Highest Rated Maps of 2013
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#402
3.84 / 5.00 from 5 votes
#405
Hikasa Yoko - Listen!!
Collab 5.34*
Jun 22nd, 2013
Lilac, Lybydose, Derekku, Shohei Ohtani, Lunah, Cristian and Lizzehb
grid snap, symmetrical, collab
Collab 5.34*
Jun 22nd, 2013
Lilac, Lybydose, Derekku, Shohei Ohtani, Lunah, Cristian and Lizzehb
grid snap, symmetrical, collab
3.14 / 5.00 from 4 votes
#409
3.24 / 5.00 from 6 votes
#411
3.22 / 5.00 from 5 votes
#412
2.56 / 5.00 from 7 votes
#414
3.09 / 5.00 from 4 votes
#415
Natsuiro Bikini no Prim - Nagisa no Koakuma Lovely~Radio
Extreme 5.88*
Aug 7th, 2013
CSY the corrupt
download unavailable
Extreme 5.88*
Aug 7th, 2013
CSY the corrupt
download unavailable
3.69 / 5.00 from 5 votes
#417
3.67 / 5.00 from 5 votes
#418
3.69 / 5.00 from 4 votes
#422
Makishima Yuki, Yoshikawa Yukako & Fujita Saki - Kiseki no Kakera
D.N.Angel 4.86*
Jan 31st, 2013
DarknessAngel
D.N.Angel 4.86*
Jan 31st, 2013
DarknessAngel
3.75 / 5.00 from 4 votes
#425
3.00 / 5.00 from 4 votes
#427
3.30 / 5.00 from 5 votes
#430
4.33 / 5.00 from 3 votes
#432
3.08 / 5.00 from 5 votes
#433
3.44 / 5.00 from 5 votes
#434
3.01 / 5.00 from 5 votes
#435
3.48 / 5.00 from 5 votes
#436
Various Artists - Square Jump Practice Maps
Rockefeller Street BPM162.5 Holy... 6.03*
Aug 23rd, 2013
Jemmmmy
Rockefeller Street BPM162.5 Holy... 6.03*
Aug 23rd, 2013
Jemmmmy
2.54 / 5.00 from 8 votes
#437
4.16 / 5.00 from 3 votes
#438
Kotera Kanako - Sora wo Miagete Ending version
Kiseki 3.00*
Jul 26th, 2013
jonathanlfj
simple, marathon, storyboard
Kiseki 3.00*
Jul 26th, 2013
jonathanlfj
simple, marathon, storyboard
3.37 / 5.00 from 5 votes
#439
3.63 / 5.00 from 4 votes
#441
4.00 / 5.00 from 3 votes
#443
3.71 / 5.00 from 4 votes
#445
3.32 / 5.00 from 5 votes
#446
2.86 / 5.00 from 4 votes
#447
3.98 / 5.00 from 5 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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