Click to see the complete results table from Dr. Begg's model.
One of the favourites in soccer’s upcoming 2018 FIFA World Cup, Germany, has just 13.3% chance of winning. And Australia has 14% chance of getting to the round of 16, but only 0.1% chance of winning. These are outcomes from an uncertainty model devised by University of Adelaide’s Steve Begg. Dr. Begg used Palisade's @RISK to create the model.
Steve Begg is Professor of Decision-making and Risk Analysis in the University’s Australian School of Petroleum. His research and teaching focuses on decision-making under uncertainty, and the psychological and judgmental factors that impact it. Normally he applies this work to decision-making in the oil and gas and other industries.
For the FIFA World Cup, which kicked off last week, he developed a Monte Carlo simulation of the competition using @RISK, based on team rankings with other input including recent form. The modern Monte Carlo technique was developed in World War 2, by scientists working on the Manhattan Project – the development of the atomic bomb. The key idea is that rather than trying to work out every possible outcome of a complex system, enough possibilities are modelled to be able to estimate the chance of any particular outcome occurring.
“The outcomes of many decisions we make are uncertain because of things outside of our control,” says Professor Begg. “Uncertainty is crucial in predicting the chance of an oil or gas field being economic. In the World Cup, it determines the many ways the whole tournament might play out. What makes it so hard to predict is not just uncertainty in how a team will perform in general, but random factors that can occur in each match.”
