× 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 #86 - 2018-07-16 08:25:54 to 08:26:03; Start Time 1531729554.5810163

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 21.840000000 () 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240529 0xcb32322771288aa1598a32553a1779dfd3a3c33f1f12e3017903dfe577ab6cca
1.007 62.400000002 (96.29629629875839) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240529 0x667e33a7277e430aa24ebe732ca6dc078e66abc4a43de956c8ace4ff6e7c8e56
1.027 60.000000002 (-3.9215686273228245) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0x76addb977445c26741efb9d26a7978d89f4b86ddfdc41af6d328b67f1ea97d04
1.832 62.400000002 (3.9215686273228245) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240303 0x858a31636c0ef0e16812f52100d3472aa5d65a5f5242ebefab7d405dab82c119
2.352 72.963000004 (15.606923607679782) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240303 0x5e9ef5bf5e1060439d7175e4b09552c7b7b3229bcb50ac8f449e74048c387f77
2.517 107.375097506 (38.1639797437608) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0xb2e93d868692a47729ecfe39b2a68bbadab0b61f4d2a621896b39b34f6141932
2.533 70.668000002 (-41.23394618244119) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240632 0x7ab8f529ed762365c068c6ba229b7d54c78f4311b7c7d3f5a134e964c828ec30
2.789 116.245364367 (48.76843827498844) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240632 0x1036a42b2df0215166d911458702f815811c14742c10ef80afb4067a6c3af624
2.831 72.600000004 (-46.22338971186564) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0x82971820cedd655b1abab50301c0bcc68c6ca45147834f04191b363d004ed9f5
2.921 90.635685077 (22.09772337960345) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240632 0x8630fd7b5726aa58a35f4f409b9870f4ff411697343627fa36d5477648e95023
2.991 88.739750004 (-2.1139294487496114) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0x62bedfc301c6bb899d27e8d3122106d21858dc51dcd772477dfb3d3d30776a8d
3.020 107.222828158 (18.86388546972499) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240529 0x133332ef48b28a116f996259b6fe80394019c15f4d50d9789a21a66247f1e42e
3.242 134.962067285 (22.907488987915546) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0xb9c103d8484d634eba71c999fd20950edddafd1781590fb9ff0871dee5e73174
3.252 163.304101416 (19.004524887575677) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0xd2c06ea1be1cfc245aa2469d02ba770b3a6e0c8a64e4b9bc9ee457e8d134d45b
3.287 131.647875145 (-21.465342690763812) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240632 0x69994d4459865fb97634a2b505d6ab002abf259d3b97d91fef65fa1bb542c621
3.364 80.031510002 (-48.76843827485156) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240632 0xdb44abb8b74401afa1b8a6fc04a6092e643ce90a31ca780fc3d462be0207f705
4.071 102.644913349 (24.757878364576825) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240632 0xb2badc449e034d13869f6c283677dc58938da784727f2e907fdff7f98b88c0dc
4.163 197.597962714 (63.250825871436156) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0x899496b8b930a6544182c5c614581895e6f1a8e4285bb7888af667c6ea7e4c71
4.896 239.093534885 (19.004524887317167) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0x8d8a1a3dc49cdda07079c253056078b4049e7521b390d09c6950efe2d715bb2d
5.016 289.303177212 (19.004524887271746) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0x910b1f6450ce435fb4c580557732a995491f96aee4725896bfde6e12ca7c7a2e
5.253 350.056844428 (19.0045248872968) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0xcc344d8b0b193740c4fc987607a0488e1f238891279e363798d6aceaa8968786
5.776 423.568781759 (19.00452488713986) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0xadee937f4b8f9ba3c38426f5470bfc24b572a43787c877fbc0a39e9f0792b006
6.185 512.518225929 (19.004524886995775) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0x37005f3fe51a2b47c9e0e7636c3401d51f4e203546f9c25cf90b44d2cea83099
6.315 620.147053375 (19.00452488702324) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0xf2718d748deb4adf95552bff40f4f008f6c951f71fd1d9078acbab1e55b7e629
6.345 82.630597504 (-152.96913759243785) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240303 0xc3f6aeb21d015a290b7a5895d2eeac0f973c3f5ff8ef14f8668d0c20604ee9a5
6.697 93.579151673 (12.426729190792212) 0xbB3a8c227bFBcB0fF70802Dee83246B507C57DcB/10853 240529 0x5db39a46d8fe0822323267c09c99e7bfebc96a208af4cf6e83cf2573cc312cde
6.743 750.377934585 (155.64743601458778) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0x6833eca18405a2d7c2ad1b80c58779e64cbba2814e13862ca5efa97b1f657031
8.579 825.415728044 (9.523809523869962) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/11479 457428 0xf071f438c9c786bba23e4e4ca32b2dde8fa8f316323e401ff11d633609de56e3
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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.