Highest Rated Maps of All Time
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#1
DJ Sharpnel - StrangeProgram
Lesjuh's TAG 7.05*
Mar 12th, 2009
Lesjuh
gimmick, storyboard, tag, complex sv
Lesjuh's TAG 7.05*
Mar 12th, 2009
Lesjuh
gimmick, storyboard, tag, complex sv
3.69 / 5.00 from 49 votes
#2
3.69 / 5.00 from 27 votes
#3
Nico Nico Douga - U.N. Owen wa Kanojo nanoka? (Nico Mega Mix)
TAG4 11.39*
May 27th, 2009
DJPop
grid snap, tag, perfect stacks
TAG4 11.39*
May 27th, 2009
DJPop
grid snap, tag, perfect stacks
2.84 / 5.00 from 24 votes
#4
IOSYS - Cirno's Perfect Math Class
TAG4 7.00*
Feb 23rd, 2011
Louis Cyphre
geometric, grid snap, symmetrical, tag
TAG4 7.00*
Feb 23rd, 2011
Louis Cyphre
geometric, grid snap, symmetrical, tag
3.10 / 5.00 from 14 votes
#5
IOSYS - Utage wa Eien ni ~SHD~
TAG4 10.40*
Sep 12th, 2009
DJPop
grid snap, tag, difficulty spike, perfect stacks
TAG4 10.40*
Sep 12th, 2009
DJPop
grid snap, tag, difficulty spike, perfect stacks
2.79 / 5.00 from 21 votes
#6
3.17 / 5.00 from 16 votes
#8
IOSYS - Marisa wa Taihen na Mono wo Nusunde Ikimashita
TAG4 13.10*
Dec 25th, 2017
DJPop
tag, difficulty spike
TAG4 13.10*
Dec 25th, 2017
DJPop
tag, difficulty spike
3.43 / 5.00 from 12 votes
#10
3.00 / 5.00 from 11 votes
#11
Hanazawa Kana - Renai Circulation (Full ver.)
TAG2 4.67*
Mar 11th, 2010
DJPop
aim control, tag, grid snap
TAG2 4.67*
Mar 11th, 2010
DJPop
aim control, tag, grid snap
3.76 / 5.00 from 8 votes
#12
lucky - Friends of Kagami
TAG4 7.74*
Apr 30th, 2025
Bloxi
grid snap, old-style revival, tag, perfect stacks
TAG4 7.74*
Apr 30th, 2025
Bloxi
grid snap, old-style revival, tag, perfect stacks
2.70 / 5.00 from 5 votes
#13
3.99 / 5.00 from 5 votes
#14
2.40 / 5.00 from 5 votes
#16
1.89 / 5.00 from 3 votes
#17
2.50 / 5.00 from 2 votes
#19
Hoshimachi Suisei - TALALALALALALALALALALALAAAAA LALAAAAAAAAAAAAA
TAG4 5.89*
Apr 15th, 2022
KecHik445
tag
TAG4 5.89*
Apr 15th, 2022
KecHik445
tag
0.83 / 5.00 from 3 votes
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Info
The chart is based on an implementation of the Bayesian average method. It updates once every day.
The next update will happen in ---
Ratings are weighed based on user rating quality, one contributing factor being their rating distribution.
Info
The chart is based on an implementation of the Bayesian average method. It updates once every day.
The next update will happen in ---
Ratings are weighed based on user rating quality, one contributing factor being their rating distribution.
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