Reviewed: Mimi by Lucy Ellmann

Under the skin.

Mimi
Lucy Ellmann
Bloomsbury Circus, 352pp, £12.99

The ground beneath our feet is shaky territory for the narrator of Lucy Ellmann’s excellent sixth novel. Harrison Hanafan, an eminent New York plastic surgeon, is walking down Madison Avenue one Christmas Eve when he slips on ice, thereby transplanting himself instantaneously “from the lofty, vertical and intellectual to . . . the lowly and prostrate”.

The irony of having a position of high social status but low morality is explored throughout with great humour. “In Manhattan a man without an upright position hasn’t got a chance,” complains Hanafan, who subsequently wallows in his literal downfall. Yet he is rescued and helped to his feet again by a “plump middle-aged gal with brown eyes” – this is Mimi, a feisty feminist going through the menopause who will, throughout the novel, be not only a physically but also a morally uplifting corrective to Hana­fan’s life.

The plastic surgeon has attempted to shape the contours of his world with the same precision as his knife slicing along flesh; he is, for example, a ferocious list-maker. Among Hanafan’s many lists is a “list of melancholy things”, which is his “life’s work”. There’s a tension between his list-making and what fails to make it on to his lists, a conflict between the attempt to craft and order life and its stubborn insistence on eluding our delineations.

Ellmann unfolds the narrative with aplomb as Hanafan’s romance with Mimi takes him on an emotional journey while he re-evaluates his life. Ellmann’s anger at the mistreatment and subordination of women simmers powerfully throughout her previous five novels; the difference here is that she has channelled that rage through another stylistic device: a male perspective. The reader sees all of Hanafan’s folly and foibles, yet there is also a sense of hope about the possibility of real change – not the superficial changes to the surfaces of human bodies that Ellmann satirises so acutely but psychological and emotional metamorphosis.

This novel is a dissection of what it means to be human and its portraits of human beings are thrown into high relief by sharing the pages with cartoon characters and animals. Hanafan spends his evenings organising his cartoon collection alphabetically, from Alvin and the Chipmunks to Yogi Bear: “Well, what of it? What’s a plastic surgeon supposed to do after a hard day’s work realigning human flesh, if not chill out to scenes of imaginary animals getting punched, stretched, bounced up and down, steamrollered, blown to smithereens, and reborn good as new?” He will learn what it really means to be “reborn”. There is a rescue cat (“The cat really knew how to live!”). There is a sister called Bee. There is pontification on “the heroism of an ant”.

Ellmann’s work is characterised by a delightfully playful style, experimenting with the boundaries of form and the visual layout of writing, and is scattered with capitals and exclamation marks and italics. Here, she liberally uses italics – the full force of emotion pressed against words – as well as pages of music scores. The rich layering of literary and artistic references adds depth to this portrait of shallow lives. In exuberant, exhilarating prose that carries a substantial cargo of humour and wit, this cutting social satire anatomises an era and, by focusing on a man who alters human bodies, offers an X-ray of the curious workings of the mind.

 

“In Manhattan a man without an upright position hasn’t got a chance." Photograph: Getty Images

This article first appeared in the 25 February 2013 issue of the New Statesman, The cheap food delusion

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