× 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 #861 - 2018-10-10 03:47:54 to 03:47:56; Start Time 1539143274.2075117

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 21.841000000 () 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 176829 0x2f86e12197de8bd7fe0a60cca2e301728d5c4ada48cafe501c2dc5903e6d35c9
0.308 21.841000001 (4.578544938313755e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0xacc1de8662a36afcfeedf9ee63c08843c3ee07bf5895c741376fbf56fe7ef5be
0.430 24.680330000 (12.206572765391561) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0xf1c634f1cbd9ee1f71231087a2c6a171898f0e23e28d280c38a65407891398de
0.617 27.888772900 (12.206572769953052) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0x8d8ce45a005791ed36a91576d79d5ed104491e22474d40af4eb951cac1a36653
0.617 27.148363002 (-2.6905829522756624) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0x3674fb557efde5f4659d1889ad7049df262dc33dbab1b484eb1c5854635bc56d
0.782 32.915218272 (19.20250224072578) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0x47da720ca03a5fa74b05da6ab45a90aaa6fbc28ef75903d36458ca7fd395f1d3
0.827 32.849519234 (-0.1998001983783665) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0xc2d23a6ddb11a8114f0dca1756c68a292dc7e3f02fdb96c7e25939f819dc48a2
0.899 39.827414110 (19.20250223814947) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0xbf81c165eb569de037a874f60c0d66e003fb32e3fed674abab04100b8a0def31
1.082 48.191171075 (19.00452489078486) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0xa0dc1221540e96a67cdff675d6c4a0e2287c6e3c8ca59d94b6db38987aa8d098
1.104 39.747918274 (-19.202502239912068) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0xdad5584e38688e09fc714a9685baf19b36f497492ec744b65d7dcf645d0cd677
1.186 48.094981113 (19.004524889886078) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0x5d60798ea1cbf5456c4a14a88799dd48ace2d7a213284d1744e641fa2cb38c07
1.307 58.311317002 (19.202502239028295) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0xf73c4dde4bef1fcd39750a6f2b48a298a60ee3ab9006e8923c7a09a25ccde0cd
1.498 70.556693573 (19.00452488769244) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0x0a452756a9f21e14ce03ae7c18a48b016771570ab57d5d88ec571a8f46f81af0
1.694 70.415861850 (-0.1998001988080908) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0x9d85c84d6c5306048ced652008ef96256e51826247d1807b71c4f1c9a1321dac
1.695 85.373599225 (19.202502238324147) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0x0406520ad70262038e8bbb84b3f6c2ffb87c73bf55eae3d2c8510b85fe9e77af
1.931 103.302055064 (19.004524888556592) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0x121d493da5d1a4b598c42087d30887708cfdb6bb0a5c0cecbd5225e4c15235a8
2.114 124.995486629 (19.004524888114606) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0x0d971b870d8c005613e82365c04ed2b3b314f9a78e7e57361e2b9d8e09de69c2
2.123 85.203192840 (-37.86160207050068) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0xa5633879d06f71f6827ade6bb7e1ba0c70d152bf89cc9d63cc5838c2dfc40869
2.179 103.095863338 (19.00452488841577) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0xb6df6cc8ccfd3968c1075f5f895921b35e297831e1af3367981f232a9d2751eb
2.290 141.244899890 (31.226092648652532) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/909 207223 0x5abc653046cba1b4777a26e70280f868a089967c1d0e48749ee66cdfa0318885 6486649 6486649 / 0
2.314 124.745994640 (-12.405616575073518) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0x30d7bf79bba52c13c99735e09e0574559fa6b6c07c459867fd0dd1d33f322a20
2.465 58.194927148 (-72.7568953316222) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0x5cd9fceca77165308b7e1c2b39917368770b08217355b2d879317a3706fc73ad
2.677 137.220594105 (80.87962148583611) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13083 347815 0x34d448d0940ce284e479d33f850bbbe7934514a4f4c092b580f5cd2e012f09e5
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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.