Matches used for learning of the knowledge model:

• World Cup 2002 and 2006, both preliminaries and final stage
• EURO Cup 2000 and 2004, both preliminaries and final stage.
• EURO cup 2008 preliminaries.
• Only World Cup matches between European countries have been considered
• Friendly matches are not included.

Additional variables have been added to learn about the prerequisites of the teams:

• Population of the country
• Gross national product of the country
• Information about how many times the country has participated in World or Euro Cup during the last 10 years.

About BayMiner
BayMiner is a browser-enabled tool for analysis of data in table format. It finds all dependencies in true multi-dimensional situations and above all visualizes their co-occurrences in a format understandable for a human being. The data to be analysed can be about products and services, processes or data collected by the company about their customers satisfaction - the method is independent of the context it is used in. The data does not need to be numeric and the source table does not need to be complete. Instead of curves and cakes, BayMiner, using machine-learning, produces an easy to use knowledge model. Unlike conventional data mining tools the BayMiner user does not require basic information about statistics or the technology used (Bayesian Networks). These are a form of probability calculus. They enable the user to grasp complex cause-dependencies and reveal those factors that cause e.g. quality disturbances. A Bayesian knowledge model can successfully be used for predictions when a time series is not long enough for conventional frequentistic methods. Bayesian networks are nowadays considered the best technology to master uncertainty.