858766438 (56.5856169397277) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 210465 0x2766a5564f3dc7af523933e044359a4b372585f7ee0161cd4fa00b6b6b583905
0.861 481.186366118 (-45.15884306515404) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4189 213832 0x3e0af3d7124f9fa215e45fcba563f9fb3b8f94081b44ddd57180b3744859ba7e
0.981 763.382483970 (45.348414084451285) 0x7E77777772d74Cba60638F3C19C60A3387172a06/4189 213832 0x62493b1201beb4a804f7b75b078d3961b0a6b4e02dba24a0e2d5e2780b6206ce
1.024 722.463764862 (-5.507799900584001) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 225494 0xec3ec4fba01560b7a3cb8a2942a280e3afaeca0b109a4aeb039b5e80f8779ad1
1.075 1295.159902944 (56.76937153545191) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 210465 0x3e8444e27e717486f68f384ac0461325d66102be20408cd14d6142d607afa6d6
1.232 249.987461890 (-135.28449969770827) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 225494 0x0dcb73cbc9a6bb76a89b10630c9c1a1b2eb3bd22f4e92c571fb79b40414ffe6d
1.455 424.978685213 (51.85185185185185) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 225494 0x3bd6f4d23e154bc9857cd7cf03948966abb8c0c8f37345fe108217a61f0b7d05
1.752 1228.188400265 (97.17223650382059) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 225523 0x675fa643c9eae20a1d5788c5bb62d150d8296888e0a521a998b3347e60e84075 6348306 6348306 / 0
4.709 793.917783328 (-42.95230591356601) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 210442 0xacad925a1e7be5e43d98a781c230216450739422d7e07362576ed9a0b309f42d
5.021 1228.188400265 (42.95230591356601) 0xAa24325B9d108492fB5D8b8583e1705986d70E04/4700 225494 0xb0742501710db1fc48ed6a3740edcef55e7d927c177e29bf7244a954ca035def
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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.