Reviewed: Life of Crime

Force of nature.

Life of Crime
ITV

I love Hayley Atwell’s performance as a south London cop in Life of Crime (10 May, 9pm) in every respect save for one: her accent. Do you know any coppers this posh? And no, before you ask, she is not supposed to be a Cambridge graduate on the fast track to the top of the Metropolitan Police (see Rupert Penry-Jones in Whitechapel). Her dad was also a policeman and her mum is London Irish, with the brogue to match. When we first meet her, she’s still living at home in a shabby terrace with a velour three-piece suite and a set of wine glasses that look like they came free with petrol. So quite where her immaculate RP came from, I don’t know. Even if she had unaccountably picked it up down her local comprehensive, you’d think she’d occasionally throw in the odd George Osborne-style glottal stop, given the company a copper keeps.

It bothered me a lot, this voice, but I kept watching because I really like the set-up of the series – it begins in 1985, when Denise Woods is a humble WPC in Brixton nick, and then follows her down the years (part two is set in 1997, by which time she is a DI; in part three it’s 2013 and she is a senior officer) – and also because Atwell is a captivatingly good actor when it comes to unspoken emotion. I believe in her character’s commitment to her work – her drive, determination and absolute refusal to allow the men to push her aside – in a way that I very much didn’t in the case of Emily Watson as an MP in The Politician’s Wife. It’s going to be fascinating to see how Atwell ages Denise; from what I read, she has done this with no help at all from wigs and stick-on wrinkles.

Anyway, 1985 . . . A girl has been murdered, but no one – by which I mean Denise’s male superiors – wants to know. Or at least, they would like to take the path of least resistance and hang it on the victim’s father, who has a temper. Denise, on the other hand, wants to know very much indeed. So determined is she to get her man, she might just be about to overstep the mark (I won’t say more, in case you’re saving it up). It’s true that Life of Crime is slightly underwritten (it’s by Declan Croghan, who also brought us episodes of Ripper Street and Waking the Dead); the dialogue is underpowered and lacks the fruity richness of, say, Life on Mars. It can be predictable. It was only a matter of minutes before a colleague had said to Woods: “Are you lesbian, or something?” But the plot is clever, dishing up an act of madness on her part that will have consequences even decades later, and I liked Con O’Neill’s performance as her boss, DI Ferguson, a man whose frayed exterior left you wondering whether he was a decent man masquerading as a ratbag, or a ratbag masquerading as a decent man.     

In truth, though, episode one was worth watching for atmosphere alone. My God, the Eighties. For all that I was there, I still can’t get over them. How weird to remember that women constables were then expected to walk the streets in bulky skirts, sheer-ish tights and cross-body leather handbags (for all their make-up, presumably). Atwell and her co-star Richard Coyle, a detective who drives a brown Ford Capri, did some fantastic Eighties dancing at a nightclub called – I’m guessing at the spelling –Subotica, where the DJ looked exactly like Paul “It-took-me- 90-minutes-to-trim-these-sideburns” King. He played some Go West, which made me smile (most series would have had him spinning the Human League or Spandau Ballet), and when Woods asked him whether he knew the girl who had died, he replied that he had merely “got off with her” one night. Do people still say “got off with”? I’d love to know.

This isn’t Broadchurch, I see that, but it’s great to see yet another tough woman copper hijack prime time. Not so long ago, we had to make do with Jane Tennison. Now, though, they’re everywhere – and some of them even manage to have private lives, too.

Life of Crime concludes on Friday 24 May

Hayley Atwell in Life of Crime. Photo: ITV.

Rachel Cooke trained as a reporter on The Sunday Times. She is now a writer at The Observer. In the 2006 British Press Awards, she was named Interviewer of the Year.

This article first appeared in the 13 May 2013 issue of the New Statesman, Eton Mess

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