Justin Bieber is a glorified Furby. Why do we expect him to have views on the Holocaust?

We need much more of a Henry VIII-style attitude to celebrities – less adulation, and more “amuse me minstrels and if you’re very, very good I might not have you executed”.

 

As a Jew and a descendent of Holocaust victims, I’m a kind of a very minor stakeholder in Anne Frank. So did Justin Bieber’s misplaced, slightly clunky, maybe self-absorbed, maybe just awkward comment about hoping that Anne Frank “would have been a belieber” ‘offend’ me? Not particularly. Trying hard to be offended ... still trying. Nope, it just won’t come.

It’s slightly crass and it made me cringe. But it baffles me that anyone would be shocked by a teenager blurting out silliness. There was even something quite sweet about Bieber’s comment. He was clearly moved by the story of Anne Frank. He just had a childish way of showing it. Sort of like a puppy pooing on the carpet then wagging its tail excitedly, as if to say, “Look at what I did! Aren’t I clever?”

So when Twitter found this flopsy puppy of a young Canadian guilty of being the Worst Person Ever, I was left shrugging. Why, I found myself asking, do we suddenly expect entertainers to be thinkers?

Bieber is 19. For a variety of misbegotten reasons, he has a Twitter following bigger than the entire population of Canada. He makes a grotesquely good living out of singing and dancing. Why this means his “views”, trite or otherwise, apparently matter is beyond me. It seems that the parents of his fans are so thrilled about their kids listening to music by someone who doesn’t swear or do drugs that they’ve decided to let him raise them. Suddenly a not-too-bright teenager’s naïve take on the Holocaust is subject to the same analysis as a speech made by a world leader.

Kim Kardashian faced a similar Twitter outrage explosion last year when, during a critical moment in the Israel-Hamas conflict, she tweeted, “Praying for everyone in Israel”, which was quickly followed up by a redemptive, “Praying for everyone in Palestine and across the world!” It’s easy to get snotty about the ponderances of such a nonentity (albeit a famous one). But why anyone would ever look to a reality TV star for an intelligent insight into one of the world’s most complex political situations is baffling. Even more puzzling is why anyone would get in a disappointed huff when she proves to be more garden gnome than Noam Chomsky.

Celebrity worship has reached a point where we expect glorified Furbies like Bieber and Kardashian to morph into divine sayers of worldly truths, purely because of their popularity. I expect that the vast majority of “beliebers” listen to Bieber’s music, enjoy it, and couldn’t care less about the guy’s opinions.

When I was a teenager, I practically worshiped Yeah Yeah Yeahs lead singer, Karen O. I was a confused queer girl with low self-esteem and she was a gutsy, punk goddess. So when, in a recent interviewwith the Guardian she claimed never to have been into “the whole feminist movement or anything like that” it upset me to think how much of a blow this would have been to the 17-year-old me.

The same goes for Morrissey, another musical hero of mine, who’s constantly dropping great opinion turds. As it happens, I found the former Smiths frontman’s assertion that wars are “heterosexual hobbies” a lot more offensive than Justin Bieber’s Anne Frank faux pas. If you grant a celebrity role model status, you’re nearly always doomed to be disappointed.

The ludicrous idea of attaching importance to the political views of entertainers can be traced back through the garishly self-righteous Sting/Bono brigade to John Lennon.

“Give Peace a Chance” was seen – and still is by some – as some kind of Ghandian insight but it’s more like something Saatchi and Saatchi would have come up with if they’d been hired by CND rather than Margaret Thatcher. It’s a slogan worthy of yoghurt or toilet cleaner. It’s not profound.

Similarly, Justin Bieber isn’t paid vast buckets of cash to be smart and insightful. Can’t we just let him be thick and carry on making horrible music? I think we should take a more Henry VIII view of entertainers. Without knowing him personally, I think it’s fair to say that the Eighth would have had an “Amuse me minstrels and if you’re very, very good I might not have you executed,” kind of attitude. Singers are there to make pleasant throat sounds, actors are there to pretend to be other people. Kim Kardashian is there to do absolutely nothing. Let’s leave it at that.

 

Justin Bieber performing recently at the O2 in London. Photograph: Getty Images

Eleanor Margolis is a freelance journalist, whose "Lez Miserable" column appears weekly on the New Statesman website.

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