Reviews Round-Up

The critics' verdicts on J. K. Rowling, Edna O'Brien and David Byrne.

The Casual Vacancy by J. K. Rowling

After praising her attempt to overcome the Potter legacy and tackle something new, the New York Times’s notoriously sharp-tongued critic Mitchiko Kakutani gives J. K. Rowling’s new book a signature dressing down: “Unfortunately, the real-life world she has limned in these pages is so willfully banal, so depressingly clichéd that The Casual Vacancy is not only disappointing – it’s dull.” Kakutani sees the characters as underdeveloped and the “circumscribed lives” of Pagford’s inhabitants technically weak by comparison to the world of Harry Potter where “identity is as much a product of deliberate choice as it is of fate.” A bit more like America then? If the novel’s grim reality disappointed Kakutani, it positively enraged Jan Moir, who saw it as “nothing more than 500 pages of relentless socialist manifesto masquerading as literature crammed down your throat.”

However, Boyd Tonkin sees something liberating in J. K. Rowling’s writing about young people, now it is no longer constrained by the censorship required of literature for children: “Rowling’s writing, which can be long-winded and laborious in the clunkily satirical set-pieces, picks up passion, verve and even magic with Krystal and the other adolescents. Indeed, the teens of Winterdown belong in a bolder, richer book than some of the parental caricatures.” George Eliot is a name being floated (The New Yorker dubbed the book “Mugglemarch”) by way of comparison – a woman with keen moral instincts and sharp insights into small-town life, something which Theo Tait in the Guardian sees as the book’s central achievement. “It’s a book that wrestles honourably and intelligently with big moral and political questions, but does so in a slightly clunky and convention-bound way,” he writes. “If you’re irritated by important episodes being telegraphed with phrases such as ‘But then came the hour that everything changed,’ then this is probably not the novel for you. But equally, it offers something more stylish, highbrow fiction often doesn’t or won’t: a chance to lose yourself in a dense, richly peopled world.” Read Margaret Drabble's review in the New Statesman later this week.

Country Girl by Edna O’Brien

Mary Robinson, former President of Ireland and UN Commissioner for Human Rights, remembers as a teenager “reading, hidden under a false cover, a dog-eared copy of The Country Girls,” Edna O’Brien’s controversial breakthrough novel of aspiration and female sexuality, “that one of my schoolfriends had managed to get a hold of and passed around among us, and being astonished that she would write these things, and somehow grateful for the insights and revelations the books held.” Mary Kenny sums up the O’Brien “enchantments” which glisten through the book in the Irish Times: “The lushness about nature; the delicate balance of rapture and rupture in recapturing the experience of love; the feminine eye for clothes; the true ear for a story; the sharpness of specific recollections.” Both note the stars with whom O’Brien spent her time in London, entertaining at her home in Carlyle Square – Robinson finding the name-dropping cloying, Kenny the opposite. Rachel Cooke wrote in yesterday’s Observer that “The book falls away as O’Brien grows older; there are repetitions and the writing becomes gluey, more opaque.” Though she quickly counters, “But this hardly matters. The first half is so wonderful, crystalline and true, it seems churlish to complain.”

How Music Works by David Byrne

In Peter Aspden’s FT review of the former Talking Heads frontman and latter day polymath’s new book How Music Works, emphasis is placed on the pie charts, numbers and fiscal reassessment of an illustrious career in music. “The chapter on the economics of music should be required reading for all 16-year-olds tinkering with their GarageBand software and dreaming of dollar signs,” Aspden writes, “while the section on ‘How to Make a Scene’ is nothing less than a manual for urban regeneration through pop culture.” A sometimes memoir sometimes essay collection, what the book appears to lack in autobiographical insight is supplanted with an unflinchingly anatomisation of the musician’s life: the author as data. “It’s a big undertaking, which Byrne approaches with encyclopoedic zeal, drawing on testimony from historians, neuroscientists, philosophers and, in looking at the industry, managers and executives,” writes Fiona Sturges in The Independent. She praises the book in particular for its focus on the reality of a life spent making music without the domineering pop personalities and rock star posturing, a fascinating hodgepodge of authoritative opinion and fact. “[Byrne’s] book offers a meticulously researched and hugely absorbing history of music, focusing on the practices rather than the personalities that have led it to where it is today.”

Margaret Drabble and Edna O'Brien in 1966.
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