3.4 Combining methods
[...] are now compared with regard to their predictive performance.
For this purpose, we apply the following general procedure:
1. Form a training data set containing three out of four World Cups.
2. Fit each of the methods to the training data.
3. Predict the left-out World Cup using each of the prediction methods.
4. Iterate steps 1-3 such that each World Cup is once the left-out one.
5. Compare predicted and real outcomes for all prediction methods.
I'm sure an accurate model has to be updated as culture and technology changes and impacts the game itself.
Take a look at robust regression and influence functions to see some of the interesting flavor of one way to look at outlier weirdness.
After playing a little with it, my takeaway was that the FIFA index is worthless (too political?) so I'd not pay attention to it. Also, the ESPN index was one of the better predictors, so I'd look almost only at it.
First of all, not a lot of teams won the cup twice in a row
Second it's way harder if everybody is focused on you
(because you won the last time)
I'm pretty sure barley any data can reflect these two statements. (ok the first one can, but the second one is a more emotionell effect)
That is just because winning itself is low probability. But repetition is not a factor.
* Italy won in 1934 and 1938
* Brazil won in 1958 and 1962
Last WC my prediction was Argentina (reached the final).
I feel intuitions do matter. This time: Argentina again
The Economist is doing it. 538 has done one. Everyone is doing it.
They all wind up with similar predictions.
Germany, Brazil, France and Spain are favourites.
This is what the betting odds, transfermarkt and the mean salaries of the teams also tell you.
There are limits to prediction. The WC is a good place for people to learn that.
I guess the idea is that over time, you measure prediction performance, but models are constantly changing and there's enough time in between WC tournaments that it'll take at least a century to have a good sample size of predictions.
If you take something more immediate like predicting tomorrow's stock prices or even the market (up/down), I wonder how their prediction models would fare.
See also: https://predictionbook.com
This is new to me. Is the mean salary of a national team predictive? And are you using the mean salary the nation pays or their club salaries?
In other words: how effective has this salary prediction worked out in the past?
My questions were: 1) is this an established metric that’s commonly used to predict football (soccer) results and 2) what salary are we talking about, the amount the nation plays to its team’s players (e.g. Brazil pays more than England) or the amount a nation’s players earn on their club teams (e.g. Neymar earns more at PSG than Rooney does for Everton)?
(2) the discussion is naturally about how much they earn for their clubs presently. National teams pay no salary and many top players do not, and in some cases, have never played in their birth country's own league.
This is not even close to true.
Makes for a bit of a dull ending sometimes.
France hadn't won a WC and kept choking until 1998. Spain were the same until 2010.
Italy and Argentina have been in and out of the favourites as well.
England were #1 in Elo rankings in the late 1980s and got to the semis in 1990 and were only knocked out with the help of a handball in 1986.
With a bit of luck Holland might also have been able to win a WC. Finals in 74, 78 & 2010.
But outside a few big teams it is pretty unlikely that there will be a real surprise winner. There are too many big good teams so that one or two surprises isn't enough to win. For example South Korea shocked Italy in 2002 but then Germany beat them. Or Croatia beat Germany in 1998 but then got beaten.
More about the journey than the destination.