× 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 #453 - 2018-09-12 09:58:09 to 09:58:20; Start Time 1536746289.5549285

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 8.000000001 () 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x4b311f928f82aa6275bde9ce2b24cc544923c1318d775fa487c919be83e92660
0.234 14.645561854 (58.691958234921884) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0x1171e82642c3c27d52c0bb25ddfc45dd067f7d94687f10983bad0ca0d17c0275
2.647 14.645561855 (6.828007077739661e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x05f75aa4796503692946cb264d701759f68c838ed73741e11ac21e69763aa04d
2.856 17.721129845 (19.004524889394244) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0x6cd5b7f885b97dc4fb4516b389d395c4499dfede30987df6264ce327f23a7845
3.196 17.721129846 (5.642981055488029e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0xb0fb678153ce233d3c38688b4613aa6e8a1b180fcf3f4189a217546edb2a3e06
3.396 21.442567114 (19.004524888449144) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0x4d8829d4209f87f73518ad70e1cf6a8d1bd24e01460efdb67cd01c56d2a987d8
3.814 21.442567115 (4.6636207067006215e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x617f09bae7eaf4ccbbf1dd4573ac349147feea2cea349479bdc0c3d7b9967be4
4.023 25.945506209 (19.004524886304914) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0x488966766b184db2c9bfe336f34c165c501f6764ef60ddaaa7343e2cc0b1d45e
4.297 25.945506210 (3.854231988866912e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x000c0dd38680f970bd0e49e28c2ac5afc54916a27ddb48b0f379daafedacbaec
4.574 31.394062514 (19.004524886562173) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0x8d1d1702578c9677fe3b79b22ca94fe185c34f3bf2f609e3fc1b67566ff5c65a
4.822 31.394062515 (3.18531569317647e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x68a9e24c2853e8026a739be6f2440aa529bd0273b03d7a5b285fce1a728d4163
5.118 37.986815643 (19.00452488648652) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0xfb8770f357f5f6c1c7a94a159f4f8e4668a7e005d1c8ebd6ee7a3f465afc6f64
5.392 37.986815644 (2.6324923083441242e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x9d97bf220a710abf8f505ac0e3d1678dd0071d0910a56ff745c08929a5188b27
5.542 45.964046929 (19.004524886360397) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0xb3315f8fbc3ea9ffdd4e33b728ceb59527fcf725dfe22a7c256d541564a81637
5.684 45.964046930 (2.1756134779294076e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x691917db2358fb722d5a7ee98eb41c0934237c3c3f6c5fca5d523363efb65bcc
5.960 55.616496785 (19.00452488634329) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0x0f5ed61bafc314f6b8b78f407ae4035fdb1287b790117b7ffcdeb6d735f55ccc
6.102 55.616496786 (1.7980276676842293e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x1ccc596653945223d3b19bc177c9640ea54e82eb811e69113832a6a4131ce339
6.366 67.295961111 (19.004524886789476) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0xe22a438e45abd0929bc4af57fbcd78747387fab41afea990b085891e03c4215e
6.449 67.295961112 (1.4859732790548007e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0xb0f9a1ef9754b3ff299f6c5762a145bf9889859c4d4dfc7ce91779115c5fdf46
6.781 81.428112946 (19.004524887461983) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0xcf102c6f841f17475864dd6277015c0da8828d206f3f445a60bcfba56e579d07
6.853 81.428112947 (1.2280770901040298e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0xc79ba029470b7ae785892b30cbd4aa14d329b36a77b6e41d8d32b01de650d007
7.118 98.528016666 (19.00452488700858) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0x46f48d00707f3ced6cde059f730989fecdd61019632434424c8070dd04d60b79
7.267 98.528016667 (1.0149397438749062e-09) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0xd2d4d266038c69833e75b95db953833941999494af6d9f09eb1571eee8067289
7.533 119.218900167 (19.00452488681964) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0xc5160962509e6c99b04379375a777985457b7eb4d1a922e68e5e975c425436a1
7.713 119.218900168 (8.387931767488388e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x74981b8ab16f529825699302d88ac2cdaaa3210a93aba71b42673a9b5218fced
7.965 144.254869203 (19.00452488668548) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0xa05d048a67c1866597ebb9fc603be63483469f8fd2f2fc7dd79ee649dd50a673
8.205 144.254869204 (6.932175014413568e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x513dd617d283926fd694aa593c97a30db2dfaa0ce2d9e377c4b6cf05edb08ee2
8.531 174.548391737 (19.004524886968667) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0xf3e9ee54aff09fee30b2125c806c1b77c59c2d3378f1a66c4dda539965acf8f6
8.708 174.548391738 (5.729070259804405e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x508cb3d30a7c2496760190d006310056be3ba3e93f876d168e68f0364a1d682f
9.124 211.203554003 (19.00452488688721) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0x7178dbc77e82853321745a31c553b086503c5cc8985e7312fa8c178527d57cea
9.320 211.203554004 (4.734768809730485e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x902e45821cceea85474d22b2ee7b903a90747f02387cfa0eb93caddee191e818
9.878 255.556300345 (19.004524886939873) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0xa317bf7bf19a6503b1ddaf6e7331363115726f7ead1c13be66ac0181c441d8af
10.183 255.556300346 (3.9130320741380566e-10) 0x55aE3f67039c332F55bE00c1d33D989d2DA108C5/13605 311090 0x779fddee2bb51911ead715ca929e726fd9f410769910a395f0b56b7ffe6f3429
10.446 309.223123419 (19.004524886986786) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/12547 307268 0x83dd4aa800b6c51d79f32b8eca7b1413fa080b5d9cb3f3d216100eb5cc7b9d04
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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.