Gilbey on Film: In praise of Billy Wilder

Ten years of after the director's death, it's worth watching <em>The Apartment</em> again.

Billy Wilder died 10 years ago this week. His films, though, have the gift of eternal life. The Apartment, along with Some Like It Hot, is probably the most cherished of these (okay, I'll be completely uncontroversial and say the best). It will be back in UK cinemas in June. This is the second or third re-release of the film that I can remember in the last 15 years. My instinct in these circumstances is to complain about the same old titles being wheeled out again, and to protest that the resources should be splashed instead on digging out the ones that are overlooked or forgotten (such as Wilder's own fascinating and incomplete The Private Life of Sherlock Holmes, which was re-released 10 years ago).

But it's hard to stay gruff for long when faced with The Apartment. Instead I find myself thinking how wonderful it will be to see it again on a large screen. The last time I watched it was on TV a year or two ago. It was three or four in the morning, I was ill, unable to sleep, knocking back the Lemsip. But finding The Apartment on TV was the best pick-me-up of all. It's snappy and jolly but with the unmistakably Wilderesque strains of regret, melancholy and scepticism running through its romance.

The stench of the immoral or the venal in Wilder's work is so potent as to be made tolerable only by the crispness of the storytelling -- if Double Indemnity and Ace in the Hole were not such wildly compelling entertainments, they would plunge us forever into an inescapable pessimism. Wilder's unshowy brilliance, his meticulous x-rays of human fallibility, make great art out of the pitiful. (How he would have hated that: "I don't make cinema," he said. "I make movies. I make movies for amusement.")

Fresh off Some Like It Hot, Wilder, his co-writer, I A L Diamond, and their star, Jack Lemmon, waltzed straight into The Apartment. "While I was working with Mr. Lemmon for the first time on Some Like It Hot," Wilder said in a delightful interview with The Paris Review,

I thought to myself, "This guy's got a little bit of genius. I would love to make another picture with him, but I don't have a story." So I looked in my little black book and I came across a note about David Lean's movie Brief Encounter, that story about a married woman who lives in the country, comes to London, and meets a man. They have an affair in his friend's apartment. What I had written was, "What about the friend who has to crawl back into that warm bed?"

CC "Bud" Baxter (Lemmon) is the poor sap in question. He's rising fast at work, one promotion after another, but the secret of his success is that he loans out his apartment to the company executives for their trysts, one 45-minute slot at a time. It's a sleazy little set-up, and Wilder keeps the movie galloping along so briskly that we can overlook the unpleasantness at first. But then reality starts to creep in as Baxter realises that the woman he longs to bring home in his arms -- chirpy elevator assistant Fran Kubelik (Shirley MacLaine) -- has already been to his apartment, in the company of his boss (Fred MacMurray). The question of how Baxter finds out allows Wilder and Diamond to demonstrate their knack for succinct storytelling: one broken compact mirror is all it takes to make his heart break.

In fact, they are unbeatable at turning out these "moments" -- witness also Baxter's classic straining-spaghetti-through-a-tennis-racket scene, born out of Diamond's realisation that "Women love seeing a man trying to cook in the kitchen."

Such stand-out scenes never impede the film's precise, fluid rhythm. Wilder shot the picture in 50 days flat, and edited it in under a week. "We had three feet of unused film," he said proudly in Cameron Crowe's excellent book Interviews with Billy Wilder. (Read Andrew O'Hagan's lively review of it here. Wilder, you see, had been Crowe's first choice to play Tom Cruise's mentor in Jerry Maguire, a role the late director sadly declined.)

Fifty-seven days! That only enriches the film's miracles. This is lean, funny film-making, expertly paced and played, ending in a romantic flourish to swoon over. It won five Academy Awards, including Best Picture, Best Director and Best Screenplay. Wilder said: "It was ideal for Lemmon, the combination of sweet and sour. I liked it when someone called that picture a dirty fairy tale..." It was, he reckoned, "the picture [of mine] that has the fewest faults."

Billy Wilder. Photograph: Getty Images

Ryan Gilbey is the New Statesman's film critic. He is also the author of It Don't Worry Me (Faber), about 1970s US cinema, and a study of Groundhog Day in the "Modern Classics" series (BFI Publishing). He was named reviewer of the year in the 2007 Press Gazette awards.

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