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Odd WCA stats/ Stats request Thread

The answer that I gave a couple posts back seemed much higher than I was expecting, and that's been bugging me for a couple of days. I went back and had a look at it, and realised that while trying to get it to run faster, I had made a stupid mistake which meant that it overcounted a lot of connections. I fixed it and took the opportunity to look into connections between competitors as well. I forgot to update the database before running it and it takes a couple hours to run, so the information is actually about a week out of date :(

Anyway, the correct answer is 5. Any competitor can be linked to any other with just 5 links.

Code: 
Distance: 0    Number of competition combinations:     3465, (  0.03 %)
Distance: 1    Number of competition combinations:   643468, (  5.36 %)
Distance: 2    Number of competition combinations:  9278754, ( 77.31 %)
Distance: 3    Number of competition combinations:  2065402, ( 17.21 %)
Distance: 4    Number of competition combinations:    15120, (  0.13 %)
Distance: 5    Number of competition combinations:       16, (  0.00 %)
Code: 
BahiaInglesaSummer2010 --> HariNgNorte2015
    (BahiaInglesaSummer2010 -- SantiagoOpen2009 -- WC2007 -- PleasantvilleFall2007 -- PhilippineOpen2013 -- HariNgNorte2015)

SanPedroDeMacoris2015 --> HariNgNorte2015
    (SanPedroDeMacoris2015 -- RepublicaDominicana2013 -- WC2007 -- PleasantvilleFall2007 -- PhilippineOpen2013 -- HariNgNorte2015)

HariNgNorte2015 --> SantoDomingoSpring2015
    (HariNgNorte2015 -- PhilippineOpen2013 -- PleasantvilleFall2007 -- WC2007 -- RepublicaDominicana2013 -- SantoDomingoSpring2015)

HariNgNorte2015 --> RDSpring2016
    (HariNgNorte2015 -- PhilippineOpen2013 -- PleasantvilleFall2007 -- WC2007 -- RepublicaDominicana2013 -- RDSpring2016)

HariNgNorte2015 --> SantoDomingoFall2016
    (HariNgNorte2015 -- PhilippineOpen2013 -- PleasantvilleFall2007 -- WC2007 -- RepublicaDominicana2013 -- SantoDomingoFall2016)

HariNgNorte2015 --> CojedesRubik2016
    (HariNgNorte2015 -- PhilippineOpen2013 -- PleasantvilleFall2007 -- USNationals2011 -- VenezuelaOpen2013 -- CojedesRubik2016)

HariNgNorte2015 --> SantiagoOpen2017
    (HariNgNorte2015 -- PhilippineOpen2013 -- PleasantvilleFall2007 -- WC2007 -- RepublicaDominicana2013 -- SantiagoOpen2017)

HariNgNorte2015 --> CapitalCube2017
    (HariNgNorte2015 -- PhilippineOpen2013 -- PleasantvilleFall2007 -- USNationals2011 -- VenezuelaOpen2013 -- CapitalCube2017)

Code: 
Maximum distance per competition
Distance: 1    Number of competitions: 0
Distance: 2    Number of competitions: 0
Distance: 3    Number of competitions: 2114
Distance: 4    Number of competitions: 1342
Distance: 5    Number of competitions: 9
Code: 
Maximum distance per competitor
Distance: 1    Number of people: 0
Distance: 2    Number of people: 107
Distance: 3    Number of people: 47226
Distance: 4    Number of people: 22537
Distance: 5    Number of people: 99
It's scary how there are so many competitors who are no more than 2 links away from every other competitor.

Code: 
Average distance from other competitions
1 .     WC2013                          Average: 1.306      Max: 3
2 .     WC2011                          Average: 1.395      Max: 3
3 .     WC2015                          Average: 1.396      Max: 3
4 .     WC2009                          Average: 1.466      Max: 3
5 .     Euro2016                        Average: 1.482      Max: 3
6 .     WC2007                          Average: 1.574      Max: 3
7 .     Euro2014                        Average: 1.59      Max: 3
8 .     Euro2012                        Average: 1.601      Max: 3
9 .     USNationals2012                 Average: 1.626      Max: 3
10 .     USNationals2014                 Average: 1.637      Max: 3
11 .     Euro2010                        Average: 1.651      Max: 3
12 .     USNationals2016                 Average: 1.682      Max: 3
13 .     USNationals2011                 Average: 1.689      Max: 3
14 .     USNationals2010                 Average: 1.689      Max: 3
15 .     FMCEurope2016                   Average: 1.691      Max: 3
16 .     FMCEurope2015                   Average: 1.709      Max: 3
17 .     USNationals2015                 Average: 1.716      Max: 3
18 .     USNationals2009                 Average: 1.718      Max: 3
19 .     AsianChampionship2016           Average: 1.718      Max: 3
20 .     Euro2008                        Average: 1.737      Max: 3
...
3446 .     TaichungPyraminx2009            Average: 2.937      Max: 4
3447 .     TunisiaSummerOpen2016           Average: 2.944      Max: 4
3448 .     KuboOpen2016                    Average: 2.944      Max: 4
3449 .     TagumCityOpen2016               Average: 2.952      Max: 4
3450 .     PrimeOneChihuahua2016           Average: 2.975      Max: 4
3451 .     SumerSpeedCubeOlympics2016      Average: 2.975      Max: 4
3452 .     SpeedcubeWeekendMerida2016      Average: 2.975      Max: 4
3453 .     PanaboSpeedcubeChallenge2017    Average: 2.975      Max: 4
3454 .     NhaTrangSummerOpen2016          Average: 2.976      Max: 4
3455 .     NLCAnniversary2016              Average: 2.982      Max: 4
3456 .     SanPedroDeMacoris2015           Average: 2.994      Max: 5
3457 .     SantoDomingoSpring2015          Average: 2.994      Max: 5
3458 .     RDSpring2016                    Average: 2.994      Max: 5
3459 .     SantoDomingoFall2016            Average: 2.994      Max: 5
3460 .     SantiagoOpen2017                Average: 2.994      Max: 5
3461 .     ChiayiPyraminx2009              Average: 3.031      Max: 4
3462 .     CojedesRubik2016                Average: 3.066      Max: 5
3463 .     CapitalCube2017                 Average: 3.066      Max: 5
3464 .     HariNgNorte2015                 Average: 3.149      Max: 5
3465 .     BahiaInglesaSummer2010          Average: 3.162      Max: 5

I worked out the average distance of each competitor from every other competitor in the database. Interestingly, there are 8 people who actually have an average distance of less than 1!
  1. Mats Valk
  2. Ron van Bruchem
  3. Sinpei Araki (荒木慎平)
  4. Kevin Hays
  5. Hanneke Rijks
  6. Fangyuan Chang (常方圆)
  7. Jong-Ho Jeong (정종호)
  8. Tomoaki Okayama (岡山友昭)
Here's a list of the top 50 and bottom 20.
Code: 
1.    2007VALK01  Average: 0.957    Distribution: [5915, 61181, 2873, 0, 0, 0]
2.    2003BRUC01  Average: 0.962    Distribution: [5271, 62076, 2622, 0, 0, 0]
3.    2006ARAK01  Average: 0.975    Distribution: [4686, 62341, 2942, 0, 0, 0]
4.    2009HAYS01  Average: 0.977    Distribution: [4938, 61671, 3360, 0, 0, 0]
5.    2008RIJK01  Average: 0.981    Distribution: [4305, 62717, 2947, 0, 0, 0]
6.    2009CHAN04  Average: 0.984    Distribution: [5262, 60557, 4150, 0, 0, 0]
7.    2008JONG03  Average: 0.99    Distribution: [4075, 62500, 3394, 0, 0, 0]
8.    2009OKAY01  Average: 0.992    Distribution: [3429, 63652, 2888, 0, 0, 0]
9.    2004CHAN04  Average: 1.002    Distribution: [5114, 59577, 5278, 0, 0, 0]
10.    2009ZEMD01  Average: 1.002    Distribution: [3902, 62000, 4067, 0, 0, 0]
11.    2005REYN01  Average: 1.003    Distribution: [5317, 59131, 5521, 0, 0, 0]
12.    2010CANT02  Average: 1.006    Distribution: [4508, 60567, 4894, 0, 0, 0]
13.    2005FLEI01  Average: 1.009    Distribution: [5067, 59237, 5665, 0, 0, 0]
14.    2008CHOI04  Average: 1.011    Distribution: [4245, 60679, 5045, 0, 0, 0]
15.    2005KOCZ01  Average: 1.012    Distribution: [4866, 59401, 5702, 0, 0, 0]
16.    2008SEAR01  Average: 1.016    Distribution: [5283, 58265, 6421, 0, 0, 0]
17.    2008AURO01  Average: 1.018    Distribution: [4499, 59723, 5747, 0, 0, 0]
18.    2008COUR01  Average: 1.018    Distribution: [4682, 59315, 5972, 0, 0, 0]
19.    2006KRUE01  Average: 1.023    Distribution: [4919, 58518, 6526, 6, 0, 0]
20.    2007VALL01  Average: 1.027    Distribution: [4253, 59606, 6110, 0, 0, 0]
21.    2008VIRO01  Average: 1.035    Distribution: [4115, 59311, 6543, 0, 0, 0]
22.    2003VAND01  Average: 1.035    Distribution: [3646, 60249, 6074, 0, 0, 0]
23.    2012BERG04  Average: 1.035    Distribution: [3338, 60837, 5794, 0, 0, 0]
24.    2012SOHO01  Average: 1.035    Distribution: [2887, 61725, 5357, 0, 0, 0]
25.    2012CANT01  Average: 1.036    Distribution: [3189, 61088, 5683, 9, 0, 0]
26.    2003HARD01  Average: 1.038    Distribution: [2632, 62071, 5266, 0, 0, 0]
27.    2009PLES01  Average: 1.04    Distribution: [3504, 60157, 6308, 0, 0, 0]
28.    2006GARR01  Average: 1.04    Distribution: [4377, 58404, 7188, 0, 0, 0]
29.    2007HASH01  Average: 1.04    Distribution: [3796, 59550, 6623, 0, 0, 0]
30.    2003LEEJ01  Average: 1.046    Distribution: [2803, 61119, 6047, 0, 0, 0]
31.    2007GOUL01  Average: 1.048    Distribution: [3991, 58658, 7311, 9, 0, 0]
32.    2005STIL01  Average: 1.048    Distribution: [2693, 61229, 6047, 0, 0, 0]
33.    2009SHEP01  Average: 1.048    Distribution: [3065, 60477, 6427, 0, 0, 0]
34.    2010HEIL02  Average: 1.05    Distribution: [3138, 60167, 6664, 0, 0, 0]
35.    2008ANDE02  Average: 1.052    Distribution: [2873, 60608, 6488, 0, 0, 0]
36.    2009ZHAN53  Average: 1.055    Distribution: [4001, 58159, 7803, 6, 0, 0]
37.    2012MCNE01  Average: 1.058    Distribution: [3120, 59651, 7198, 0, 0, 0]
38.    2010DESJ01  Average: 1.059    Distribution: [2736, 60353, 6880, 0, 0, 0]
39.    2009OHRN01  Average: 1.06    Distribution: [3358, 59030, 7572, 9, 0, 0]
40.    2010BENT01  Average: 1.065    Distribution: [3491, 58436, 8033, 9, 0, 0]
41.    2007LUCH02  Average: 1.067    Distribution: [3713, 57821, 8435, 0, 0, 0]
42.    2012ARTH01  Average: 1.071    Distribution: [3323, 58384, 8262, 0, 0, 0]
43.    2010KIPA01  Average: 1.072    Distribution: [3351, 58240, 8378, 0, 0, 0]
44.    2006GALE01  Average: 1.072    Distribution: [3786, 57335, 8848, 0, 0, 0]
45.    2010MALL01  Average: 1.075    Distribution: [3563, 57627, 8779, 0, 0, 0]
46.    2009INGE01  Average: 1.075    Distribution: [1793, 61162, 7014, 0, 0, 0]
47.    2004KRIG01  Average: 1.075    Distribution: [2863, 59010, 8087, 9, 0, 0]
48.    2007HESS01  Average: 1.075    Distribution: [4625, 55464, 9880, 0, 0, 0]
49.    2009YAUR01  Average: 1.079    Distribution: [2722, 58990, 8248, 9, 0, 0]
50.    2011HAYS02  Average: 1.079    Distribution: [1911, 60593, 7465, 0, 0, 0]
...
69950.    2017BUST03  Average: 3.032    Distribution: [40, 324, 5682, 55274, 8640, 9]
69951.    2017SILV06  Average: 3.032    Distribution: [40, 324, 5682, 55274, 8640, 9]
69952.    2017VELA03  Average: 3.032    Distribution: [40, 324, 5682, 55274, 8640, 9]
69953.    2017PARE02  Average: 3.032    Distribution: [40, 324, 5682, 55274, 8640, 9]
69954.    2016GILA03  Average: 3.032    Distribution: [14, 350, 5682, 55274, 8640, 9]
69955.    2015SORI02  Average: 3.05    Distribution: [38, 335, 4985, 55418, 9103, 90]
69956.    2015LUMA01  Average: 3.05    Distribution: [38, 335, 4985, 55418, 9103, 90]
69957.    2015DRAP01  Average: 3.05    Distribution: [38, 335, 4985, 55418, 9103, 90]
69958.    2015ARAG01  Average: 3.05    Distribution: [38, 335, 4985, 55418, 9103, 90]
69959.    2015MULD01  Average: 3.05    Distribution: [38, 335, 4985, 55418, 9103, 90]
69960.    2015BARR05  Average: 3.05    Distribution: [38, 335, 4985, 55418, 9103, 90]
69961.    2015CONT01  Average: 3.05    Distribution: [38, 335, 4985, 55418, 9103, 90]
69962.    2015LOPE10  Average: 3.05    Distribution: [38, 335, 4985, 55418, 9103, 90]
69963.    2015MANO01  Average: 3.05    Distribution: [38, 335, 4985, 55418, 9103, 90]
69964.    2010OREL01  Average: 3.122    Distribution: [13, 199, 4355, 52076, 13317, 9]
69965.    2010SERR01  Average: 3.122    Distribution: [13, 199, 4355, 52076, 13317, 9]
69966.    2010MUNO01  Average: 3.122    Distribution: [13, 199, 4355, 52076, 13317, 9]
69967.    2010VERG01  Average: 3.122    Distribution: [13, 199, 4355, 52076, 13317, 9]
69968.    2010VERG02  Average: 3.122    Distribution: [13, 199, 4355, 52076, 13317, 9]
69969.    2010LABB01  Average: 3.122    Distribution: [13, 199, 4355, 52076, 13317, 9]

I also thought it would be interesting to see how many people various competitors have competed with. Ming Zheng has competed with 7220 unique competitors! That's more than 10% of the people in the WCA database!

Here's the top 50 and bottom 20:
Code: 
1.    2009ZHEN11  Average: 1.23    Distribution: [7220, 39520, 23121, 108, 0, 0]
2.    2007VALK01  Average: 0.957    Distribution: [5915, 61181, 2873, 0, 0, 0]
3.    2005REYN01  Average: 1.003    Distribution: [5317, 59131, 5521, 0, 0, 0]
4.    2008SEAR01  Average: 1.016    Distribution: [5283, 58265, 6421, 0, 0, 0]
5.    2003BRUC01  Average: 0.962    Distribution: [5271, 62076, 2622, 0, 0, 0]
6.    2009CHAN04  Average: 0.984    Distribution: [5262, 60557, 4150, 0, 0, 0]
7.    2004CHAN04  Average: 1.002    Distribution: [5114, 59577, 5278, 0, 0, 0]
8.    2005FLEI01  Average: 1.009    Distribution: [5067, 59237, 5665, 0, 0, 0]
9.    2009HAYS01  Average: 0.977    Distribution: [4938, 61671, 3360, 0, 0, 0]
10.    2006KRUE01  Average: 1.023    Distribution: [4919, 58518, 6526, 6, 0, 0]
11.    2005KOCZ01  Average: 1.012    Distribution: [4866, 59401, 5702, 0, 0, 0]
12.    2006ARAK01  Average: 0.975    Distribution: [4686, 62341, 2942, 0, 0, 0]
13.    2008COUR01  Average: 1.018    Distribution: [4682, 59315, 5972, 0, 0, 0]
14.    2007HESS01  Average: 1.075    Distribution: [4625, 55464, 9880, 0, 0, 0]
15.    2010CANT02  Average: 1.006    Distribution: [4508, 60567, 4894, 0, 0, 0]
16.    2008AURO01  Average: 1.018    Distribution: [4499, 59723, 5747, 0, 0, 0]
17.    2006GARR01  Average: 1.04    Distribution: [4377, 58404, 7188, 0, 0, 0]
18.    2003BURT01  Average: 1.131    Distribution: [4361, 52153, 13410, 45, 0, 0]
19.    2008RIJK01  Average: 0.981    Distribution: [4305, 62717, 2947, 0, 0, 0]
20.    2009HILD01  Average: 1.125    Distribution: [4254, 52707, 13002, 6, 0, 0]
21.    2007VALL01  Average: 1.027    Distribution: [4253, 59606, 6110, 0, 0, 0]
22.    2008CHOI04  Average: 1.011    Distribution: [4245, 60679, 5045, 0, 0, 0]
23.    2008DONG06  Average: 1.327    Distribution: [4204, 38815, 26829, 121, 0, 0]
24.    2011SAKO01  Average: 1.156    Distribution: [4130, 50873, 14915, 51, 0, 0]
25.    2008VIRO01  Average: 1.035    Distribution: [4115, 59311, 6543, 0, 0, 0]
26.    2011DWYE02  Average: 1.148    Distribution: [4115, 51439, 14364, 51, 0, 0]
27.    2008JONG03  Average: 0.99    Distribution: [4075, 62500, 3394, 0, 0, 0]
28.    2008CLEM01  Average: 1.148    Distribution: [4029, 51581, 14308, 51, 0, 0]
29.    2009ZHAN53  Average: 1.055    Distribution: [4001, 58159, 7803, 6, 0, 0]
30.    2007GOUL01  Average: 1.048    Distribution: [3991, 58658, 7311, 9, 0, 0]
31.    2008JEWR01  Average: 1.157    Distribution: [3983, 51076, 14859, 51, 0, 0]
32.    2005CAMP01  Average: 1.122    Distribution: [3956, 53551, 12462, 0, 0, 0]
33.    2011BANS02  Average: 1.087    Distribution: [3915, 56071, 9983, 0, 0, 0]
34.    2009ZEMD01  Average: 1.002    Distribution: [3902, 62000, 4067, 0, 0, 0]
35.    2010BURN01  Average: 1.091    Distribution: [3863, 55878, 10222, 6, 0, 0]
36.    2010WANG53  Average: 1.255    Distribution: [3858, 44561, 21429, 121, 0, 0]
37.    2008LIKA01  Average: 1.174    Distribution: [3825, 50221, 15833, 90, 0, 0]
38.    2007HASH01  Average: 1.04    Distribution: [3796, 59550, 6623, 0, 0, 0]
39.    2006GALE01  Average: 1.072    Distribution: [3786, 57335, 8848, 0, 0, 0]
40.    2007OEYM01  Average: 1.1    Distribution: [3781, 55407, 10781, 0, 0, 0]
41.    2009LIDO01  Average: 1.395    Distribution: [3734, 35040, 31003, 192, 0, 0]
42.    2009DIEC01  Average: 1.115    Distribution: [3723, 54452, 11794, 0, 0, 0]
43.    2003LARS01  Average: 1.086    Distribution: [3722, 56518, 9729, 0, 0, 0]
44.    2007LUCH02  Average: 1.067    Distribution: [3713, 57821, 8435, 0, 0, 0]
45.    2009OLSO01  Average: 1.162    Distribution: [3675, 51272, 15016, 6, 0, 0]
46.    2003VAND01  Average: 1.035    Distribution: [3646, 60249, 6074, 0, 0, 0]
47.    2008BARA01  Average: 1.127    Distribution: [3643, 53806, 12520, 0, 0, 0]
48.    2010THOM03  Average: 1.156    Distribution: [3642, 51778, 14543, 6, 0, 0]
49.    2012DELI01  Average: 1.153    Distribution: [3609, 52128, 14181, 51, 0, 0]
50.    2010MALL01  Average: 1.075    Distribution: [3563, 57627, 8779, 0, 0, 0]
...
69950.    2012LUKA01  Average: 1.958    Distribution: [9, 5563, 61775, 2622, 0, 0]
69951.    2012ALFA02  Average: 1.958    Distribution: [9, 5563, 61775, 2622, 0, 0]
69952.    2012BARG01  Average: 1.958    Distribution: [9, 5563, 61775, 2622, 0, 0]
69953.    2015MORA07  Average: 2.126    Distribution: [9, 2035, 57089, 10827, 9, 0]
69954.    2005WASS01  Average: 2.53    Distribution: [9, 504, 32226, 36863, 367, 0]
69955.    2015ARIA03  Average: 2.126    Distribution: [9, 2035, 57089, 10827, 9, 0]
69956.    2005JOHA01  Average: 2.53    Distribution: [9, 504, 32226, 36863, 367, 0]
69957.    2013CRON02  Average: 2.014    Distribution: [9, 4679, 59574, 5707, 0, 0]
69958.    2012DOOF01  Average: 1.958    Distribution: [9, 5563, 61775, 2622, 0, 0]
69959.    2013AHAD01  Average: 2.287    Distribution: [9, 2214, 45550, 22106, 90, 0]
69960.    2012EIDR01  Average: 1.958    Distribution: [9, 5563, 61775, 2622, 0, 0]
69961.    2005ERIC01  Average: 2.53    Distribution: [9, 504, 32226, 36863, 367, 0]
69962.    2013BRIC01  Average: 2.014    Distribution: [9, 4679, 59574, 5707, 0, 0]
69963.    2010GJOS01  Average: 2.171    Distribution: [9, 2259, 53438, 14257, 6, 0]
69964.    2013ASRI01  Average: 2.287    Distribution: [9, 2214, 45550, 22106, 90, 0]
69965.    2012ISSI01  Average: 1.958    Distribution: [9, 5563, 61775, 2622, 0, 0]
69966.    2016MONZ01  Average: 1.96    Distribution: [6, 5435, 61906, 2622, 0, 0]
69967.    2016MONZ02  Average: 1.96    Distribution: [6, 5435, 61906, 2622, 0, 0]
69968.    2016GONZ10  Average: 1.96    Distribution: [6, 5435, 61906, 2622, 0, 0]
69969.    2016VALD03  Average: 1.96    Distribution: [6, 5435, 61906, 2622, 0, 0]

And finally, the embarrassingly ugly Python code I used.
 
AlphaSheep said:
I worked out the average distance of each competitor from every other competitor in the database. Interestingly, there are 8 people who actually have an average distance of less than 1!
Click to expand...
I'm not sure how you're working out the difference (and this might just be an off-by-one error in your code), but the usual approach is to consider two people connected by a link if they have competed at the same competition, then to get the distance between two people you count how many links you need to traverse to get from one to the other. That means the distance between two people should always be at least 1, which means the average distance from any given person to every other person must also be at least 1.
 
bobthegiraffemonkey said:
I'm not sure how you're working out the difference (and this might just be an off-by-one error in your code), but the usual approach is to consider two people connected by a link if they have competed at the same competition, then to get the distance between two people you count how many links you need to traverse to get from one to the other. That means the distance between two people should always be at least 1, which means the average distance from any given person to every other person must also be at least 1.
Click to expand...
I started off thinking in terms of competitions, so two competitions are a distance of 1 apart if at least one competitor went to both competitions. When I started looking at competitors, I just carried that over without giving it too much thought, so I treated two competitors as at a distance 1 apart if the competitions they've been to were 1 apart... So I landed up treating the distance between two competitors as 0 if they've been to a competition together.

And yes, to get to the usual definition of distance, it's as simple as adding one to each distance.
 
Since registration is now full for the World Championships, here's the count of how many competitors there are from each country:

Code: 
+------------------+-------+
| country          | count |
+------------------+-------+
| France           |   174 |
| United States    |    92 |
| Germany          |    68 |
| United Kingdom   |    64 |
| Spain            |    64 |
| China            |    57 |
| Netherlands      |    37 |
| Sweden           |    34 |
| Poland           |    30 |
| India            |    26 |
| Switzerland      |    22 |
| Denmark          |    21 |
| Japan            |    21 |
| Belgium          |    20 |
| Hungary          |    18 |
| Norway           |    17 |
| Canada           |    16 |
| Finland          |    16 |
| Italy            |    16 |
| Australia        |    12 |
| Russia           |    11 |
| Colombia         |    10 |
| Mongolia         |     9 |
| Brazil           |     8 |
| Ukraine          |     8 |
| Taiwan           |     7 |
| Malaysia         |     7 |
| Korea            |     6 |
| Mexico           |     6 |
| New Zealand      |     6 |
| Tunisia          |     6 |
| Algeria          |     6 |
| Argentina        |     5 |
| Chile            |     5 |
| Hong Kong        |     5 |
| Estonia          |     5 |
| Peru             |     4 |
| Slovenia         |     4 |
| Philippines      |     4 |
| Ireland          |     4 |
| Austria          |     4 |
| Croatia          |     3 |
| Belarus          |     3 |
| Czech Republic   |     3 |
| Indonesia        |     3 |
| Latvia           |     3 |
| Israel           |     3 |
| Romania          |     3 |
| Slovakia         |     3 |
| Bahrain          |     2 |
| Greece           |     2 |
| Singapore        |     2 |
| Uruguay          |     2 |
| Jordan           |     2 |
| Andorra          |     1 |
| Mauritius        |     1 |
| Guatemala        |     1 |
| Jamaica          |     1 |
| Kuwait           |     1 |
| Serbia           |     1 |
| French Polynesia |     1 |
| Nigeria          |     1 |
| Suriname         |     1 |
| Montenegro       |     1 |
| Venezuela        |     1 |
+------------------+-------+
 
3x3 average percentiles in seconds
0: 525.07
1: 145.70
2: 120.87
3: 107.44
4: 99.18
5: 93.08
6: 88.09
7: 83.90
8: 80.47
9: 77.20
10: 74.32
11: 71.73
12: 69.47
13: 67.40
14: 65.30
15: 63.29
16: 61.37
17: 59.68
18: 58.11
19: 56.61
20: 55.16 [1st quintile]
21: 53.77
22: 52.52
23: 51.31
24: 50.22
25: 49.15 [1st quartile]
26: 48.11
27: 47.07
28: 46.07
29: 45.09
30: 44.24
31: 43.33
32: 42.44
33: 41.58
(33⅓: 41.33) [1st tertile]
34: 40.80
35: 40.03
36: 39.25
37: 38.52
38: 37.80
39: 37.07
40: 36.37 [2nd quintile]
41: 35.71
42: 35.06
43: 34.46
44: 33.85
45: 33.22
46: 32.64
47: 32.06
48: 31.51
49: 30.99
50: 30.46 [median]
51: 29.92
52: 29.40
53: 28.90
54: 28.41
55: 27.93
56: 27.47
57: 27.01
58: 26.57
59: 26.14
60: 25.70 [3rd quintile]
61: 25.31
62: 24.88
63: 24.49
64: 24.10
65: 23.70
66: 23.33
(66⅔: 23.07) [2nd tertile]
67: 22.96
68: 22.58
69: 22.22
70: 21.86
71: 21.49
72: 21.11
73: 20.75
74: 20.41
75: 20.08 [3rd quartile]
76: 19.74
77: 19.38
78: 19.04
79: 18.71
80: 18.38 [4th quintile]
81: 18.04
82: 17.70
83: 17.37
84: 17.04
85: 16.71
86: 16.38
87: 16.06
88: 15.69
89: 15.34
90: 14.97
91: 14.60
92: 14.23
93: 13.84
94: 13.41
95: 12.92
96: 12.43
97: 11.90
98: 11.17
99: 10.19

The derivative is completely wacky. It starts out really low, going from 4 to 5 is a drop of 6.10. At the median, going from 49 to 50, it's much lower, at 0.53. It keeps going down after that, and is lowest from 86 to 87, at just 0.32. However, by 98 to 99, it drops 0.98, a large increase.
 
Torch said:
Anyone know if this is the tie between the most people?
Click to expand...

For first place in a final, yes. The most people tying for first place before this, in any event, was 4, also for FMC, at the CCC End of Summer 2015 competition. There have been 3 people tied for first place in FMC 11 times, and there have been 2 people tied for first place lots of times in FMC, and a few times in 2x2 (but not in a final), magic, 3x3, 3BLD and MBLD.
 
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