American readers may know that the ongoing 2018 international soccer/football tournament is a big deal in other countries. But it's hard to grasp just how ubiquitous and important it is when there's no other event like it in the United States. The best way I can describe it is if the series finale of Game of Thrones aired during the commercial breaks of the Super Bowl and the halftime show was Beyoncé hosting the Oscars.
Now that we have a better idea of just how significant this tournament is, I thought it would be fun to dig into the upcoming tournament in Russia and also see what we could learn from reviewing the results of past tournaments using SAS Visual Analytics on SAS Viya.
How far will teams travel for the tournament?
If the visualization is not rendering in your browser, you can see how far teams travel here.
This report shows the distance the participating countries will travel during the first stage of the tournament. In the first stage, eight groups of four teams play each other and the top two in each group qualify for the knock-out stage. Therefore, each team will play at least three games in 11 days. In between game days, the teams will stay at a team base camp somewhere in western Russia.
It turns out Russia is very big, resulting in a potential advantage for teams that are playing more games near to their team’s base camp. Colombia clearly has the best travel situation by staying in Verkhneuslonsky. Egypt, the country doing the most traveling, is staying in Chechnya, where Islam is the predominant religion.
Which stadiums hold the most fans?
The "Maximum Possible Attendance" refers to the seating capacity of the stadiums the teams will be playing in. Therefore, if every game sells out, Russia will be the team that plays in front of the most fans, and Serbia will be the team that plays in front of the least.
Does the age of players correlate with the team's probability to win?
If the visualization is not rendering in your browser, you can see how player age correlates with winning here.
Football and drama go together like eggs and bacon, peanut butter and jelly, FIFA and bribery allegations. However, there has not been much drama lately in terms of dramatic upsets.
This report shows the average age of the players of each country and the implied probability of each country winning, as well as those of the previous five champions. The implied probability of each country winning comes from publicly available betting lines.* The five previous champions have a similar profile in terms of predicted probability of winning and average team age. They were all heavy favorites and boasted rather young players.
Brazil, with about a 21.1% chance of winning, has the highest odds overall in this tournament. Belgium, with about a 9.1% chance of winning, has the highest odds for a country that has never been to a final.
*Note: The probabilities of each team winning comes from betting lines posted before the start of each tournament.
Historic international football performances
If the visualization is not rendering in your browser, you can see historic performance data here.
There have not been a lot of major upsets, as covered above. This report only shows South American and European countries because every champion has come from one of these two continents. Only eight countries have won at least one of the 20 tournaments. Only 12 countries have been represented in the finals, and one of them (Czechoslovakia) has since dissolved into two separate countries.
*Note: In the report above, England is designated as United Kingdom for mapping purposes
My final prediction
As for my personal prediction, I think history will repeat itself with the major football powers dominating again, and no new countries will be represented in the finals. As a Brazilian, it pains me to write this like it pains Sepp Blatter to not be part of the 2026 bidding process – but I think Spain will take on France in the finals, and France will hold the trophy.
Who do you think will win the tournament? Comment below and share your thoughts!Explore more industry data with SAS Visual Analytics