osu!catch world cup 2023 | round of 16 statistics

	C	D	F	G	H	I	J	K	L	M	N	P
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3	CWC 2023 Round of 16 - Team Perf. Scores
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5		#	team	pscore ▼	maps	w-l	avg. score	avg. acc	highest score			notes
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7	★	#1	South Korea	1.673	7	6-1	2,948,822	99.84%		HD1	3,030,875	- performance score takes into account relative scores per map - star (★) = match won
8	★	#2	Philippines	1.552	6	6-0	2,942,574	99.72%		NM2	2,987,589
9	★	#3	Canada	1.531	6	6-0	2,892,804	99.68%		HR3	3,000,000
10	★	#4	Italy	1.492	8	6-2	2,881,521	99.76%		HR3	2,963,488
11	★	#5	United States	1.473	9	6-3	2,889,220	99.23%		HR1	2,986,855
12	★	#6	Chile	1.432	7	6-1	2,899,243	99.73%		NM2	3,000,028
13	★	#7	Indonesia	1.358	6	6-0	2,896,384	99.72%		NM1	2,975,858
14		#8	Germany	1.348	8	2-6	2,837,746	99.62%		HD1	2,972,569
15	★	#9	Mexico	1.291	7	6-1	2,871,967	99.58%		NM2	2,987,310
16	★	#10	Poland	1.238	8	6-2	2,828,265	99.53%		HD1	3,009,905
17		#11	Finland	1.182	9	3-6	2,801,241	99.42%		DT1	2,970,842
18		#12	Taiwan	1.169	8	2-6	2,807,598	99.54%		NM2	2,943,511
19		#13	Russian Federation	1.167	6	0-6	2,824,034	99.49%		HD1	2,898,135
20	★	#14	Belgium	1.134	6	6-0	2,805,539	99.46%		NM1	2,989,572
21	★	#15	France	1.113	6	6-0	2,788,826	99.36%		NM1	3,006,904
22		#16	Australia	1.039	7	1-6	2,765,654	99.36%		NM2	2,849,597
23		#17	Norway	0.966	7	1-6	2,735,240	99.35%		NM1	2,981,352
24	★	#18	Japan	0.918	7	6-1	2,704,150	99.11%		DT3	2,783,246
25	★	#19	Denmark	0.909	11	6-5	2,698,017	99.27%		NM1	2,982,992
26		#20	Netherlands	0.897	7	1-6	2,727,431	99.33%		NM2	2,868,954
27	★	#21	Sweden	0.880	8	6-2	2,668,671	98.97%		DT2	2,840,567
28	★	#22	Vietnam	0.867	7	6-1	2,697,779	99.07%		NM1	2,972,210
29		#23	Peru	0.861	6	0-6	2,692,096	98.97%		NM1	2,881,617
30		#24	Colombia	0.809	11	5-6	2,660,813	99.15%		NM1	2,846,418
31		#25	Spain	0.778	7	1-6	2,624,457	98.69%		NM4	2,919,939
32		#26	China	0.749	8	2-6	2,611,148	98.78%		NM2	2,812,651
33	★	#27	United Kingdom	0.746	11	6-5	2,636,655	99.05%		NM2	2,875,564
34		#28	Thailand	0.710	7	1-6	2,588,588	98.82%		DT1	2,844,969
35		#29	Brazil	0.695	11	5-6	2,608,234	98.96%		NM1	2,878,586
36		#30	Argentina	0.616	6	0-6	2,454,374	97.77%		NM2	2,774,060
37		#31	Hong Kong	0.485	6	0-6	2,480,811	98.45%		NM1	2,794,627
38		#32	New Zealand	0.439	6	0-6	2,412,290	98.18%		NM1	2,875,675
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