Gilbey on Film: the greatest movie scores

And does "A Single Man" boast this year's finest music?

If you find yourself losing faith in the subtlety of film music, allow me to suggest a few composers with restorative powers. Like the couple in a recent New Yorker cartoon who stroll unwittingly from the pastures marked "rock" through to "pop" and then "easy listening" (caption: "They never even knew"), the once-intriguing Danny Elfman, a regular Tim Burton collaborator, has lapsed -- perhaps irretrievably -- into mediocrity.

But Carter Burwell is still on the money. Burwell is best known for his work with the Coen brothers -- he's scored every one of their films, from 1984's Blood Simple to last year's A Serious Man.

My favourite scores of his can be heard in Rob Roy (this is how good he is: he makes Celtic pipes palatable), Adaptation and especially Before the Devil Knows You're Dead (where Burwell was called in at the 11th hour to replace another composer's score).

I was going to add The Hi-Lo Country: I can still hum that one despite not having seen Stephen Frears's film for over a decade. But on reflection, it's not a good fit. It's very grand and rousing, whereas those descriptions don't pertain to anything in the characters or story; you can't tell what the music is expressing.

It's not Burwell's fault, nor is it a slight on his work. Pure speculation alert: I wonder if the music was brought in once everyone realised that no one in the movie was particularly heroic, nor did they want to be. The idea may have been to get the audience excited, and hope they wouldn't realise until they got home that there was nothing on screen to be excited about.

Surely a fundamental rule of any score is that it has to have a correlation to what we're watching; otherwise it floats free of the movie, and can be as incongruous as an unnatural light source or a visible boom mic. Stuart Staples of Tindersticks has done some incredible work for Claire Denis, including her new film White Material (which I review in the next NS).

Check out the Tindersticks' score for Denis's last film, 35 Shots of Rum, where it ebbs and flows in gorgeous synchronicity with the performances, camerawork and editing -- a model not only of how to compose great film music, but of how to weave it into the action.

I also rest easy when I see on the opening credits of a film the names Alexandre Desplat (best scores: Birth and Lust, Caution) or Mychael Danna (The Ice Storm, Capote and 8MM -- the latter a classic case of great score/dud movie).

A contender for the finest film music of this year is the score for A Single Man, Tom Ford's adaptation of Christopher Isherwood's novel about a gay professor in early 1960s Los Angeles, mourning the death of his lover. (The film has just been released on DVD.) I should clarify "finest" by explaining that this score seems to emerge fully and organically from the movie, with no suggestion that it wasn't in fact generated spontaneously by the images, or vice versa.

"The music was an extension of George," Ford told me last year.

I was thinking about it as I was writing and shooting. Violins I knew I wanted to be prominent because they're the most human instrument; they can convey the most incredible sadness and also joy. Shigeru Umebayashi, a brilliant Japanese composer, wrote three pieces; he works with Wong Kar-Wai a lot, he's incredible. And Abel Korzeniowski is a Polish composer in Los Angeles, he's also incredible: he scores not just action but emotions. That's a crucial device in helping the audience know what George is feeling. Abel is the difference between someone scoring and just composing. When I was working with him, I was saying, 'This is great, but I need more.' And he said, 'More? Usually I get asked for something that just goes away into the background.' That's incredible! Why have music that just fades away, fills space?

"Often a finished film can be a slight disappointment," Firth chipped in,

or it might go off in a different direction to the one you'd anticipated. But the musical choices in A Single Man conformed to what I felt the film should be. Very rarely have I heard music on a score that reflected what the film felt like to make. If the music is an extension of George's thoughts, then it's bang on. It could not be more right. When I heard it for the first time, I had this strange idea that I'd sung it or something because it felt like it had come out of the character. To feel that this was what Abel was doing, following the thought processes of the character -- well, that really made sense. I want to meet this guy, because I really feel like we worked together. And you almost never feel that.

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