Blogging the London Film Festival: the highlights

Ten to watch, as recommended by us

The 53rd London Film Festival begins on 14 October. Among the hundred-plus films drawn from around the world are the latest Coen brothers comedy, a biopic of the poet John Keats and not one, but two, films starring George Clooney. Over the coming weeks, the NS culture team will bravely attend as many screenings as possible and blog about it here. In the meantime, here is our pick of ten highlights to whet your appetite:

Fantastic Mr Fox (dir: Wes Anderson)

Anderson, director of quirky comedies such as The Royal Tenenbaums, makes his first foray into animation with this adaptation of Roald Dahl's classic children's story.

The White Ribbon (dir: Michael Haneke)

The Austrian-born Haneke has long been known for his punishing films, but his last, Funny Games, proved a little too much for our own Ryan Gilbey. Will this tale of malice and spite in early-20th-century Germany fare any better?

Bluebeard (dir: Catherine Breillat)

Famously retold by Angela Carter in her story collection The Bloody Chamber, this fairy tale gets a low-budget treatment from the provocative Breillat.

Tales from the Golden Age (dir: Cristian Mungiu)

The 20th anniversary of the fall of communism is being marked by various arts projects. Here, the acclaimed Romanian director Mungiu presents a series of vignettes of life under Ceausescu. You can read the NS review of his previous film, 4 Months, 3 Weeks and 2 Days, here.

Oil City Confidental (dir: Julien Temple)

After giving us documentaries on the Sex Pistols and the Glastonbury Festival, Temple turns his attention to Britain's much-maligned pub rock scene.

She, a Chinese (dir: Xiaolu Guo)

Guo is better known for her novels (the most recent of which we reviewed here), but she is also an accomplished film-maker. She, a Chinese tells the story of a young immigrant in Britain and features a score by John Parish, the PJ Harvey collaborator.

Hadewijch (dir: Bruno Dumont)

With a visual style that has more in common with the painters of his native Flanders than any of his contemporaries, Dumont cuts something of an outsider figure in French cinema. Hadewijch is tipped to be his best work yet -- while you wait for it, read this 2007 NS interview with the director.

Journey to the Moon (dir: Kutluğ Ataman)

Ataman, who was nominated for the Turner Prize in 2004, may be better known to NS readers as a video artist -- Fisun Güner wrote about him in April. Journey to the Moon reconstructs an incident from 1950s Turkey.

Perestroika (dir: Sarah Turner)

Structured around a journey on the Trans-Siberian Express, this exploration of amnesia is a promising highlight of the festival's experimental film strand.

Bad Lieutenant: Port of Call New Orleans (dir: Werner Herzog)

Herzog, the visionary German director who has been making films since the 1960s, is enjoying a late surge in popularity. This remake of a 1992 Abel Ferrara crime drama, starring Nicholas Cage, is a departure from his recent run of documentaries. You can read our Q+A with the director here.

Daniel Trilling is the Editor of New Humanist magazine. He was formerly an Assistant Editor at the New Statesman.

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