Careless People by Sarah Churchwell: The glamour and grimness of Gatsby

Sarah Churchwell's Careless People is as mixed and inclusive as F Scott Fitzgerald’s scrapbooks. Both offer 1922 as the chief exhibit to explain the jazz age.

Careless People: Murder, Mayhem and the Invention of The Great Gatsby
Sarah Churchwell
Virago, 448pp, £16.99

F Scott Fitzgerald wrote his greatest novel in France in 1924, having exiled himself in order to get some work done. But during those ten months of intense writing, he thought his way back to the parties, quarrels, hopes and disappointments of his life with Zelda and their friends on Long Island in the feted and fateful year of 1922.

This is the world that Sarah Churchwell reconstructs for us as she lays out the raw materials from which The Great Gatsby was made. We meet the people Fitzgerald met: newspaper tycoons such as Herbert Swope and entrepreneurs such as Larry Fay, who made his money from liquor and taxis (and smuggling liquor in taxis) and spent it on his rainbow collection of beautifully tailored shirts. We start to learn the ropes of 1920s Manhattan: the colour of taxis, the customary length of skirts, the modish vocabulary. Eventually, we feel we might just telephone through to the Fitzgeralds (ask the operator for Great Neck 740). Dialling codes and lexicons – these details matter. The first readers of Gatsby thought it was all about themselves, a book of the moment. Today, we tend to admire its enduring mythology of aspiration and undoing. Churchwell brilliantly brings these two perspectives together as she holds in counterpoint the sprawling stuff of Fitzgerald’s daily life and the gleamingly taut prose poem that emerged from it.

It is too easy, Churchwell warns, to make simple equations between fiction and reality. She deals instead with hauntings, doublings and reverberations. The enigmatic green light across the dock, to which Gatsby stretches out his arms, is not literally related to the traffic lights recently erected in Manhattan. Yet there is just a shadow of shared meaning, a shadow that deepens and enriches the enigma.

The jazz age documented here is sadder and less glittering than Baz Luhrmann would have us believe in his new film of The Great Gatsby. Churchwell evokes the allure of the speakeasies but also the seediness of an underground world run by crooks without compunction: “Speakeasies had false fronts, barrels had false bottoms, drunk drivers gave false names to the police and upstarts depended on making false impressions.”

Fitzgerald conjugated the verb “to cocktail” but tired of the game after reaching the conditional subjunctive. The continuous round of drinking could turn, likewise, from pleasure to tedium. There is a photograph of a party at the Fitzgeralds’ house in which the guests look weary. “Where is the magic?” asks Churchwell. Where, indeed? As the parties went on through 1923, Fitzgerald had a sense of repetition and disintegration. “February: Still drunk . . . April . . . Another fight. Tearing drunk,” he noted in his ledger. He summed up the mood in a marginal note: “No ground under our feet.” There was nothing inherently enchanted about these lives. In his fiction, Fitzgerald kept writing about the awful realisation that magic cannot always be summoned.

Knowing that the good times would pass, desperately needing facts that would ground him, Fitzgerald saved things up. This was his counter to the carelessness of his milieu. He kept ledgers and scrapbooks, he made lists, he preserved cuttings. He had a profound need to archive and Churchwell takes her cue from him as she sorts through the flotsam of his life, honouring his curious relics. Here is a photograph of Zelda in the snow, faded to ghostliness. Here are notes on the back of a dinner menu, a yellowed rhyme saying “Flappy New Year”, a Fitzgerald autograph ready to cut out and keep.

Careless People is as mixed and inclusive as Fitzgerald’s scrapbooks. There are both glamour and grimness here. Even the typography varies between chic deco lettering and the blotchy ink of newspaper headlines. If Churchwell’s book is biography, literary criticism and social history, it is also a work of “detective non-fiction” that might be compared with Kate Summerscale’s The Suspicions of Mr Whicher. The unfolding story of a long, botched murder trial is woven into every chapter, getting stranger and stranger by the page, exposing corruption, envy and ambition of many kinds. A shooting under an apple tree in New Brunswick doesn’t at first sound congruous with Gatsby but it comes to stand as a “phantom double” of the novel’s murderous denouement. The sordid and the tragic become difficult to tell apart.

The police investigating this murder were blunderers who let tourists walk all over the crime scene. The truth went missing, carted off by souvenir hunters. As Nick Carraway says at the end of Gatsby, “It was all very careless and confused.” Churchwell, on the other hand, demonstrates how careful detective work is done.

Fitzgerald offered the year 1922 as the chief exhibit when he tried to explain the meaning of the jazz age. It is an exhibit worth looking at very carefully. Careless People does so with a mixture of patience and panache and it would take a long time to get bored of that particular cocktail.

Churchwell evokes the allure of the speakeasies but also the seediness of an underground world.

This article first appeared in the 10 June 2013 issue of the New Statesman, G0

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