So says a quantitative model from JP Morgan. Analysts Matthew Burgess and Marco Dion used a model designed to predict stock prices and fed it with past scores and Fifa rankings and came to this unauthordox conclusion.

“Having developed a rather successful Quant Model over the years, we intend to introduce it to our readers and also use its methodology to apply it to a fruitful field for statistics: Football and the World Cup,” they wrote.

Given the reputation of Wall Street “quants” at the moment, doesn’t this seem a little hubristic?

I had my own brush with soccer stardom this week in Sao Paulo, where I spent Monday and Tuesday with Marcello Magalhaes and the wonderful people in the the Ogilvy office there.  This is one of the beacons of the Ogilvy network.  Check out their work here.

During my short visit, there was a running joke that I would be rewarded with a free T-shirt.  And on the last day I was given a Corinthians soccer shirt signed by Ronaldo, in a gesture typical of the Brazilian’s crazy  generosity.

Sadly, Ronaldo will not be playing in the world cup this year.  Instead, Ogilvy has signed him up for a Twitter campaign for Claro, the country’s largest mobile phone network, in a superb digital influence campaign.

Obviously, as a Scot, I have to assume that the JP Morgan prediction is deeply flawed, and thus that their models are worthless.  I have, of course,  shorted their stock.

The last time Scotland qualified for the World Cup, in 1998, they were crushed by the Brazilians in their first match.  I will, however, this year, be giving my full support to their valiant team.

I mapped the companies on a scatterplot using Many Eyes (please be patient as this page can take time to load).  There were a few outliers like Starbucks so I took the log of both the mentions and followers to make the map legible.

The dots on the horizontal axis represent brands that do not officially participate in the conversations on Twitter (they have no followers).  The ones on the right hand side of the graph (Apple, Microsoft and AIG for example) are mentioned frequently in conversations so they might want to consider taking a more active role.  

For the brands that do have followers there seems to be a correlation between followers and mentions.  That makes sense intuitively.  Brands in the top right quadrant are very active and the ones on the bottom left are not.

If you draw an imaginary trend line through the scattercloud you would find brands on that line to have a number of followers that is in proportion to the volume of mentions they get.  Brands above the line however get followed more than they are talked about.  It’s the other way around for brands below the line.  If you mouse over the dots on the graph you see which brands fall where.

I think we need more data to really interpret the graph.  Being followed more than being talked about could be good or bad depending on the engagement levels of the followers.  Being talked about more than being followed could be good or bad depending on the sentiment of the conversations about the brand.  Even if the interpretation of this graph isn’t 100% clear, I thought I’d post it anyway as I think it is interesting to compare brands visually.  Would love to hear your thoughts.

A couple of weeks ago I wrote about the new York Times’ award winning visualization of movie ticket sales.  This is a similar graph displaying words that are included in Tweets about American Idol leading up to yesterday’s finale.  The Neoformix folks put a nice little Twitter Streamgraph app online so you can make these graphs yourself about anything you want.  Here’s one for the word doublethink.