R, Scientometrics, Knowledge Management, and Social Network Analysis

Most Important Player in the Spanish Team from 2008 to 2012 tournaments

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Below is the rank of importance among Spanish players in the EURO 2008, FIFA World Cup 2010, and EURO 2012. The rank is based on the number of touches in the game (i.e. the number of outgoing AND incoming passes of each player). The calculation is done in R, thanks to Tore Opsahl’s tnet package.


Note: In the tnet package, the alpha that I used was 0.5.


Written by Mat

March 16, 2013 at 9:44 am

Barcelona vs AC Milan Passing Distribution (2nd Leg)

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Barcelona vs AC Milan 2nd Leg

Some changes can be noticed clearly when the passing distribution in the 2 legs are compared. Here is the link to the first leg passing distribution.

  1. With David Villa playing rather than Fabregas, Messi could drop deeper and work more cohesively with Xavi and Iniesta.
  2. Moving Pedro to the left seems to be a fruitful decision too. First, Alves can work directly with Messi once again and at the same time Jordi Alba is “forced” to be more discipline defensively (i.e. doesn’t need to overlap very often as Pedro is already there). This impact can also be seen in AC Milan passing distribution in the two legs. See how Abate-Boateng thick link in the first leg is no longer present in the 2nd leg (replaced by Constant-Shaarawy link).

Written by Mat

March 13, 2013 at 10:19 am

Euro 2012 Multidimensional Scaling Analysis

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Based on OPTA’s data (via footytube), below is the multidimensional scaling plot based on per game data of passes, passes completed, touches, crosses, dribbles, corners taken, and offsides.

I was using Classic Multidimensional scaling, from wiki:

Multidimensional scaling (MDS) is a set of related statistical techniques often used in information visualization for exploring similarities or dissimilarities in data.

Also known as Principal Coordinates Analysis, Torgerson Scaling or Torgerson–Gower scaling. Takes an input matrix giving dissimilarities between pairs of items and outputs a coordinate matrix whose configuration minimizes a loss function called strain.

Based on the figure below, it is indicated that Germany and Netherland should have similarities, the same can be said with Ukraine, Czech, and Sweden. However, as far as my memory goes in watching the Euro 2012 games, I failed to notice how the teams are similar. In addition, what should be the label for the x and y dimensions?

Any comment?

Euro 2012 Multidimensional Scaling Analysis

Note: The input matrix in this case is as shown below and can be downloaded here.

I then used R to do the multidimensional scaling analysis.


Written by Mat

March 6, 2013 at 12:18 pm

Barcelona vs AC Milan Passing Distribution

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Barcelona vs AC Milan Passing Distribution

Barcelona vs AC Milan Passing Distribution

Written by Mat

February 21, 2013 at 10:48 am

Munchen vs Madrid Passing Distribution

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Munchen vs Madrid Passing Distribution

Didn’t watch the match, but have been reading how Toni Kroos played an important role in the match. Based on the graph, he IS quiet central for Munchen in the match.

Some notes:

  1. Why were there so many passes by Alonso to both central defenders Ramos and Pepe?
  2. Centrao-Arbeola and Alaba-Lahm have similar passing distribution towards their central defenders (backward pass), but see how they differ in terms of forward passes.

Written by Mat

April 20, 2012 at 12:45 pm

Chelsea vs Barcelona Passing Distribution

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Which side is Barcelona?

Chelsea vs Barcelona Passing Distribution

Chelsea vs Barcelona Passing Distribution

The number of passes by all Chelsea players: 194.
The number of passes by all Barcelona players: 779 (Xavi alone completed 127 successful passes and received 133 passes!).

Ball Possession: Chelsea 28% – 72% Barcelona.

But, the most important fact is still Chelsea 1, Barcelona 0.

Written by Mat

April 19, 2012 at 4:09 pm

Most Productive Authors in JASIST

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Timeframe: Dec 2001 (JASIST vol 52, No. 14) – July 2011 (JASIST vol 62, No. 7)

Two types of counting method are used:

  1. Whole count: Each author receive a credit with a count of 1.
  2. Fractional count: Here, if a publication is authored by N number of authors, each author receive credit with a count of 1/N.

Source: ISI Web of Knowledge

Written by Mat

July 17, 2011 at 10:31 am

Posted in Scientometrics

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