2014 World Cup Squads

I have been having a go in R at visualising player movements for the World Cup. I wanted to use similar plots to those used to visualise international migration flows in the recent Science paper that I co-authored. In the end I came up with two plots. The first, and more complex one, is based on a non-square matrix of leagues system of players clubs by their national team.

You can zoom in and out if you click on the image.

Colours are based on the shirt of each team in the 2014 World Cup. Lines represent the connections between the country in which players play their club football (at the lines base) and their national teams (at the arrow head). Line thickness represent number of players. It’s a little cluttered, but shows nicely how many players in the English, Italian, Spanish and French leagues are involved in the world cup. It also highlights well some countries where almost all the players are at clubs abroad, for example most of the players in the African squads.

Whilst the first plot gave a lot of detail, I wanted to visualise the broader interactions, so I aggregated over leagues systems and national squads by regional confederations. This gives a square matrix:

> m
  AFC       49        2        1   3    1
  CONCACAF   0       13        0   0    0
  CONMEBOL   2        0       54  11    0
  CAF        0        0        0  36    0
  UEFA      41       99       37  86  296

The plot of which looks like:

This type of aggregation works really well to show how few European national players play elsewhere (only Zvjezdan Misimovic in all the European World Cup squads). It also provides a way to compare the share of non-European players plying their trade in the European leagues to those in more local leagues within their confederation.

I scraped the data from the provisional squads on Wikipedia, and then created the images with the circlize package. All the code to reproduce the plots + scraping the Wikipedia squad pages are on the my github.

Football Predictions: 2010 World Cup

The world cup is over, and I have updated prediction table (see final version below). Well done to Tom who correctly predicted the final. Hard luck to Dave C. who would have won if Tom was 1) patriotic (and actually supported England) and 2) did not make his golden boot prediction a week into the tournament. However, given that these predictions are based on a FIFA tournament, its logical that no action is taken against those who do not play by the rules correctly. Congratulations Tom.

Scoring system:

Lowest points total wins. Points calculated from each category as such:

Winner: 10 x No of wins away from predicted team becoming champions.
Runner: Up 7 x No of wins/losses away from predicted team becoming runner up.
Semi Final: 3 x No of wins/losses away from predicted teams loosing in Semi Finals.
Quarter Final: 1 x No of wins/losses away from predicted teams loosing in Quarter Finals.
Own Team: 7 x No of wins/losses away from own teams predicated finish.
Golden Boot: 5 x No of goals your chosen player is away from the top scorers tally.
Fair Play: -5  If you correctly predict the fair play team.

Tie breaks decided by own team predictions, then alphabetical order.