If a simulation he devised is any indication, decision analyst Steve Begg of the Australian School of Petroleum at the University of Adelaide does not look favourably on his home nation’s chances in football’s 2018 World Cup, which kicks off in Russia on June 14.
His uncertainty model only gives Australia’s team, the Socceroos, a 0.1% chance of winning the tournament, but fans may be consoled by Germany’s fortunes – despite their lofty status as perennial favourites and the presence of stars such as goalkeeper Manuel Neuer and prolific forward Thomas Müller, Die Mannschaft are given a modest 13.3% chance of equalling Brazil’s record five World Cup wins.
Using a combination of team rankings and recent form, Begg set aside his usual focus on the oil and gas industry to develop a ‘Monte Carlo simulation’ of the competition.
The Monte Carlo method was devised in World War II as part of research carried out for the Manhattan Project, an American undertaking supported by the UK and Canada which resulted in production of the world’s first atomic bomb. The aim of the technique is to model enough possibilities to allow a reasonable estimate of the chances of a particular outcome materialising, instead of devising every single potential result.
“The outcomes of many decisions we make are uncertain because of things outside of our control,” Begg explains.
“In the World Cup, [uncertainty] 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.”
There are many potential outcomes of the 63-game, 32-team competition – over 400,000 for the initial group stage alone. However, Begg believes the 100,000 permutations generated by the model – at the speedy rate of 800 per second – are “more than enough” to assess each team’s likely chances.
The two key areas of uncertainty identified by Begg for each team are “tournament form” (their general performance entering the finals) and “match form” (their likelihood of under- or over-performing relative to tournament form in a given match). The possible results for each match are generated based on results from the last three World Cup tournaments, with a likely number of goals allocated to each team based on their relative match form.
The model also takes into account each team’s placing in the Fédération Internationale de Football Association (FIFA) world rankings over the past four years, with adjustments made by Begg based on his knowledge of each team.
For instance, he calculates that Russia’s home advantage gives higher weight to their “tournament form”, and with good reason – the trophy has been lifted by the host nation on six occasions across 20 instalments of the competition. Meanwhile, teams with less tournament pedigree have a higher “giant killing” quotient than stronger teams.
Based on current inputs, the Australian national team – ranked fortieth in the world by FIFA going into the competition – is given a modest 14% chance of advancing from Group C, where their opponents include 1998 world champions France.
The Socceroos are then given a 3.8% chance of bettering their best-ever World Cup performance, in 2006, by reaching the quarter-finals, a 1.2% chance of reaching the semi-finals, a 0.3% chance of reaching the final and a 0.1% chance of winning the World Cup – an honour which is yet to be achieved by a nation outside the traditional football hotbeds of Europe and South America.
“This may be disappointing,” Begg says, “But to make good decisions, it is really important to base beliefs on evidence and reason, not what you would like to be true.”
If Australian fans are hoping for better news from elsewhere, a similarly broad study by a computer-gamer on the popular simulation Football Manager only brings further disappointment.
The YouTube broadcaster, known as Golden FM, simulated the tournament 100 times on the game and unlike relative outsiders such as Poland, Mexico and Serbia, Bert van Marwijk’s Aussie troops couldn’t register a single tournament victory. This study, such as it is, marks a strong Belgium side as favourites with 22 wins, edging out France with 17.
Begg and Golden FM, however, have stiff competition in the World Cup prediction industry – their Russian counterparts include a deaf cat and a polar bear, both of whom make their forecasts based on the flags placed next to their bowls of food. They follow in the footsteps of the late ‘animal oracle’ Paul the Octopus, who made global headlines by correctly predicting Spain’s 2010 World Cup triumph using a similar method.
Andrew Patterson is a freelance science writer from Newcastle, UK.
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