Reviews Round-Up

The critics' verdicts on Christopher Hitchens, Michael Chabon and Ian McEwan.

Mortality by Christopher Hitchens

Published eight months after his death, this collection of observations about what Hitchens called “living dyingly” are drawn from the Vanity Fair pieces that he wrote throughout his illness. John Lloyd, writing in the Financial Times, observes that “Hitchens’ wit doesn’t desert him till the last few fragmentary notes made in the last few sinking days; nor does his sense that he has, after all, been somebody, made it big in the most competitive arena of the most competitive country in the world.”

In the New York Times, Christopher Buckley calls the first seven chapters of the book “diamond-hard and brilliant” and offers a poignant description of the fragmentary jottings which make up the eight and final chapter: “they’re vivid, heart-wrenching and haunting — messages in a bottle tossed from the deck of a sinking ship as its captain, reeling in agony and fighting through the fog of morphine, struggles to keep his engines going.”

In the Guardian, Colm Tóibín calls the memoir “sad and oddly inspiring” and adds that Hitchens “writes with a calm and searching honesty about the idea that “I don’t have a body, I am a body.” He concludes with the claim that Hitchens “does everything to make sure that his voice remains civilised, searching and ready to vanquish all his enemies, most notably in this case the dullness of death and its silence.”

A review will appear in the next issue of the New Statesman.

Telegraph Avenue by Michael Chabon

The title of Chabon’s first novel in five years refers to the famous Telegraph Avenue that bridges Berkeley and Oakland, California. The jacket refers to it as a "Californian Middlemarch".

Michiko Kakutani writes in the New York Times that “[Chabon] draws an extraordinarily tactile, Kodachrome-crisp picture of the Bay Area world that his characters inhabit… while conjuring the music from the ’50s, ’60s and ’70s that [they] love so much and that has given them their vocation. The result is a novel with the grooviest soundtrack since High Fidelity.” She goes on to say that “although the novel gets off to a somewhat sluggish start, it soon achieves escape velocity, demonstrating that Mr. Chabon can write about just about anything… and write about it not as an author regurgitating copious amounts of research, but with a real, lived-in sense of empathy and passion.”

“In keeping with a novel full of jazz, the prose glimmers with accidentals, chromatic flats and sharps and syncopated rhythms,” says The Scotsman, “this stylistic virtuosity would nevertheless be meagre unless it was harnessed to specific ethical and empathetic ends. And Telegraph Avenue is a big book in an almost 19th-century manner; it has births and deaths, separations and reconciliations, the loss of virginity and the loss of friendship, moments of madness and sudden clarities. It is, above all, about consequence and forgiveness. The final pages are genuinely remarkable in their ability to create closure without compromising on emotional complexity.”

Sweet Tooth by Ian McEwan

Catherine Taylor, writing in the Telegraph, describes McEwan’s latest novel as “a genial, if flawed, foray into John le Carré territory – a wisecracking thriller hightailing between love and betrayal, with serious counter-espionage credentials thrown in.” Eileen Battersea in the Irish Times simply calls it a “glib beach read, marred by stagy dialogue,” and “a middlebrow spy spoof stuffed with self-regard.”

A review in the Economist declares that it is “not Mr McEwan’s finest book” and adds that, despite being “clever”, it is also “curiously forgettable. What it lacks is not so much an animating spirit, as a heart”.

Leo Robson, writing in the New Statesman, notes that the book “contains a certain amount of reflection on reading and writing, offered in the form of an ongoing argument between Serena and Tom which follows to an almost caricatural degree McEwan’s well-established version of the male-female dynamic . . . The couple disagree about modern fiction 'at every turn', and always for crass, gender-essentialist reasons.” Robson writes that “[Sweet Tooth] is a riddle, or perhaps a joke, in which a number of baffling, even boring, elements are clarified and justified by a final flourish. It rewards rereading, but not reading.”

Ian McEwan Photograph: Getty Images
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