Conquer Club

Took the top 1,000 ranked players and divided total score by total games played for each country represented in the top 1,000.

This provides a comparable country ranking that minimizes the low player count bias. The ratio still gets skewed if you have a low player count so I segmented the results to countries with more than 5 ranked players and countries with less than 5 ranked players.

Overall best country: Bulgaria. Bulgarians (or rather the Bulgarian) earn, on average, 59 points for every game they play.

Best country with 5 or more ranked players: Portugal. Portuguese earn an average of 11 points for every game they play.

Overall worst country: Malta. The two players from Malta earn an average of 3 points per game they pay.

Worst country with 5 or more ranked players: Netherlands. The Dutch earn an average of 4 points per game they play.

Results:
More than 5 Ranked Players
Country / # of players / (Total Score/Total games played)
Average / 943 / 4.99
Portugal / 6 / 10.87
Belgium / 9 / 9.68
Finland / 6 / 9.37
Denmark / 9 / 9.28
Serbia / 5 / 8.37
Spain / 5 / 7.95
Ireland / 7 / 7.84
Thailand / 7 / 7.78
Switzerland / 8 / 7.16
Turkey / 7 / 6.90
Croatia / 10 / 6.86
Japan / 7 / 6.79
Sweden / 21 / 6.61
Singapore / 14 / 6.14
Germany / 17 / 6.01
Israel / 10 / 5.84
Canada / 106 / 5.13
France / 16 / 4.90
Australia / 24 / 4.67
US / 499 / 4.66
UK / 95 / 4.38
Norway / 8 / 3.92
Netherlands / 47 / 3.80

Less than 5 Ranked Players
Country / # of players / (Total Score/Total games played)
Bulgaria / 1 / 59.38
Iran, / 1 / 45.98
Poland / 2 / 23.21
Nigeria / 1 / 23.17
Bosnia / 1 / 20.00
Russian / 4 / 19.77
Mexico / 2 / 17.41
Morocco / 1 / 17.28
Europe / 1 / 13.92
New Zealand / 2 / 13.22
UAE / 1 / 10.48
Italy / 2 / 10.22
Hong Kong / 4 / 10.19
Lithuania / 2 / 10.09
China / 2 / 9.50
Jordan / 1 / 9.05
Romania / 4 / 8.98
Malaysia / 4 / 8.91
Colombia / 1 / 7.96
Brazil / 3 / 7.07
Ecuador / 3 / 6.88
Greece / 4 / 6.35
South Africa / 1 / 5.14
South Korea / 2 / 4.96
Egypt / 1 / 3.97
Lebanon / 2 / 3.51
Bahrain / 2 / 3.31
Malta / 2 / 2.78

nice idea. impressed you did it.

but still.. the number of games played per points doesnt tell anything..

(of course it can say something at some points..)


But take my self for an example... when i had 3000 points and 200 games... I was not better then compered to now.. Even if my points per game ration is much much worse now

Yeah, its about the best ratio I could build with data from the Scoreboard. The ratio options are:
1. average wins/games played by country
2. total points/games played by country
3. total wins/games played by country
4. total points/games won by country

The only ratios that made sense are total points/games won and total points/games played. Its better than nothing.

Probably a better way to portray the results is how efficient is each country at CC, that is really what the ratio is telling us.

I agree with Juve there! this must've taken you ages... but it proves not much... i really am sorry to say that.

so Juve what formula would give the most accurate result?

Hari's level of dedication should be used for something more telling i reckon.

Took 20 minutes. Copy/paste to excel and a pivot table.

If you deduct from each player the 1000 points that everybody is given (not won) then the figures will be far more accurate;

joecoolfrog wrote:If you deduct from each player the 1000 points that everybody is given (not won) then the figures will be far more accurate;

If I did that then I would probably change the ratio to total score/games won.

That ratio would better capture performance when playing against more difficult opponents.

Harijan wrote:

joecoolfrog wrote:If you deduct from each player the 1000 points that everybody is given (not won) then the figures will be far more accurate;

If I did that then I would probably change the ratio to total score/games won.

That ratio would better capture performance when playing against more difficult opponents.

You should completely forget games won because team/1 v1/3 player games compared with 5/6 player games would make the numbers meaningless. By using your current method and simply deducting the 1000 points ,the bias in favour of those who have played fewer games will be lessened quite a bit.

Most of those countries don't have a large enough sample size for a survey.

TChao wrote:Most of those countries don't have a large enough sample size for a survey.

That is why I shifted the sample unit from player count to games played. With the sample unit set to games played i only need 400-500 games for 95-99% assurance statements. If I wanted to change the sample unit to player count I would need to expand the population to probably the top 5,000 players which would cause all kinds of other problems.

On an interesting side note, of the almost 1 million games played on CC, the top 1,000 ranked players have participated in approximately 390,000 of them. The only bias in that stat is that I cannot control for multiple top 1,000 players at the same game. The actual number could be as low as 300,000 which is still pretty impressive.

great...just great

joecoolfrog wrote:

Harijan wrote:

joecoolfrog wrote:If you deduct from each player the 1000 points that everybody is given (not won) then the figures will be far more accurate;

If I did that then I would probably change the ratio to total score/games won.

That ratio would better capture performance when playing against more difficult opponents.

You should completely forget games won because team/1 v1/3 player games compared with 5/6 player games would make the numbers meaningless. By using your current method and simply deducting the 1000 points ,the bias in favour of those who have played fewer games will be lessened quite a bit.

Maybe we can solve that problem by dividing by the win ratio somewhere, someone who's played lots of doubles and triples and has a win ratio of 0.8 would thus be "penalized" against people who stick to singles but don't get over a win rate of 0.3-0.4

I like the idea, but I can't figure out how to do it without more data. I would need to know what % of games played were singles, doubles or triples.

I think using score gets around this idea because the points gained is not influenced by the game type. For example, if you win a triple with 6 players you get the same amount of points as if you won a single against a player with the same average score as your triples opponents.

MeDeFe wrote:

joecoolfrog wrote:

Harijan wrote:

joecoolfrog wrote:If you deduct from each player the 1000 points that everybody is given (not won) then the figures will be far more accurate;

If I did that then I would probably change the ratio to total score/games won.

That ratio would better capture performance when playing against more difficult opponents.

You should completely forget games won because team/1 v1/3 player games compared with 5/6 player games would make the numbers meaningless. By using your current method and simply deducting the 1000 points ,the bias in favour of those who have played fewer games will be lessened quite a bit.

Maybe we can solve that problem by dividing by the win ratio somewhere, someone who's played lots of doubles and triples and has a win ratio of 0.8 would thus be "penalized" against people who stick to singles but don't get over a win rate of 0.3-0.4

Even if you did that you would still need to distinguish between 2 3 4 5 6 player games and then to distinguish calibre of opponent - all of which are reflected in your score which is why its the obvious point to work from. Again I will note that deducting the 1000 point start from the already collected data will render it far more accurate and probably as close a guide as we will ever get.

Pretty cool . . . an interesting stat might be the total winning percentage for all games played
by country.

I hope u will update those scores often

oVo wrote:Pretty cool . . . an interesting stat might be the total winning percentage for all games played
by country.

Why !
All you will get is a list of who plays the most 1 v1 instead of more competetive games