Skip to main content

How to create a dream team

How to create a dream team

With the BBC and several major football teams on our doorstep, the University’s latest research centre, the Centre for Sports Business, is well positioned to help sporting organisations get a head start.

And they’re off to an auspicious start with Rick Parry, the former Chief Executive of the Premier League, kicking off the proceedings at the launch, with a speech about how and why the Premier League was created.

Research and consultancy

The Centre for Sports Business is particularly strong in analysing the statistics of sport, which has led to a tie-in with global video game company EA SPORTS. Several years ago, a call went out to universities asking about rating players in the Premier League. The rating system needed to be objective and the mathematical model proposed by statisticians in the Centre was accepted by the Premier League. The rating system now known as the EA SPORTS Performance Index (PPI) is the official player rating system for the Barclays Premier League, the most-watched league in global football with an estimated TV audience of 4.7 billion people. This is the kind of high- profile work that has made the new Centre a leader in its field.

Dream Team - Research - University of SalfordThe PPI, which is also used for the second-tier league in English football – The Championship– is cleverly constructed so that it can compare players from different positions, looking at the contribution each player makes to the success of his team. The highest ranked player doesn’t need to be a goal scorer or even be in the top team. The best player is simply the player that would hurt any team the most if they were to lose him.

The key to being able to set up success stories such as EA’s PPI is the revolution in the mathematical analysis, or ‘analytics’, of football. Several things have come together to make this possible. Naturally, there has been the rise of computer processing power – a general trend in all data analysis. However, you must have data in the first place to be able to process it.

This is where the most significant change has occurred. Companies such as Opta and Prozone now collect astonishing amounts of data for every Premier League match. Each game generates a 1,500 row by 200 column spreadsheet of match facts and figures. It looks at the X-Y coordinates (position on pitch) of shots and passes, and their destination. Z coordinates even tell you how high the ball travels. Everything imaginable is logged: from the position of the ball to recording if a tackle is sliding or standing. There are even companies that now record the positions of all 22 players four times a second, which means you can get data on not just the speed but also the acceleration of players.

All this information, and the computers to handle it, means that it is now possible to mathematically model a continuous, fluid, dynamic game like football. The statisticians at the Centre take this data, feed it through their computer models and produce analysis of games and players.

The ‘stats’ are essentially the collection of data, perhaps given a very rudimentary level of analysis; for example, the average number of goals per game, but the real power comes from analytics – using the statistical modelling on large data sets to offer insights into teams and the effect of individual players.

Just how powerful this knowledge can be is shown by its impact on North American sport.

It was first demonstrated successfully with an American baseball team called Oakland Athletics, which wasn’t very successful and relatively speaking didn’t have much money. A statistician suggested to them that instead of using old-fashioned scouting techniques for identifying talent, they should use an analytical model of baseball matches to find players who are statistically undervalued by the market.

They used the model, and with a fraction of the budget of the top-rated New York Yankees, beat them. The model looked at what attributes players bring that can have the biggest impact on the probability of being successful, and then looked for gaps in the market to sign up promising but ‘cheap’ players.

The next stage in the evolution of sports analytics is to ensure UK sports management get the buy-in of UK sports, like football, so that the owners and management can appreciate what analytics offer. It is far more than just choosing new players. Devising strategies and working out which players in a team work well together are the kind of problems that analytics is good at helping to solve. In Britain, football’s popularity makes it a big focus for the Centre’s work, but researchers are also looking at other sports.

Tennis and golf are amenable to similar models that examine a player’s strengths and progress over time and work is ongoing in these sports.

Fighting corruption and match fixing

An area of growing interest is detecting and preventing match fixing. One of the Centre’s researchers is heavily involved with a Qatar- based organisation called the International Centre for Sports Security. Qatar, having recently won the rights to host the World Cup, is serious about preventing corruption in sport.

It’s not easy to spot a fixed match but one approach is to use models of match outcomes based on what is going on in the match, and compare the predicted match outcomes with betting market activity. The point is that when a match is fixed, somebody somewhere puts a lot of money on a particular outcome that the crooked better knows is more likely to happen than the prediction model. When this happens, bookmakers move the odds to protect themselves.

So, if you watch the odds, and know the probabilities inferred by the model, which is based only on what’s going on in the match, then it should be possible to flag up an event that doesn’t ring true, possibly by a large volume of abnormal betting caused by dishonest insider knowledge. This is not pointing the finger at bookies, rather highlighting red flag events revealed by their reacting to betting levels. From there, depending on the circumstances and the level of suspicion, a report to football governing bodies such as UEFA or FIFA could be generated.

That’s the analytical approach, but the Centre is also looking at other aspects of match fixing.

The basic economics of crime say a player will choose to commit a crime if it’s worth his while. In a sport like football it’s generally not worth it for a Premier League striker to fix a match. He’s paid very well, has excellent sponsorship and would risk losing a fortune. On the other hand, referees are not paid very much, so from an economic point of view, a referee could be offered a ‘realistic’ amount of money and he might start thinking about cheating.

It’s not just football; other sports can be even more vulnerable to match fixing. For example, in snooker some top players are not paid a great deal of money.

The first prize in an international snooker competition is just a week’s wage for a top Premier League footballer. Couple that with the enormous amounts of money involved in betting on snooker in the Far East and the risks are serious. Last, but not least, it’s not difficult to hide cheating in snooker – a player just has an ‘off day’.

Analysing which sports and what form corruption can take is an important aspect of the Centre’s research.

The National Lottery

Analytics can also be used to demonstrate that match fixing or other forms of malpractice have not been taking place. A good example is the Centre’s work for the UK National Lottery via the Gambling Commission.

Given the size of the lottery, it is not surprising that a small number of people develop varying levels of conspiracy theories about the appearance of certain numbers or combinations of numbers. Someone might call up and say ‘36 has appeared three times in the last four weeks, this is clearly impossible and the lottery must be a fix’. So, the Lottery uses statisticians at the Centre to run a series of tests to show it is random and nobody is cheating or being cheated. People tend to think it’s extremely unlikely that two consecutive balls will appear in the lottery and complain if this happens on a regular basis.

In fact, quite simple probability theory reveals that the odds of consecutive numbers appearing is actually nearly 0.5 and so will happen nearly every other week in the long run.

Ian McHale, Director of the Centre for Sports Business, University of SalfordPerhaps the last word on the new Centre for Sports Business should go to its director, Dr Ian McHale.

"You only have to look at the interest and excitement last year’s Olympics brought to the UK to see how much sport matters to us. And of course it is not just here that sport means so much – sport is a global business and to me, there is no doubt about it, it is the most exciting business there is.

"Here at Salford we are extremely fortunate in having a group of academics who, during the last ten years and more, have earned a global reputation for high-quality research in each of our subject disciplines when applied to sport. This group of people now form the Centre for Sports Business.

"So who are we? We have expertise in statistics, economics, business and management and law. We already constitute what is arguably the leading collection of researchers into quantitative analysis in sports from around the world.

"But it is not just research we do – we are heavily involved in consultancy projects within the sports and betting industry. From developing the EA SPORTS Player Performance Index to advising governments and sport’s governing bodies on strategies to detect and prevent match fixing, the Centre for Sports Business is already at the heart of the sports business.”

To receive research findings, reports and papers, please send your details to