Michael Haneke's "Amour" and the music of time

A thought-provoking portrayal of the realities of nursing a partner in deteriorating health.

Amour (12A)
Michael Haneke

Anyone purchasing the soundtrack to Michael Haneke’s Amour before seeing the film would get a comically misleading impression of the director’s use of music. It isn’t that the album’s track listing is incorrect. There is indeed Schubert and a selection of Beethoven’s Bagatelles. But every piece included in Amour is curtailed after only a few seconds by an abrupt cut, or by someone saying: “Switch it off.” (An early title for the picture was The Music Stops.) The sense of pleasure thwarted is overwhelming and appropriate for a film in which a woman’s means of communication are stemmed, her life foreshortened, after she suffers a stroke.

Anne (Emmanuelle Riva), who is in her eighties, is sitting at the kitchen table when she experiences a break in perception. One moment she and her husband, Georges (Jean- Louis Trintignant), are talking, the next she is gazing at him uncomprehendingly; it’s as though she too has been switched off. Following surgery, she is left paralysed in one side of her body. “It will go steadily downhill for a while,” Georges tells their adult daughter, Eva (Isabelle Huppert). “And then it will be over.”

Like Georges, Haneke is not someone to whom you’d turn if you wanted the truth broken gently. He lacks, shall we say, a certain bedside manner. The cruelty of the world he depicts is not tempered by reassurances; his is a form of tough love. The White Ribbon (village plagued by unattributable acts of violence), The Piano Teacher (woman terrorised by her mother performs degrading, self-harming acts), Benny’s Video (parents cover up a murder committed by their desensitised son) – each of these films would lose their air of appalled horror if Haneke didn’t mourn implicitly the sufferings and shortcomings on show.

Amour is different. Haneke is no less stringent now as a film-maker – a quick browse through a photograph album is the nearest Georges and Anne get to a soft-focus montage of marriage highlights. But his emphasis in Amour is on love and loyalty as positive counterpoints to mortal tortures. Even when the couple bristle at one another, or Georges loses his temper, the tension illuminates the capacious dimensions of their life together – the depth and breadth of their marriage. Partly this is the result of putting performers as profound as Riva and Trintignant in front of the camera. To whom can you look for actorly eloquence if not the woman who shouldered much of the emotional weight of Alain Resnais’s Hiroshima Mon Amour (1959), and the man who embodied refrigerated rage in Bernardo Bertolucci’s The Conformist (1970)? We believe in their long marriage not only because they are superb actors working from a note-perfect screenplay; there is also a lifetime’s tenacity shining through Trintignant’s husk-like face, a well of memories in Riva’s eyes. In a film frugal with music, everything still depends on this duet.

Music has always been central to Haneke, whether he has used it to terrorise (the screeching death-metal audible to us, but not to the sweetly smiling family on screen, at the start of Funny Games) or hasn’t used it at all (Hidden, his most admired film, is so unsettling partly because it includes no music whatsoever). It is in every way pivotal to Amour. Georges and Anne are retired music teachers who share an elegantly sombre Parisian apartment, shot with respectful warmth by the cinematographer Darius Khondji. The piano in their study is played only twice (once in a hallucination or memory). In its big close-up, there is noise rather than music emanating from its vicinity: the piano simply stands there while the cleaner vacuums around its legs. It is no more able to participate in the action of the scene than the paralysed Anne can object to having her hair brushed roughly by an unfeeling nurse. What a waste. The woman and the piano, that is.

Though music is rarely heard in Amour, it is often discussed. One of Anne’s former students (played by the pianist Alexandre Tharaud) visits to tell her about his recording work but neglects to bring his latest CD – another instance of music placed beyond Anne’s reach or denied outright. After Anne’s operation, Georges attends a funeral where, he later recounts, someone plays a tape-recording of the Beatles song “Yesterday”. The story rightly invites our disdain: this is not, after all, a nostalgic film. There’s no suggestion that, yesterday, all Georges and Anne’s troubles seemed so far away, only that they possessed the strength to cope with them back then (which admittedly doesn’t scan nearly as well).

The reality of nursing a partner in deteriorating health must be cushioned by the couple’s rarefied climate. Georges can produce €800 to pay a carer’s bill without noticeable pause, while Eva issues investment advice to her mother. But fortification in Amour is ultimately emotional rather than financial. The apartment, from which the film never strays after the first five minutes, becomes a symbol of that security. The picture begins with the front door being broken down but the onset of illness is more insidious.

Prior to Anne’s stroke, the couple find that the lock on their door has been tampered with inexpertly by a would-be burglar. Anne’s friend was the victim of a more successful violation: intruders gained access to the apartment building via the attic. You might say Anne is brought low in much the same way. In Amour, the home is no less pregnable than it was in Funny Games or Hidden, but now Haneke has moved out of the inhibiting genre of thriller and into a higher metaphorical register. The threat posed in Amour is not to family or morality but to life itself. Love, rather than any sophisticated security system, stands Anne and Georges in good stead against death, the ultimate housebreaker.

 

Jean-Louis Trintignant and Emmanuelle Riva in Michael Haneke's "Amour".

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.

This article first appeared in the 19 November 2012 issue of the New Statesman, The plot against the BBC

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