Gilbey on Film: Five things I love about La Grande Illusion

Here's why you need to see Jean Renoir's 1938 classic.

La Grande Illusion, Jean Renoir’s sublime 1938 masterpiece about spirit, class and camaraderie in a German POW camp in the First World War, is out in cinemas now in a restored print; it reaches DVD on 23 April. This is a movie that does not want for admirers. Woody Allen counts it as one of his eight favourite films (in case you’re curious, the others are: Bicycle Thieves, The 400 Blows, The Hill, Rashomon, The Seventh Seal, Wild Strawberries and a second Renoir, The Rules of the Game). The late Pauline Kael, interviewed in May 2000 by the director Michael Almereyda for a still-unmade film essay about Renoir, said:

The first Renoir picture I ever saw was Grand Illusion, which was probably the greatest picture I’d ever seen. I was in San Francisco, and it didn’t play in art houses; it played in regular theatres and it got a huge response. It is a movie that people don’t have to be movie specialists to enjoy. I think that The Rules of the Game, which is certainly a great film, could never reach the wide audience that Grand Illusion did in the 1930s when I first saw it. It has an immediacy, and you understand everything in it, whereas The Rules of the Game has a kind of mad capriciousness; the pulse in The Rules of the Game is different—it isn’t as naturalistic—and Grand Illusion was simply a heavenly experience for people who hadn’t seen much in the way of European films. But even if we had, there was nothing comparable to it.

You can read the full text of this interview, which Almereyda planned to use as his documentary’s narration, in Projections 13 (Faber). But Kael is right: it’s one of those films that you can confidently show to a friend, prefacing it with the words “You will adore this” without fear of being contradicted.

In addition to its accessibility, here are a further Five Things I Love About La Grande Illusion:

Jean Gabin

Ahead of the forthcoming Jean Gabin season at the BFI Southbank, you can marvel here at the subtlety and strength of French cinema’s brute poet. As Lieutenant Maréchal, an unpretentious, working-class officer holed up in the POW camp, he had a way of bringing the simplicity and beauty of a sonnet to his every grunted line; his eyes sparkled in his rough-hewn mug like diamonds in a sack of spuds. From raucous humour and stir-crazy intensity through to the unembarrassed tenderness of the final scenes, Gabin was as dexterous as they come. I like the way Maréchal twice reaches for the sentimental during intimate conversations with a colleague or a lover, only to have his declaration cut short by the intended object of his compliment. That feels like a comment on all the softness beneath Gabin’s own sandpaper exterior.

The Framing

Any director wishing to frame a group of actors in a shot needs to look at Renoir in general, and La Grande Illusion in particular. Faces crowded in a window, men huddled together on an allotment to empty out surreptitiously the sacks of dirt from the previous evening’s tunnel-digging, or gathered around a costume box inspecting the delicate female clothing that is the closest any of them can get to an actual woman. All these scenes and shots demonstrate Renoir’s uncanny ability to frame action in a way that expresses his characters’ camaraderie while providing compositions upon which the eye can feast.

The Music

The urgent military tempo of Joseph Kosma’s main title music is echoed later in the film when Maréchal remarks of the sounds emanating from his captors’ parade ground: “It’s not the music that gets to you. It’s the marching feet.” Music is soaked into the picture. Musical instruments play a key part in the action—bugles, a harmonica, flutes and a cacophonous improvised orchestra of clanging pots, pans and plates. An early emotional peak comes when the prisoners burst into a rendition of “La Marseillaise” to celebrate the recapturing of Fort Douaumont by French forces.

A Great Director Before, As Well As Behind, The Camera

I have a personal love of directors who act, and one of the finest was Erich von Stroheim. To be fair, he was an actor before he was a filmmaker—but now that history knows him best as the director of Greed, it is understandable that we should think of acting as his supplementary career. He is devastatingly emphatic as Captain von Rauffenstein, who clings fast to the old certainties of class, breeding and etiquette as the world crumbles around him. Von Stroheim’s moments of greatness in La Grande Illusion are too numerous to list, so I will single out two. First, the way his whole upper body tilts backwards suddenly whenever he swigs his brandy. Second, the torture, played out on his agonised face, as he is called upon to fire on a man he considers a friend and an equal, albeit one fighting for the enemy.

The Final Shot (No Spoilers)

The most quietly magnificent use of snow in cinema.

"La Grande Illusion" is in cinemas now.

 

Jean Gabin, star of La Grande Illusion, in 1975. 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