[Serie Zed]

I've heard rumors that part of this is already done, and am hoping I can piggy back on it...

I'd love to do a simple regression that looks at average FIFA rankings over the last X years vs population, per-capita GDP and some measure of overall social health in countries with a domestic league.

I just looked at the population numbers solo and I have a feeling the fit would be exceptionally strong.

[Serie Zed]

Talk about a waste of time. (Serious) stat boys...help me out.

I ran FIFA points (used to determine rankings) vs population in millions and per capita GDP and got squadoosh.

GDP is actually correlated, but only has an adjusted R squared of .12 or so. Population doesn't explain anything. At all.

Unless I'm doing something bass-ackward of course.

Also...

I added a field based on a metric that rates the strength of a country's institutions (basically "rule of law" and "lack of corruption"). Rank ordered 1, 2, 3 etc from good to bad.

My problem is that there's a positive correlation! (Which seems to suggest that the worse a country's institutions the better its football team, on average).

Argh

[ChrisE]

If I remember correctly, Voros had done this, and probably the most important part was that it was only used inside federations (UEFA, CONCACAF, etc.).

[mpruitt]

http://www.bigsoccer.com/forum/showt...threadid=78472

[voros]

Originally posted by ChrisE
If I remember correctly, Voros had done this, and probably the most important part was that it was only used inside federations (UEFA, CONCACAF, etc.).

Actually I used "dummy" variables for the Confeds. If a country was in a particular confed it got a "1" otherwise it got a "0" each of the confeds got a different coefficient except for OFC (you'll trash your Matrices if you use all the confeds for reason's I won't go into)

I didn't use FIFA's rankings but I used my own that I had been working on.

I've since redone my rankings to be a better, so I probably need to re-do the study.

Anyway the variables were: Confed, Total GDP, and GDP per capita. Using just these three I got an R of .82 and an adjusted R-Squared of .66.

The new system uses the Bradley-Terry method suggested by someone in another thread, but is modified a bunch of ways to apply to individual game scores.

It also uses a solving algorithm to find the competition multipliers that best fit the source data, feeds those back into the system, gets new ratings, redo the solving algorithm, and repeat the process until the numbers stabilize. Those multiples were tested against an independent data sample, and slightly adjusted based on those results and common sense.

So friendlies now count in the ratings, and it has a simple yet powerful method of predicting game results (FINALLY prohbitive favorites don't have too high of chances of being upset). Turks & Caicos probably doesn't want to know what it says Haiti is going to do them. The biggest shock is that American Samoa is NOT the worst ranked team. (Though they share something in common with the worst ranked team, other than lots of double digit losses).

[Serie Zed]

Thanks Voros. Since I've got pop and p/c GDP it will be easy to get to total GDP without looking up again.

[Serie Zed]

I'm guessing that your rankings must be pretty different than FIFA's?

I'm only doing the top 100, but running your variables v FIFA points still doesn't give a whole lot. Though it's better than the ones I started with.

[voros]

Originally posted by Serie Zed
I'm guessing that your rankings must be pretty different than FIFA's?

I'm only doing the top 100, but running your variables v FIFA points still doesn't give a whole lot. Though it's better than the ones I started with.

When I get a chance, I'll run the ones I'm using against FIFA's and see what I get.

Also, it might also help to take the natural log of the population rather than just the population.

I've ran them against my new rating system, and now the R is all the way up to around .85. 8 of the top 9 teams in my rankings, were also in the top 9 when projecting using GDP, Population and Confed (the USA didn't make the top 9 in the rankings, but did in the projections, and the Czech Republic did make the top 9 of the rankings but not the projections).

My next step is to add in a variable for how many years it has been since they played their first international match, and see if that's worth anything.

[NoSix]

Originally posted by voros

My next step is to add in a variable for how many years it has been since they played their first international match, and see if that's worth anything.

I'm wondering if the number of years since the founding of a domestic professional league would be more relevant. At least in the case of the US and Japan, their international standing changed dramatically after the founding of MLS and the J-league, respectively. The US played their first friendlies back in the 19th century.

[Serie Zed]

I was thinking of some other measures that kind of get at the same thing...some not very practical...

Total salary of national team players?
Average attendance at top flight matches?
Number of continental champion's league trophies lifted by domestic league?
Domestic players sold for more than $x in last x years?