The late Chris Brasher, founder of the London Marathon, described the event as the ‘Suburban Everest’ - something everyone can aspire to do. Over the years, an increasing number of people have done just that. At the first London Marathon in 1981 there were 7,000 runners, in 2016 there will be 37,000 (and that ignores the growth in the sport due to new events around the country).

In the absence of huge amounts of money, gaining a competitive edge in sport requires creative innovation. As Moneyball most famously dramatised, statistics is one avenue that can deliver that edge. But different sports can have vastly different levels of noise to wade through before a signal is found. This question was the basis for a panel discussion at this year’s RSS Conference in Exeter. The panel consisted of a mix of sports coaches, academics and a statistician, who are all trying to discover an insight into sport through data, that would otherwise remain hidden.

As Yogi Berra, once said: ‘It's tough to make predictions, especially about the future’. Like most future events, it is impossible to know for certain who will win the 2015 Rugby World Cup, but we can estimate probabilities of various outcomes occurring. We do this by building a rating system for international rugby matches and using these ratings to estimate expected score margins (like who will win and by how much.) We can then characterize uncertainty around these predictions.

The transfer market in football is a strange beast. For anyone who doesn't know how it works, clubs are allowed to buy and sell players during two windows each year: one during January (a maximum of four weeks long during the playing season) and another during the summer (approximately from June to the first few days in September, this time with a maximum length of 12 weeks).