We Steal Secrets rightly restores Bradley Manning to the centre of the WikiLeaks story

Alex Gibney's WikiLeaks documentary rightly celebrates Bradley Manning, while at the same time providing plenty of ammo for Julian Assange's many critics.

We Steal Secrets: the Story of WikiLeaks (15)
dir: Alex Gibney

Until a few years ago, the description of a public figure as a “crazy, white-haired Aussie dude” would likely have called to mind Sir Les Patterson, the sozzled Australian cultural attaché created by Barry Humphries. In We Steal Secrets: the Story of WikiLeaks, the silver-maned nut job we are presented with is Julian Assange. Whether his personal conduct towards women gives him something else in common with Sir Les is one of several questions that Alex Gibney can only raise without any hope of answering conclusively.

It’s regrettable that Assange didn’t consent to an interview – or, at least, to one that wasn’t accompanied by a $1m price tag. On the whole, Gibney (who directed Enron and Taxi to the Dark Side, about the murder of an Afghan cab driver by US soldiers) has made the best of what he’s got. Most importantly, the picture restores to the centre of the narrative Private Bradley Manning, a genuine hero not at liberty to take advantage of the hospitality of the Ecuadorian embassy.

Gibney traces Assange’s subversiveness back to his involvement in the Wank Worm, which sounds like a subject for a post-watershed edition of Gardeners’ Question Time but is actually a virus (“Worms Against Nuclear Killers”) used by Australian hackers to destabilise Nasa computer systems in the late 1980s. For the film’s first hour, Assange is presented as quite the folk hero. He set up WikiLeaks as a confidential drop box for secrets requiring urgent disclosure; an early success for the site was its revelation about suspicious practices at Icelandic banks, which prompted riots by a people not renowned for their fury, Björk aside.

Entering the story stage left, burdened with secrets personal and governmental, is Manning, a guilt-ridden innocent who resembles a smudge of Angel Delight with acne. Among the classified videos he passes anonymously to WikiLeaks is one of a US air strike on Baghdad by whooping, adrenalised soldiers who appear to be under the impression that they’re playing Call of Duty. Eleven people died in that sustained attack, including a father driving his children to school and two members of Reuters staff whose cameras were mistaken for weapons.

While the reach of Assange and WikiLeaks is represented in the film by images of lines latticing the globe, Manning’s words are rendered entirely in a lonely ticker tape of computer type, the cursor blinking plaintively at the end of each line. (His username, bradass87, is touchingly aspirational in the special way that only usernames can be.) Asked by Adrian Lamo, the hacker to whom he reaches out and who ends up shopping him to the authorities, why he has turned whistle-blower, Manning types: “I . . . care?”

We Steal Secrets is correct to celebrate Manning. But it’s obvious from the roll call of interviewees, which includes a number of people who believe they’ve been wronged by Assange (such as his former partner-in-espionage Daniel Domscheit-Berg), that any bias will not be favourable to the WikiLeaks founder. Admittedly, he doesn’t help matters. From colossal errors (refusing to confront fully the allegations that he sexually assaulted two women) to trifling ones (there’s some unflattering footage of him bullishly contradicting Domscheit-Berg in public or disingenuously expressing a discomfort with being photographed), he has supplied much of the ammo for his character assassins.

What the film doesn’t convey is the possibility that only someone of Assange’s personality type could have engineered something as revolutionary as WikiLeaks (even if his approach to life-saving redactions in classified documents could be cavalier). Just as Assange’s misjudgements threaten to sully the good name of WikiLeaks, so it only takes a few indulgent flourishes by Gibney to shake our faith in his methods. A superfluous interlude reconstructing a night in the life of James Ball, a former WikiLeaks employee, suggests that Gibney harbours ambitions to make moody pop promos for Radiohead. And it can only weaken the movie’s charges against Assange to play in slow motion footage of him boogieing appallingly at a party. Impugn his integrity by all means. Savage his character. But don’t show the world his white man’s overbite and his dad-like dance moves.

Mystery man: Julian Assange emerges onto the balcony of the Ecuadorian Embassy. 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.

This article first appeared in the 15 July 2013 issue of the New Statesman, The New Machiavelli

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