It's finally acceptable to cast off the shackles of TV snobbery

Who knows, Bim Adewunmi might even give the next series Big Brother a go.

Oh, I don’t watch Big Brother.” A harmless admission, right? It looks like a simple statement of telly preference, a brief glimpse into the personal habits and quirks a person has formed over years of watching the box in the corner.
 
But lurking behind those words is an unasked question, hanging invisibly at the end of that sentence. It is laced with mild incredulity and it goes a little something like, “But you do?!” You know what that is? That’s basic telly snobbery and we all engage in it.
 
Before you begin to protest a little too strenuously, take a hard look at yourself. If you watch television, you will have a show that you love, a show that you hate and a show that you’re a snob about. Come on. I’ll start with one trio that fits: I love The Good Wife; I hate Britain’s Got Talent and I look down on Big Brother (and all those who watch it). There is always a programme on the air that we feel is the very nadir of human civilisation, an insult to the riches that technology has brought to our lives, a waste of time and effort and a stain on the televisual landscape. That’s TV snobbery at its finest and don’t you deny it.
 
Television is a tribal medium. Clear evidence springs up in our own lives: the adults who were not allowed to watch ITV as children, because it was “common”, what with its advertisements and sense of fun. Or those of us who will not watch Coronation Street until forced to by extended family consensus at Christmas. Or even those people who exclusively watch box sets of HBO dramas that feature lashings of sex and black comedy and death. You pick your tribe and stick with it, because it is deft shorthand for the person you are, or perhaps the person you want to be (or be seen as). If you watch the Elmore Leonard adaptation of Justified, what does that say about you? If you love a nerdcom such as The Big Bang Theory, what are you projecting to the world? If you enjoy Sex and the City so much that you unashamedly call yourself a “total Carrie” in real-life situations, what is the world supposed to think?
 
I once worked alongside a man who very proudly and somewhat sniffily told me that he didn’t watch television. He said it – just like that – in that practised way that suggested to me that he had come to expect an awed gasp and a request to elaborate on his charming quirk.
 
So I obliged him – why, I asked, do you hate fun? And he gave the usual spiel that people like him give: oh, there’s never anything good on, I’d rather read a book and let my imagination soar free, it rots your brain and stunts your mental growth . . . On he went, ad nauseum, emphasis on the “nauseam”.
 
I thought about arguing the point – there I sat, an avid viewer of television, having imbibed hours of it a day every day since I was a child, and I was no less engaged in the world, no more stunted than any child of the 1980s, holding down jobs and paying taxes – but then I saved my breath. If you don’t want television, I thought, then television doesn’t want you.
 
And that sentiment is largely true of the programmes I (and you) hate. They’re not specifically looking for you, hankering after you to love and adore them. Television as it was in the days of one channel, then two, then five channels is gone, replaced by hundreds of channels, DVR (digital video recorders) and PVR (personal video recorders) and the king of bingeing, the box set. Shows are finding their audiences and growing with them, content to have found one at all. Nobody is really pushing to the front, shouting “like me, like me!”
 
In turn, that frees us to watch more things and cast off the shackles of the TV snobbery. Every autumn for the last few years, I’ve found myself engaging in energetic bouts of tweeting about the singing competition, The X Factor. I used to get a few people expressing surprise, mild dismay and disappointment when they saw my tweets but that’s largely stopped now; I’m allowed to like Frasier and The X Factor. Earlier this week, I watched the former contestant Rylan Clark presenting Big Brother’s Bit On The Side. My snobbery was no contest for his charm – the guy was no singer, but as a presenter? Boy, can he work a room.
 
Who knows, next series maybe I’ll give Big Brother a go after all. Another one bites the dust.
The set for the finale of last year's Celebrity Big Brother. Photograph: Getty Images

Bim Adewunmi writes about race, feminism and popular culture. Her blog is  yorubagirldancing.com and you can find her on Twitter as @bimadew.

This article first appeared in the 24 June 2013 issue of the New Statesman, Mr Scotland

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