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bubbagrub

Member
Joined
Sep 22, 2013
Messages
406
Location
UK
WCA
2013COPP01
This guy

View attachment 7871

SELECT * FROM rankssingle WHERE personID IN(SELECT personID FROM ranksaverage WHERE eventID = '333' and best > 2999) AND eventID = '333fm' ORDER BY best ASC

That guy does have a sub-30 average in FMC...

I think you need to replace '333' by '333fm' in your query... :)

Edit: and I'm not sure if your query will include people that have no average in FMC at all, will it?
 

sam596

Member
Joined
Jan 1, 2012
Messages
89
Location
Lincs, UK
WCA
2015SPEN01
YouTube
Visit Channel
That guy does have a sub-30 average in FMC...

I think you need to replace '333' by '333fm' in your query... :)

Edit: and I'm not sure if your query will include people that have no average in FMC at all, will it?

I was assuming the question meant sub-30 3x3, since the answer to the sub-30 fmc mean is kinda obvious.
 

mycube

Member
Joined
Sep 3, 2011
Messages
1,019
Location
Regensburg, Germany
WCA
2011FRES01
Here you go:
[td]NameCompsAverage solvesTotal solves
1 Jesser Armando Ramírez Diaz 2 103.5000 207
2 Henri Gerber 17 100.7059 1712
3 Pavel Galaktionov 23 95.1739 2189
4 Robert Yau 57 93.8947 5352
5 Kevin Gerhardt 21 93.2857 1959
6 Bence Barát 108 92.7593 10018
7 Dorian Stein 4 92.7500 371
8 Callum Hales-Jepp 43 92.6744 3985
9 César Abraham Briones Arreola 6 92.1667 553
10 Stephano Saucedo Reyes 13 91.0000 1183
11 Vladislav Kaminskiy 23 90.3913 2079
12 Lucas Wesche 25 90.3600 2259
13 Vladyslav Zhydkov (????????? ??????) 4 90.2500 361
14 Oliver Fritz 17 89.7059 1525
15 Ivan Zabrodin 45 89.0000 4005
16 Alexis Rodrigo Cazu Mendoza 12 88.4167 1061
17 Jure Gregorc 26 88.1154 2291
18 Simon Westlund 34 87.8235 2986
19 Fabio Schwandt 16 87.4375 1399
20 Shivam Bansal 38 87.1053 3310
21 Pavel Yushkevich 23 86.3913 1987
22 Matic Omulec 40 86.2250 3449
23 Rok Glinšek 14 86.2143 1207
24 Alexey Modenov 1 86.0000 86
25 Hunor Bózsing 62 85.8226 5321
26 Vladislav Ushakov 12 85.7500 1029
27 Francisco Alberto Castañeda Lima 9 85.5556 770
28 Staš Zupanc 14 85.5000 1197
29 Victor Rafael Ortiz Villaseñor 9 85.3333 768
30 Artem Yashkov 14 85.2857 1194
31 Carlos Macias Valadez 6 85.1667 511
32 Aldo José Gramajo de León 6 85.0000 510
33 Jakob Gunnarsson 10 84.6000 846
34 Nikita Bespalov 4 84.5000 338
35 Alexey Zharikov 10 84.4000 844
36 Kari Hyttinen 7 84.2857 590
37 Ben Whitmore 26 84.1154 2187
38 Antonio López 12 84.0833 1009
39 Wilhelm Kilders 43 83.9767 3611
40 Oleg Martynov 12 83.5000 1002
41 Pablo Say 17 83.2353 1415
42 Ciarán Beahan 22 83.0000 1826
43 Jan Bentlage 116 82.9310 9620
44 Laura Holzhauer 7 82.8571 580
45 Nathan Liang 1 82.0000 82
46 Kunal Oak 13 81.9231 1065
47 Luboš Bartík 13 81.7692 1063
48 Alberto Pérez de Rada Fiol 38 81.5789 3100
49 Róbert Maróti 14 81.5000 1141
50 Mattia Furlan 17 81.2353 1381
[/td] [td]

[/td]
[td]
[/td]
[td][/td]
 

sneze2r

Member
Joined
Nov 30, 2012
Messages
162
Location
Rumia, Poland
WCA
2012JALO01
YouTube
Visit Channel
Just fun country rank stats:

x% perc.- x% percentile of average result per person per event. I.e if for country xyz event abc there is 100 persons, then 1% perc.= mean of 10th person in this country rank
x% mean.- mean of the top x% averages per country per event
best.10.mean- most imprtant i think- mean of 10 best averages per country per event

All stats from ranksAverage table

eventId country 1% perc. 5% perc. 1% top mean. 5% top mean. best.10.mean
333 USA 9.98 13.12 8.95 11.19 7.24
333 Germany 9.28 11.60 8.13 10.03 7.95
333 Korea 9.09 11.63 8.07 10.02 8.07
333 China 10.63 12.79 9.57 11.41 8.12
333 Canada 10.34 13.27 9.15 11.49 8.30
333 Poland 9.47 12.18 8.80 10.52 8.44
333 Russia 9.62 12.35 8.86 10.67 8.75
333 Japan 9.34 11.76 8.85 10.42 8.80
333 Taiwan 9.62 11.86 8.71 10.31 8.80
333 France 9.80 12.65 8.99 10.99 8.85
444 USA 35.46 44.43 32.89 39.11 30.46
444 China 36.50 42.45 33.13 38.33 32.16
444 Germany 33.34 40.92 30.69 35.87 33.18
444 Japan 33.26 40.03 31.79 35.28 34.17
444 Korea 34.65 42.17 30.17 36.68 34.32
444 Taiwan 33.79 38.74 30.86 35.36 34.39
444 Canada 33.56 44.16 30.56 37.37 34.72
444 Poland 34.61 41.36 32.47 37.85 35.10
444 Indonesia 37.16 45.41 32.55 39.63 35.52
444 Russia 35.42 42.93 34.42 38.07 36.42
555 USA 67.24 79.14 60.84 71.79 60.29
555 Taiwan 60.61 70.19 53.94 63.24 64.78
555 China 68.47 76.96 64.31 71.25 65.15
555 Germany 65.63 73.91 57.78 67.94 66.39
555 Japan 63.80 72.42 61.18 65.76 67.04
555 Indonesia 65.35 77.22 57.82 68.25 68.97
555 Canada 64.73 78.11 60.15 67.56 69.37
555 Korea 64.03 79.96 54.83 66.85 69.57
555 Russia 68.92 79.40 61.81 70.57 71.45
555 France 71.43 77.56 58.82 70.35 72.04
 
Last edited:

CJK

Member
Joined
Nov 11, 2015
Messages
61
WCA
2015KOEN01
Just fun country rank stats:

x% perc.- x% percentile of average result per person per event. I.e if for country xyz event abc there is 100 persons, then 1% perc.= mean of 10th person in this country rank
x% mean.- mean of the top x% averages per country per event
best.10.mean- most imprtant i think- mean of 10 best averages per country per event

All stats from ranksAverage table

eventId country 1% perc. 5% perc. 1% top mean. 5% top mean. best.10.mean
333 Australia 1052 1253 910.36 1109.62 896.60
333 Germany 928 1160 817.75 1003.59 798.60
333 Netherlands 1007 1262 805.00 1076.16 968.20
333 Korea 909 1163 807.50 1001.80 807.50
333 USA 1001 1315 899.91 1124.60 729.60
333 Canada 1034 1327 914.92 1148.72 830.20
333 Poland 947 1218 879.95 1052.25 843.50
333 United Kingdom 962 1217 852.67 1047.47 896.10
333 France 980 1267 899.31 1103.07 885.70
333 Taiwan 962 1186 871.33 1031.13 880.40
444 USA 3554 4459 3280.68 3919.18 3048.00
444 Germany 3334 4092 3122.25 3605.25 3339.00
444 Australia 3360 4526 2923.00 3838.18 3770.30
444 Netherlands 3345 4573 2654.00 3825.43 4097.50
444 Korea 3465 4217 3016.67 3674.19 3442.90
444 Canada 3356 4416 3055.67 3736.87 3472.20
444 Spain 3880 4646 3271.00 3980.83 3773.80
444 Taiwan 3379 3874 3086.50 3535.86 3438.90
444 France 3656 4243 3282.67 3857.94 3696.30
444 China 3654 4280 3369.53 3848.58 3270.60
555 Australia 6892 8096 4932.00 6887.20 7728.90
555 USA 6730 7970 6116.00 7187.04 6055.20
555 Taiwan 6061 7019 5394.00 6324.00 6478.30
555 Germany 6563 7391 5778.00 6794.54 6639.00
555 Korea 6403 7996 5483.00 6684.75 6956.90
555 Netherlands 7009 8205 5579.00 6671.33 8338.10
555 United Kingdom 6251 7728 5756.00 6773.80 7390.40
555 Indonesia 6535 7722 5782.00 6825.44 6908.30
555 France 7143 7756 5882.00 7035.25 7204.40
555 Thailand 5939 7190 5939.00 5939.00 7915.90

Can someone explain me how this is sorted?
 

Lid

Member
Joined
Jul 8, 2008
Messages
906
Location
Sweden
WCA
2008LIDS01
Lowest 5x5/4x4 ratio? 4x4/3x3?
Singles btw.

top10 for 4x4/3x3
Code:
--wcaID--	444	333	ratio	name, country
2015MALY01	1:22.48	56,81	1,45	Aleksandr Malygin, m, Russia
2015BANS04	47,56	28,22	1,69	Alankar Bansal, m, India
2010LIYA01	52,9	29,63	1,79	Yalong Li (李亚隆), m, China
2013KESH01	3:23.03	1:31.76	2,21	Ketan Keshri, m, India
2017SCHL02	1:19.94	35,26	2,27	Heinz Schlatter, m, Switzerland
2012MARQ02	1:36.14	41,68	2,31	Gabriel Campos Marques, m, Brazil
2011LIUA02	1:12.91	30,84	2,36	Yiqi Liu (刘奕祺), m, China
2012ZHUS01	1:17.43	32,07	2,41	Shengnan Zhu (祝胜男), f, China
2007XING01	3:05.30	1:16.09	2,44	Xinghui Zhao (赵星辉), m, China
2013KARI01	27,81	10,91	2,55	Jithin Prakash, m, India
top12 for 5x5/4x4 = all with faster 5x5 than 4x4
Code:
--wcaID--	555	444	ratio	name, country
2011TELA01	3:13.71	9:09.13	0,35	Julio Martín Gómez Telésforo, m, Mexico
2015POMA01	2:28.72	5:16.73	0,47	Abhinav Pomalapally, m, USA
2012MAGA01	1:51.44	3:37.09	0,51	Kelvin Maganes, m, Philippines
2009SHIN02	1:49.96	3:06.36	0,59	Forte Shinko, m, Canada
2013PITE01	2:22.57	3:12.84	0,74	Przemysław Piątek, m, Poland
2010AILE01	4:42.15	5:45.25	0,82	Alexx Ailes, m, USA
2012XULI02	1:29.07	1:43.72	0,86	Linqi Xu (徐琳淇), m, China
2011YAHI01	2:28.34	2:45.80	0,89	Vahid Mohammad Yahia (وحید محمد یحیی), m, Iran
2009GOMB01	2:00.68	2:07.71	0,94	Daniel Gömböš, m, Slovenia
2015GROB02	2:20.69	2:28.15	0,95	Ruben Grobler, m, South Africa
2015RICH13	1:40.28	1:44.30	0,96	Benjamin Richler, m, Canada
2009MOTT01	2:19.71	2:20.18	0,997	Eduardo Lins Motta, m, Brazil
 
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