Show Hide image

Laurie Penny: What Margaret Thatcher means to my generation

We are living in the shadow not of Thatcher herself, but of Thatcher the icon.

Why do young liberals hate Margaret Thatcher? It's a fair question, given that many of us, myself included, were still potty-training when she left Downing Street 20 years ago. We weren't on those picket lines. We weren't in those riots. We weren't even old enough to understand why our parents had lost their jobs. So why the drunken half-jokes about dancing on her grave? Why, after two decades, is it still so personal?

It could hardly be anything else. Today's young people are living in the shadow not of Thatcher herself, but of Thatcher the icon. Thatcher for us isn't a real politician with convictions and committees to attend: she is an image, the wicked witch in the woods, the rubber mask of neoliberalism in drag gurning down at a generation just beginning to understand how it has been cheated. In most respects, we still live in a Thatcherite society, atomising itself into marketable units at the expense of the social. Thatcher has become part of the creation myth.

Young people who weren't born during the poll tax riots focus their alienated rage on the image of Thatcher, because, in neo-Thatcherite Britain, images are all we have. The Iron Lady and her cronies instigated the junk-food principle of politics, whereby hungry, needy people will invariably swallow something that isn't good for them if it has a recognisable cartoon face on it - even if, as the coalition cabinet proves, it is sickeningly rich and stuffed with yellow preservatives.

Handbags at dawn

For young women, Maggie casts a second shadow over the entire notion of female empowerment. Twenty years after she left office, it is depressing rather than encouraging that Thatcher is still the enduring Anglo-American model of a woman in a position of political power, one to which all women seeking public office, from Sarah Palin to Harriet Harman, are eventually expected to respond.

Thatcher was no more a feminist than Bradley from S Club 7 was ghetto, but she created a brand of female empowerment - all heels, warmongering and expensive handbags - striking enough to replace the erstwhile aspiration of real woman-power.

There were good reasons for her stylistic self-management; the electorate was always far more likely to accept an Iron Lady than a woman of flesh and blood. But that handbag hovers over today's ambitious young women like a sartorial guillotine, reducing feminism, along with progressive politics, to a lifestyle choice, and neutralising it in the process. As the recession has given the lie to the dream of perpetual growth, young people have begun to develop an idealised, almost pantomimic understanding of what was lost.

Ask any 20-year-old for a Thatcher slogan and they will tell you, "She said there's no such thing as society." We understand, and painfully so, that we now live in a country where community has been replaced with an image of community that can be broken up and sold back to us at a profit.

This is what the "big society" is all about: not cuddly One-Nation Toryism, but the logical conclusion of Thatcherism, with the corporate iconography of society replacing the social even as the welfare state is destroyed. It is no accident the Camerons have employed a stylist and a photographer at public expense, while it has been decided that "wasteful" quangos such as the Youth Justice Board ought to be axed. In personality politics, image is everything.

We may be too young to remember Thatcher high-heeling it out of No 10, but our leaders still dance to the rhythm of her politics and our aspirations are still dominated by her project. The mythology of Thatcherism is more than mortal. When Elton John is called upon to sing her eulogy, he will no doubt conclude that the country burned out long before her legend ever will.

Laurie Penny is a contributing editor to the New Statesman. She is the author of five books, most recently Unspeakable Things.

OLIVER BURSTON
Show Hide image

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