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Best sub leaderboard

What if every single team had chosen their best sub for final scoring?
This LB is based on that scenario.
Team name Public(final) Private(final) Private(best) Public score Private score Date
pampampampam (ooc) 1 1 1 0.8068291470136629 0.8072498120356044 2014-01-03
Dataiku Data Science Studio ○○○○ 2 2 2 0.8064671675625773 0.807143936199658 2014-01-10
LR 3 3 3 0.8057349046207614 0.8063612793012775 2014-01-10
learner 4 4 4 0.8043807927928421 0.8047584598626383 2014-01-08
DenXX 5 5 5 0.8037816768193204 0.804259480149285 2014-01-10
YS-L 6 6 6 0.8033393772668782 0.8039083194706002 2014-01-10
lucky guy 8 7 7 0.8027789424497155 0.8032207675970221 2014-01-10
Gábor S 7 8 8 0.8027929681774963 0.8032037999854065 2014-01-10
Vermillion Team 3 ○○○○○ 9 9 9 0.8025006145801551 0.8028983721851307 2014-01-10
Ruslan Mavlyutov (ooc) 10 10 10 0.8014805644829772 0.801916492538498 2014-01-10
Bazingaaa ○○ 11 11 11 0.8010973179053555 0.8016302800836241 2014-01-08
E. G. Ortiz-García 12 12 12 0.8004379002849628 0.8008093252979495 2013-11-22
Anton Kochnev 13 13 13 0.8001748317130148 0.8007310813950455 2014-01-10
blue_maple 14 14 14 0.7996793306544733 0.8000764560445975 2013-12-22
DB2(walt) 15 15 15 0.7995640594195782 0.8000723485597403 2014-01-09
camcamcam ○○ 16 16 16 0.7993277032149332 0.7997191950193425 2014-01-07
AIMORE 17 17 17 0.7991407069737342 0.7996188162870927 2013-12-15
Martin Martin 18 18 18 0.7988680290429819 0.7994129653546795 2014-01-05
DerivedByData 19 19 19 0.7986342665367321 0.7991669958023646 2014-01-10
Montblanc 20 20 20 0.7984759309214906 0.7989151436273468 2014-01-09
arnav 22 21 21 0.7982692143668831 0.7988083047432354 2014-01-10
James King 21 22 22 0.7983603689083818 0.7987232854616253 2014-01-08
gaddawin 24 23 23 0.7980536238793465 0.7984775642194026 2013-12-19
Chun-Hao Chang 23 24 24 0.7980615468946989 0.7984125103486961 2014-01-10
Richard Hughes 25 25 25 0.7978614351587001 0.7983969947204137 2014-01-08
yi zhan 26 26 26 0.797484625573228 0.7979830946603427 2014-01-06
DuckTile 28 27 27 0.7973497507568599 0.7978797896518325 2014-01-10
bart 27 28 28 0.7974261823857594 0.7978612939307388 2013-12-05
Yu Xu ○○ 29 29 29 0.7973019684909038 0.7978581433001619 2014-01-10
mathintelligence 31 30 30 0.7972015894242833 0.797622735831265 2014-01-02
orchid 30 31 31 0.7972192299650027 0.7976164916384589 2014-01-10
Waterloo ○○ 35 32 32 0.7967827023124762 0.7973323570532216 2014-01-10
Vogue Merry ○○○ 33 33 33 0.7968470707197481 0.7973309747806253 2014-01-10
Panda ○○○○○ 32 34 34 0.7969466827285414 0.7973002602782245 2014-01-10
Fellows 34 35 35 0.7968072442340323 0.7972918170904383 2014-01-09
Fluttershy 36 36 36 0.7967097823868484 0.7972429017926914 2013-11-04
flyer 38 37 37 0.7966377223543027 0.7972311932576388 2014-01-10
Viandox ○○○○ 37 38 38 0.7967056502581399 0.7972022318761199 2014-01-10
Luca Massaron 40 39 39 0.7964914010162173 0.7970085451347521 2014-01-10
Wei Yuan 39 40 40 0.7965528263103171 0.7969624019132779 2013-12-20
Alberto Bosko Boschetti 41 41 41 0.7964285578660943 0.7969183908444233 2014-01-05
Quentin Jerome 43 42 42 0.7963806761465257 0.7969034753155054 2013-12-23
Alexandru Stanciu 42 43 43 0.7964191318343333 0.7968859212424577 2014-01-10
shantou_datamining ○○○ 44 44 44 0.7962937319252749 0.7967799438374915 2014-01-10
vbs 0711 46 45 45 0.7962009256247891 0.7967363549124375 2013-12-25
loser 47 46 46 0.7961281920477574 0.7966745942241366 2013-12-26
Joao Palotti 45 47 47 0.7962040013515923 0.7966378661191214 2014-01-04
radium 50 48 48 0.7960489538001999 0.7965379981576485 2013-11-25
VASAPTEX 49 49 49 0.7960727302519778 0.7965030553672224 2014-01-08
IDEAS ○○○○ 51 50 50 0.7959534303650344 0.7964911914723733 2014-01-10
Kinnskogr & Miroslaw ○○ 48 51 51 0.7960896581445395 0.7964887741314833 2014-01-09
Silogram 52 52 52 0.7956943480992535 0.7964702369578329 2013-12-05