Sisterland by Curtis Sittenfeld: A modern American fable about the danger of tempting fate

In her latest novel, Curtis Sittenfeld depicts the tedium of modern motherhood a little too well - a gamble she has taken before, but has consistently paid off.

Sisterland
Curtis Sittenfeld
Doubleday, 416pp, £16.99
 
Near the beginning of Sisterland, Curtis Sittenfeld’s latest novel, the twin sisters Violet and Kate are having a fight. Kate, the devoted mother of two small children, is listening with some asperity to what she feels is a deliberate provocation from her free-spirited sister, who announces with studied insouciance that she has begun dating women. While insisting that her resistance to this idea is not homophobic, Kate informs Violet that choosing to be gay will make her life more complicated, especially if she decides she wants children. Violet, who dropped out of university and lives a defiantly unconventional life, is unimpressed by her sister’s frustration at the “sheer choreography” entailed in caring full-time for a baby and a toddler. She tells Kate: “Children are nothing but a problem people create and then congratulate themselves on solving.”
 
This idea, to which Kate returns later in the novel, might be said to comprise the leitmotif of Sisterland: it is about the consequences of self-created problems and the risks of self-fulfilling prophecies. In order to explore these ideas, Sittenfeld bestows upon Kate and Violet psychic powers – what their family calls “the senses” – which become a metaphor for questions about the relationship between choice and destiny. This is a bold, romantic move for Sittenfeld to make in a novel that otherwise seems to find satisfaction in undiluted realism, cataloguing the quotidian details of ordinary American life with near-anthropological interest.
 
The book is narrated by Kate and before long it appears that the almost fetishistic listing of her daily activities – from feeding her children and burping the baby to errandrunning and playground activities – is Kate’s protective ritual: the consolations of the mundane in a life straightjacketed by its efforts to ward off the demons of misrule.
 
Kate has embraced suburban normality in an attempt to repudiate her psychic powers, which she has viewed since adolescence as dark and disturbing. At high school, she has the frightening ability to intuit which of her classmates would die youngest and realises that a girl’s boyfriend is cheating. (This proves awkward for Kate, as it turns out that Violet is the person with whom he is cheating.) When their classmates realise that Kate and Violet have these intuitions, the twins are branded as witches. Kate goes off to university, determined to reinvent herself: she changes her name from Daisy and settles into sorority life and serial monogamy.
 
By 2009, Kate is happily married to a kind, intelligent man who teaches geophysics at the local university and she is facing two problems that shape the novel. First, Kate is a deeply anxious, solipsistic mother, obsessed with her children’s safety and torn between devotion to them and self-pity over the way they dominate her life. Second, Violet has had a premonition and announces that she believes St Louis will be rocked by a devastating earthquake. (This is roughly equivalent to making the same prediction for, say, Kent.) Despite its improbability, Kate thinks her sister might be right, for she has her own impression of an impending disaster. Violet decides to make her fears public to warn the community, although Kate suspects that her motives are also commercial, as she scrapes together a living as a clairvoyant. The media pick up on the story and soon their lives have become a circus, while Kate and her husband find themselves at odds over whether he has ever accepted the reality of the sisters’ gifts. Kate is both embarrassed by her sister’s notoriety and afraid that an earthquake will devastate her family.
 
Sittenfeld cross-cuts Kate’s anxiety as the fateful day approaches with flashbacks of her adolescence with Violet, as they grow up with a depressed mother who dies young and an affectionate but distant father. While fixating on her children, Kate also tries to take care of – if not control –Violet and their father, who make varying demands on her time and attention. And she spends a great deal of time with Hank, a stay-at-home father whose wife is a colleague of Kate’s husband at the university. Gradually, her anger and resentment, suppressed since high school, begin to simmer to the surface.
 
It is only through the glimpses we get of Violet – flamboyant, intelligent, defiant – that Sittenfeld suggests there might be a life less ordinary in the margins of this book. The risk Sisterland runs is the affective slippage that can happen with any rebarbative subject in fiction, when the novel becomes infected by the flaws of its protagonist. The trick of the dramatic irony in which Sittenfeld specialises is to ensure that there is a discernible gap between, for example, a story about stupid people and a stupid story or a story about boredom and a boring story. As is the case in all of Sittenfeld’s fiction, her characters are neither stupid nor boring but Kate is perhaps the most riskily tiresome of her protagonists, a woman blind to her shortcomings but without the redemptive charm of self-deceptive characters such as Jane Austen’s Emma.
 
Sittenfeld may depict the tedium of young motherhood a little too well for readers in search of entertainment. This is a gamble that she has taken before and it’s paid off, in novels from her debut, Prep, about a girl trying to fit in at a competitive boarding school, to American Wife, her widely acclaimed portrait of a young woman who grows up be First Lady Laura Bush in all but name.
 
In Sisterland, Sittenfeld throws in a plot twist that is, as Kate says, “a situation from a soap opera”. The problem is not only that what happens to Kate is improbable but that the woman we have come to know is precisely the person who would never make the choice that drives the story to its conclusion. The shift from the all-too-believable to the implausible is too abrupt but the questions it raises about self-fulfilling prophecies remain compelling. In the end, Sisterland is a modern American fable about tempting fate and in it Sittenfeld shows that she is willing to practise what she preaches.
Tempting fate: The novelist Curtis Sittenfeld. Photograph: Artz/Laid/Camera Press.

This article first appeared in the 29 July 2013 issue of the New Statesman, Summer Double Issue

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