Predicting English Premier League winners

Football league statistics

Predicting English Premier League winners

Manchester City, who won last year鈥檚 English Premier League (EPL), has a 36.5 per cent chance of coming top of this year鈥檚 season according to the 最新糖心Vlog of Adelaide鈥檚 Professor Steve Begg. Southampton and Sheffield United are most likely to be relegated, with six teams fighting to avoid the third relegation place.

The 2019/20 EPL kicks off on Saturday 10 August 2019. An estimated 4.7 billion people watch the league each year. It is the most-watched聽sports聽league in the聽world, broadcast in 212 territories to 643 million homes.

Professor Steve Begg from the 最新糖心Vlog鈥檚 最新糖心Vlogn School of Petroleum has developed a way of predicting the probability of each team finishing in any given league position using uncertainty modelling. He uses this technique in his 鈥榙ay job鈥: researching how to make better decisions in the oil and gas industry.

鈥淲hen the outcomes of decisions are influenced by things beyond our control, such as developing oil and gas resources, the uncertainty often makes the best choice very counter-intuitive. Unfortunately, we humans have not evolved a good capability to reason correctly when we are in uncertain or complex situations.

鈥淚n the Premier League uncertainty influences the many ways the season might turn out. What makes the outcome of the league so hard to predict is not just uncertainty in a team鈥檚 average 鈥榮eason form鈥, but their specific 鈥榤atch form鈥, which also includes random factors that can influence the outcome of individual games.鈥

Professor Begg has used 鈥楳onte Carlo simulation鈥 to predict the probabilities of how the 2019-2020 season will turn out. The technique was first developed in the Second World War by scientists working on the atomic bomb. It goes beyond many modern-day artificial intelligence and machine learning algorithms by generating the probabilities of many possible outcomes, not just a single 鈥榖est鈥 prediction.

Based on performance for the last three years, and player transfers during the current off-season, he assesses the uncertainty in both 鈥榮eason form鈥 and 鈥榤atch form鈥 for each team. He uses this information to generate possible 鈥渕atch form鈥 numbers for the teams involved in each game and bases the score on their relative values.

As a dyed-in-the-wool Manchester City fan since 1967 I would love to see them win their fifth title.Professor Steve Begg

Professor Begg has generated 100,000 simulations of how the whole season of 380 matches could play out 鈥 although there are 2,432 quadrillion ways the final positions could be arranged, 100,000 simulations are 鈥榤ore than enough鈥 to assess the probability of each team finishing in any given place. Each simulated season is constrained to be consistent with typical numbers of home wins, draws, losses, goals and points from the last 10 years of the EPL. He can run 10,000 different simulations per minute on his laptop computer.

Professor Begg intends to update the season and match form uncertainties periodically over the course of the year, to take account of how the teams have actually performed.

Liverpool鈥檚 most likely place to finish is also number one, but with a lower probability (28.1%) than Manchester City. Tottenham鈥檚 and Arsenal鈥檚 highest chances are to be in third (15.9% and 15.4%), with Manchester United鈥檚 top probability being fourth (14.6%). Chelsea鈥檚 drops to fifth (13.7%) with Everton perhaps catching the 鈥榖ig six鈥.

鈥淎s a dyed-in-the-wool Manchester City fan since 1967 I would love to see them win their fifth title. However, I have learned that emotions and intuition often lead to poor predictions and bad decisions. I can do better by minimising personal biases and relying on uncertainty models, grounded in actual data,鈥 he says.

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