Asunder by Chloe Aridjis: More interested in being than becoming

Asunder communicates its ideas, and their supporting cultural references, subtly and efficiently.

The second novel by London-based author Chloe Aridjis, Asunder appears on its surface to be about quiet contemplation, and how far it is possible to abstract oneself from the dramas and traumas of social interaction. Claiming not to suffer from listlessness or boredom, protagonist Marie has sought out a job (but not a career) as a museum guard at the National Gallery, working there as "I have always been more interested in being than becoming", killing time by trying to guess how long remains before closing without looking at her watch, or ruminating upon the gradual process of paint cracking.

After nine uneventful years, Marie becomes restless. The sad, quiet death of a 68-year-old colleague, felled by a heart attack at work, jolts her into realising that life is slowly slipping away from her. Her friendship with poet Daniel, fired from the Gallery for noisily pacing around, encourages her to think about his unrequited loves and her own brief liaisons "that didn’t threaten the peace", but when he offers to take her to Paris, she struggles with the potential short-term change to her routine, deliberating for days before taking the trip which irrevocably alters her carefully contained world.

"Painters create order from disorder, but the moment that order has been created, the slow march towards disorder begins again", reflects Marie, and her greatest fear, it seems, is of encounters that will change her situation in any way. Like her, Daniel keeps people at a distance, writing to other poets across the world, preferring not to meet them as this always leads to the correspondence shrivelling; Marie wrote to a prisoner who later escaped from Belmarsh, the realisation that he had her address leading her to panic that he would enter her life in a ruinous fashion (as in Robert Hamer’s It Always Rains on Sunday, about a Bethnal Green housewife whose life is torn apart by this very occurrence). This does not happen, and Marie wonders what became of her penfriend: finally, in Paris, she reaches the uncharacteristic yet inevitable point where she spontaneously breaks out of herself and struggles to connect with an inscrutable stranger.

At its core, Asunder is about time: how slowly it passes, the futility of trying to fight its effects, and generational changes in people and ideas. Besides her memories of vanished shops and her knowledge of different approaches to the restoration of art, Marie often thinks about the history of violence against the suffragettes, as well as her great-grandfather Ted, and the most significant moment of his life as a National Gallery guard, in 1914, when he slipped in trying to catch Mary Richardson, granting her vital seconds to slash Velazquez’s Rokeby Venus in protest against Emmeline Pankhurst’s imprisonment. As a child, Marie heard this story countless times, aware that she was supposed to see Richardson as a criminal but sympathising with her cause, touchingly confessing that "I loved [Ted] just a tiny bit more for not reaching her in time".

Asunder communicates its ideas, and their supporting cultural references, subtly and efficiently. Aridjis is particularly strong on the nature of travel, in London and in general. Her prose is full of deft imagery – such as the way the women "comb the city from [their] hair" on changing into their Gallery uniform – and the moment where Marie becomes aware that she has become "captive to that irrational behaviour in foreign cities when you feel everyone is watching when in reality not a soul has noticed your existence" is especially touching.

The influence of nouveau roman authors such as Marguerite Duras and Nathalie Sarraute, and British counterparts Ann Quin and Christine-Brooke-Rose can be felt in the rarefied focus on the narrator’s interior world, her corresponding observations of the mundane realities of so much human behaviour, and the way in which her narrative slowly builds towards a climax that changes her life without feeling life-changing. As a reminder that life will pass you by if you choose to experience it passively, however, Asunder is far more powerful than it immediately seems.

Protagonist Marie takes a job as a museum guard at the National Gallery. Photograph: Getty Images.

Juliet Jacques is a freelance journalist and writer who covers gender, sexuality, literature, film, art and football. Her writing can be found on her blog at and she can be contacted on Twitter @julietjacques.

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