New memoirs by Alan Johnson and Ann Widdecombe: "Look, I'm like you, I'm human, I've lived!"

Politicians create narrative from scant facts on a daily basis - it's part of the job. New memoirs from Johnson and Widdecombe offer an example of how-to (and how not-to) use this skill.

This Boy: a Memoir of a Childhood
Alan Johnson
Bantam Press, 304pp, £16.99

Strictly Ann: the Autobiography
Ann Widdecombe
Weidenfeld & Nicolson, 452pp, £20

Politicians adore narrative. They spend their careers telling stories, of a sort, in a bid to make sense of reality and create an impression of control. They tell their own stories, too: the childhood memory, the apposite encounter with the man on the street, the time they were treated so kindly by the NHS nurses when they had their tonsils removed. Anecdotes colour up a speech. It’s their way of saying, “Look, I’m like you, I’m human, I’ve lived.”

Then there’s memoir. The exceptions – such as Barack Obama – write their lives into myth before the apex of their political career. But most wheel back to the beginning from the discomfort of old age and semi-irrelevance. The perspective should help – there’s no need to win votes; honesty can prevail. Yet often they’ve been so well-schooled in the art of political narrative that they can’t resist the urge to manipulate.

Here, anyway, are two lessons in the form: a how-to and a how-not-to. Alan Johnson captures only the first 18 years of his life in This Boy but there is enough pain, poverty and hardened experience in his childhood to fill volumes. He achieves two exceptional things. First, he manages to write about stark deprivation while growing up in North Kensington – permanent hunger, no electricity, constant damp, parental abandonment – without a note of self-pity. Second, he writes about his life without dominating the story. He gives the stage instead to his elder sister, Linda, who takes charge of their unwell mother, the household and Johnson after their father leaves. Somehow, while they are both still children and then orphaned, Linda keeps the authorities at bay, finds them a home and supports them financially.

Johnson is as movingly fulsome in his admiration as he is unflatteringly honest about his fears and limitations. When he sees his mother weeping in hospital before a heart operation, he admits to being “as embarrassed as I was concerned . . . In the space of a few minutes I’d had three thoroughly unwelcome experiences. I’d seen Lily cry openly, she’d hugged me for practically the first time and now she was talking about dying.” He is the anti-hero of his own tale.

And then there’s Ann Widdecombe. You know you’re in trouble with Strictly Ann on page seven, when the author has just been born and she segues bluntly from her mother’s attitude towards friendship to her views on gay marriage (against). This is the way Widdecombe rolls: memory, negligible link, moral pronouncement. She hasn’t managed to unwind her life from her work or her real self from her public image. Instead, she reveals how smitten she is by her curious fame – framing the most cruel of political cartoons, quoting with glee the brutal criticisms of her laboured efforts on Strictly Come Dancing (“a dalek in drag” and so on).

If Johnson’s is a work of self-effacement, this is the opposite: a blast of inelegantly transcribed ego. Perhaps Johnson is saving his politics for subsequent volumes but it would have been easy for him to spin his often desperate childhood into a party political broadcast. Instead, he fills his book with vivid recollection and genuine style – recalling a shop where “ambrosia was available” for sixpence in the form of pie, mash and a “thickish clear sauce freckled with parsley”. This is not memoir as PR but as storytelling. Almost until the end of This Boy, he is convinced that his future holds rock stardom, a dream only undercut by some gentle self-mockery.

Irony isn’t in Widdecombe’s arsenal: this is political memoir played straight and dull, through long Westminster procedural chapters with the odd break for a sermon (she is particularly strong on the absurdity of linking Catholic teaching to the prevalence of Aids: “The best cure for HIV and Aids is chastity before and fidelity within marriage,” in case you weren’t aware). At last, you think, when you reach the final chapter on Strictly, some laughs! Some witty self-deprecation! But no. Widdecombe’s heavy prose and psychologically fascinating lack of humorous selfawareness means that even an account of a Titanic-inspired rumba, with Widdecombe as Winslet, falls as flat as the rest.

Public image limited: Ann Widdecombe. Photograph: Getty Images.

Sophie Elmhirst is features editor of the New Statesman

This article first appeared in the 01 July 2013 issue of the New Statesman, Brazil erupts

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