Reviews round-up

The critics’ verdicts on the latest books by Orlando Figes, Colm Tóibín and P D James.

Crimea: the Last Crusade by Orlando Figes

Angus Macqueen in the Observer praises "Figes's lucid account of three years of bloodletting in the Black Sea", whose chief merit resides in "attempting to place the Crimean war as the fulcrum of 19th-century Europe between Waterloo and the First World War". "With his deep understanding of Russia and its uncomfortable position in the world, Figes elegantly underlines how the cold war of the Soviet era froze over fundamental fault lines that had opened up in the 19th century."

For Mark Bostridge, writing in the FT, "The book's true originality lies in its unravelling of the Crimean war's religious origins." The rivalry between the Catholics and the Greeks, backed by France and Orthodox Russia respectively, "is represented as the vital spark igniting the conflagration that followed". The author of Florence Nightingale: the Woman and Her Legend (Penguin) finds less convincing other aspects of Figes's book, including his characterisation of Florence Nightingale, which "relies on tired old sexist taunts".

Oliver Bullough in the Independent acknowledges that he is not unbiased: Bullough's book Let Our Fame Be Great was the only one to be reviewed positively by Figes, who savaged all other rival accounts of the Russian Revolution in comments "unwisely" posted on Amazon. While recognising that "it is not a perfect book, and his sourcing can be erratic", he concludes that Figes's "lucid, well-written" account is "the only book on the Crimean war anyone could need".

"Crimea: the Last Crusade" will be reviewed in the next issue of the New Statesman.

The Empty Family by Colm Tóibín

For Hermione Lee in the Guardian, the "stories in The Empty Family – like the painful stories of family conflicts in his last collection, Mothers and Sons – are threaded through with regret and need". A few "soggy moments" set aside, Tóibín's "scenes of longing for lost family homes or missed landscapes" are admirable in their "dramatic economy". Lee sees the depiction of "women's interior lives" in particular as "one of Tóibín's great strengths".

Keith Miller in the Telegraph comments on "a certain autobiographical element: in the characters' age, sexuality, nationality and profession". "But from the particular crucible of his own life," she writes, "Tóibín has forged something of wider, if not quite general, interest: a schedule of the principal torments available to the educated, left-leaning, upwardly mobile, male baby boomer in middle age."

David Mattin in the Independent notes the "deep-running concern for modernity, and the spiritual deformations that it visits on us", underpinning the nine short stories in Tóibín's collection. "Running deep beneath the stories is a concern for our new, modern rootlessness, and the collapse of old certainties."

Talking About Detective Fiction by P D James

Edmund Gordon in the Observer, thinks that, "As a personal (and gleefully partial) survey of the highlights of English detective fiction over the past 200 years, her book offers much that will enlighten and entertain." He is less convinced by her claim that "the genre has been unfairly stigmatised by critics, and is as worthy of academic attention as any other kind of writing". But her "modesty", combined with "intellectual vigour . . . make it impossible not to take [her views] seriously".

For Amanda Craig in the Independent it is "P D James's longevity, as well as her serene intelligence, that makes this book especially noteworthy and enjoyable, for at 89 she has grown up with the Golden Age of detective fiction as well as made a substantial contribution to it".

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