Why is the Pope resigning?

Benedict XVI to step down on 28 February, citing "health reasons".

The Italian state news agency, ANSA, is reporting that Pope Benedict XVI is to resign on 28 February for health reasons due to his "advanced age". He will be the first pope to resign in nearly 600 years, since Gregory XII gave up the throne in 1415 to solve the fact that there were three claimants to the Papacy.

Cardinal Angelo Sodano, the dean of the college of cardinals, called the decision - which was made personally in a speech in Latin by the Pope at a meeting called a consistory - "a bolt from the blue". Benedict XVI is 85 years old, and has been Pope since April 2005. 

Paddy Power is offering odds on where the next pope will come from, with Italy the favourite at 5/4, but both Africa and Canada (yes, a continent being compared to a nation) looking likely at 2/1 and 5/2 respectively. Ladbrokes is offering odds on named successors: 5/2 for Cardinal Peter Kodwo Appiah Turkson, 3/1 for Cardinal Marc Ouellet, 4/1 for Cardinal Francis Arinze, and 6/1 for Cardinal Angelo Scola.

The full text of the pope's resignation reads as follows:

Dear Brothers,

I have convoked you to this Consistory, not only for the three canonisations, but also to communicate to you a decision of great importance for the life of the Church. After having repeatedly examined my conscience before God, I have come to the certainty that my strengths, due to an advanced age, are no longer suited to an adequate exercise of the Petrine ministry.

I am well aware that this ministry, due to its essential spiritual nature, must be carried out not only with words and deeds, but no less with prayer and suffering. However, in today’s world, subject to so many rapid changes and shaken by questions of deep relevance for the life of faith, in order to govern the bark of Saint Peter and proclaim the Gospel, both strength of mind and body are necessary, strength which in the last few months, has deteriorated in me to the extent that I have had to recognise my incapacity to adequately fulfil the ministry entrusted to me.

For this reason, and well aware of the seriousness of this act, with full freedom I declare that I renounce the ministry of Bishop of Rome, Successor of Saint Peter, entrusted to me by the Cardinals on 19 April 2005, in such a way, that as from 28 February 2013, at 20:00 hours, the See of Rome, the See of Saint Peter, will be vacant and a Conclave to elect the new Supreme Pontiff will have to be convoked by those whose competence it is.

Dear Brothers, I thank you most sincerely for all the love and work with which you have supported me in my ministry and I ask pardon for all my defects. And now, let us entrust the Holy Church to the care of Our Supreme Pastor, Our Lord Jesus Christ, and implore his holy Mother Mary, so that she may assist the Cardinal Fathers with her maternal solicitude, in electing a new Supreme Pontiff. With regard to myself, I wish to also devotedly serve the Holy Church of God in the future through a life dedicated to prayer.

From the Vatican, 10 February 2013

BENEDICTUS PP XVI

Pope Benedict XVI, who is resigning on 28 February. Photograph: Getty Images

Alex Hern is a technology reporter for the Guardian. He was formerly staff writer at the New Statesman. You should follow Alex on Twitter.

OLIVER BURSTON
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How science and statistics are taking over sport

An ongoing challenge for analysts is to disentangle genuine skill from chance events. Some measurements are more useful than others.

In the mid-1990s, statistics undergraduates at Lancaster University were asked to analyse goal-scoring in a hypothetical football match. When Mark Dixon, a researcher in the department, heard about the task, he grew curious. The analysis employed was a bit simplistic, but with a few tweaks it could become a powerful tool. Along with his fellow statistician Stuart Coles, he expanded the methods, and in doing so transformed how researchers – and gamblers – think about football.

The UK has always lagged behind the US when it comes to the mathematical analysis of sport. This is partly because of a lack of publicly available match data, and partly because of the structure of popular sports. A game such as baseball, with its one-on-one contests between pitcher and batter, can be separated into distinct events. Football is far messier, with a jumble of clashes affecting the outcome. It is also relatively low-scoring, in contrast to baseball or basketball – further reducing the number of notable events. Before Dixon and Coles came along, analysts such as Charles Reep had even concluded that “chance dominates the game”, making predictions all but impossible.

Successful prediction is about locating the right degree of abstraction. Strip away too much detail and the analysis becomes unrealistic. Include too many processes and it becomes hard to pin them down without vast amounts of data. The trick is to distil reality into key components: “As simple as possible, but no simpler,” as Einstein put it.

Dixon and Coles did this by focusing on three factors – attacking and defensive ability for each team, plus the fabled “home advantage”. With ever more datasets now available, betting syndicates and sports analytics firms are developing these ideas further, even including individual players in the analysis. This requires access to a great deal of computing power. Betting teams are hiring increasing numbers of science graduates, with statisticians putting together predictive models and computer scientists developing high-speed software.

But it’s not just betters who are turning to statistics. Many of the techniques are also making their way into sports management. Baseball led the way, with quantitative Moneyball tactics taking the Oakland Athletics to the play-offs in 2002 and 2003, but other sports are adopting scientific methods, too. Premier League football teams have gradually built up analytics departments in recent years, and all now employ statisticians. After winning the 2016 Masters, the golfer Danny Willett thanked the new analytics firm 15th Club, an offshoot of the football consultancy 21st Club.

Bringing statistics into sport has many advantages. First, we can test out common folklore. How big, say, is the “home advantage”? According to Ray Stefani, a sports researcher, it depends: rugby union teams, on average, are 25 per cent more likely to win than to lose at home. In NHL ice hockey, this advantage is only 10 per cent. Then there is the notion of “momentum”, often cited by pundits. Can a few good performances give a weaker team the boost it needs to keep winning? From baseball to football, numerous studies suggest it’s unlikely.

Statistical models can also help measure player quality. Teams typically examine past results before buying players, though it is future performances that count. What if a prospective signing had just enjoyed a few lucky games, or been propped up by talented team-mates? An ongoing challenge for analysts is to disentangle genuine skill from chance events. Some measurements are more useful than others. In many sports, scoring goals is subject to a greater degree of randomness than creating shots. When the ice hockey analyst Brian King used this information to identify the players in his local NHL squad who had profited most from sheer luck, he found that these were also the players being awarded new contracts.

Sometimes it’s not clear how a specific skill should be measured. Successful defenders – whether in British or American football – don’t always make a lot of tackles. Instead, they divert attacks by being in the right position. It is difficult to quantify this. When evaluating individual performances, it can be useful to estimate how well a team would have done without a particular player, which can produce surprising results.

The season before Gareth Bale moved from Tottenham Hotspur to Real Madrid for a record £85m in 2013, the sports consultancy Onside Analysis looked at which players were more important to the team: whose absence would cause most disruption? Although Bale was the clear star, it was actually the midfielder Moussa Dembélé who had the greatest impact on results.

As more data is made available, our ability to measure players and their overall performance will improve. Statistical models cannot capture everything. Not only would complete understanding of sport be dull – it would be impossible. Analytics groups know this and often employ experts to keep their models grounded in reality.

There will never be a magic formula that covers all aspects of human behaviour and psychology. However, for the analysts helping teams punch above their weight and the scientific betting syndicates taking on the bookmakers, this is not the aim. Rather, analytics is one more way to get an edge. In sport, as in betting, the best teams don’t get it right every time. But they know how to win more often than their opponents. 

Adam Kucharski is author of The Perfect Bet: How Science and Maths are Taking the Luck Out of Gambling (Profile Books)

This article first appeared in the 28 April 2016 issue of the New Statesman, The new fascism