This has probably answered somewhere in this thread, but:
What's the average for 3x3 calculated from ALL people that competed? So the average of ~25000(?) people? And this for the other events aswell :)

Would ne quite interesting for me, thanks in advance :D
 
This has probably answered somewhere in this thread, but:
What's the average for 3x3 calculated from ALL people that competed? So the average of ~25000(?) people? And this for the other events aswell :)

Would ne quite interesting for me, thanks in advance :D
Already had a script for this (will add other events later)

Code:
┌──────────────────────────────────────────────────────────────────────────
│ 2015-11-18 @ 18:30:40
├──────────────────────────────────────────────────────────────────────────
│ Event: Rubik's Cube (333)
│ Year : ALL
├──────────────────────────────────────────────────────────────────────────
│ Total solves: 1072611
│ Total good  : 1044184
│ Total DNF   :  27394
│ Total DNS   :   1033
│ Total sub10 :  29246
│ Global mean :  26.19
│ Total competitors: 44858
 
RankCompIDNumber of Competitors
1SCMUJuhuOpen2015189
2FMCEurope2015176
3BeijingSummerOpen2009162
4ShenYangOpen2011154
5SuzhouOpen2014153
6SanFranciscoOpen2009150
7BeijingMetropolisOpen2009149
GuangdongOpen2008149
9KrakowCubingSpree2014147
ShenyangOpen2014147
SLSJastrzebie2013147
12PantheonCubeOpen2014139
TorontoOpenSpring2015139
14SLSBielskoBiala2014136
SLSTarnowskieGory2014136
16LibertyScience2013134
17RedCrossCubingOpen2014131
18NorwichSummer2015129
19BUAAOpen2010127
20IETEC2015124
MITSpring2015124
22DoylestownSpring2015123
23RiverHillWinter2015122
24France2012121
Indiana2014121
26TaiwanSummer2012120
27DuanwuFestivalOpen2009119
JoanaDArcOpen2014119
29TokyoOpen2006118
30GuangzhouCCSA2013116
TorontoOpenWinter2013116
32BayAreaSpeedcubin42014115
KCAKoreaOpen2008115
PragyanOpen2011115
35GeniusKidIndiaOpen2014113
GuangzhouNewYear2015113
37BerkeleyFall2014111
SLSCzestochowa2013111
ZhengzhouOpen2015111
40CanadianCubingFifty2014110
MITFall2014110
42BerkeleySpring2014108
CaltechFall2013108
NationalTPolyOpen2014108
NiseiWeek2015108
46TorontoWinter2011107
47FECAPOpen2015106
PragyanOpen2012106
49ShantouOpen2015105
SPCSStanfordSpring2015105
TorontoOpenWinter2015105
52Atlanta2015104
UTNOtono2015104
54BeijingSpringOpen2009103
LexingtonSpring2015103
56CaltechWinter2007102
HarbinOpen2009102
58IGARubik2014101
LawrenceSpring2015101
ShanghaiWeisuoOpen2009101
TorontoOpenSpring2014101
UtahMegacomp2015101
63BerkeleySummer2015100
PrincetonWinter2014100
RiverHillSummer2014100
TorontoFall2010100
TorontoWinter2010100
68Germany200999
PuneFallOpen201599
70PrincetonFall201098
ShenzhenOpen201598
72HarvardFall201497
NanjingNormalUniveristy201397
SLSSwierklany201397
TaiwanWinterOpen200997
TorontoOpenFall201497
77NanjingSpring201296
78Indiana201295
Indiana201395
TaiwanSummer201095
81ChangChun201094
GLSSummer201394
HarbinOpen201494
JapanOpen200794
Johannesburg201494
NanjingOpen200994
NewarkWinter200994
88BASC7201593
BeijingSummer201493
BerkeleySpring201593
DneprCubeDay201493
ICTOpen201593
NanjingSpringOpen201093
ParaxCubecomp201593
RoseCity201593
TorontoSummer201093
97CaltechWinter201492
KharkivSpecial201592
PolishOpen200892
RybnikOpen201392

Code:
results = read.csv("WCA_export_Results.tsv", sep="\t", encoding="UTF-8")
competitions = read.csv("WCA_export_Competitions.tsv", sep="\t", encoding="UTF-8")

oneday = as.character(competitions$id[competitions$day == competitions$endDay])

numComp = function(comp) {
  dump = results$personName[results$competitionId == comp]
  return(length(unique(dump)))
}


num = sapply(oneday, numComp) #long wait

output = as.data.frame(cbind(oneday, num))
output = output[order(-num),]
write.csv(output, "OneDayComps.csv")

For those asking about largest one day comps. Originally posted September 24th.
 
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