From the fact-checking department: Let me count the ways

The errors and inaccuracies of Richard Bradford.

Here, for the record, is a list of some of the factual errors alluded to in my review of Richard Bradford's book Martin Amis: The Biography:

- "Around 1956-57 Martin's parents' marriage came close to collapse, due primarily to Hilly's affair with the journalist Henry Fairlie. Fairlie resembled the sort of character played by Leslie Phillips or Terry-Thomas in Ealing Comedies". Neither Leslie Phillips nor Terry-Thomas appeared in an Ealing comedy. Terry-Thomas did, however, play Bertrand Welch in the adaptation of Lucky Jim.

- "Butterfield was fully aware of Peterhouse's reputation as the most conservative ... of the Cambridge colleges - Tom Sharpe's Porterhouse Blue was comprised partly of stories, many accurate, of the bizarre, ritualistic archaisms of the place." Herbert Butterfield may have been aware of Peterhouse's reputation in 1961, when he interviewed Kingsley Amis for a Fellowship, but Tom Sharpe's novel wouldn't have reinforced that impression for another 13 years.

- "Kingsley Amis met Elizabeth Jane Howard at the Cheltenham Literature Festival in October 1962. She was, that year, director of the event. Its theme was 'Sex in Literature', drawing in such luminaries as Joseph Heller and Carson McCullers and encouraging flirtatious banter between all involved." I cannot be certain on this point; accounts differ. But it seems that Elizabeth Jane Howard was the honorary artistic director for that year's festival, of which "Sex in Literature" was not the theme, merely the title of one panel discussion. I am fairly confident that there was no flirtatious banter between Kingsley Amis and Joseph Heller.

- "Martin's and Philip's initial encounter with Jane occurred shortly after their return from Majorca and is described in Experience, rather as if a piece by Iris Murdoch had been rewritten by a copy-editor with some cognizance of the real world." Iris Murdoch possessed cognizance of the real world.

- "Thirty-five years later the letters between Amis senior and Philip Larkin would be published and recognized as the most outrageous epistolary novel ever". The letters of Kingsley Amis and the letters of Philip Larkin were published almost a decade apart. (Neither was recognised as the most outrageous epistolary novel ever - or rather, as half of one.)

- "His tutor Jonathan Wordsworth was the poet's great, great, great, great nephew and in case anyone suspected otherwise his rooms were generously distributed with 'family' memorabilia". Leaving aside the use of "distributed" in that sentence, it should be noted that despite the memorabilia, some might have suspected that Jonathan Wordsworth was in fact William Wordsworth's great-great-great nephew. (Christopher Ricks once said, memorably, that Jonathan Wordsworth had an Oedipal relationship to the poet, although he was only "a collateral descendant".)

- "Like most major writers he rarely if ever admits to anything so compromising as influence". It's hard to know where to start. Let this admission, from a 1980 article never collected in a book, stand for all the hundreds of reasons why Bradford's claim is false: "That bit about 'wiry wings' [in The Rachel Papers] was stolen ... from Dickens ... I once lifted a whole paragraph of mesmeric jargon from J G Ballard's The Drowned World."

- "John Gross, then editor of the TLS, and guest at one of the numerous, informal gatherings at Lemmons, asked Martin if he had any interest in a full-time junior post. He did but asked if the appointment could be deferred for about six months ... He began work officially at the TLS in March 1972." John Gross did not move from the New Statesman to the TLS until 1974 (as Bradford later informs us).

- "[In 1973, Clive James] had only been in London for three years." Clive James came down from Cambridge in 1969 (or thereabouts), but he had lived in London for three years in the 1960s, having left Australia in 1961.

- "'To get to [Tina Brown's] room in college I would have to step over waiting TV crews, interviewers, profilists.'... Martin's description is certainly not hyperbole." It is hyperbole.

- Jeremy Treglown did not work "mainly for the TLS" in 1977. At that time, he taught at UCL; he joined the TLS in 1979. According the Times Literary Supplement Historical Archive, established in part by Jeremy Treglown, his first article appeared in the issue of 23 November 1979.

- Bradford quotes Clive James as saying that Leavis retired in 1964. However you define "retired" in relation to an academic, Leavis didn't retire in 1964.

- "Martin and Mary and later Angela were the Becks and Posh of their day." Really?

- "Martin continued for the simple reason that Kavanagh had settled a fee that went far beyond any advance even the most popular novelist could hope for: £30,000." At around the same time, Joseph Heller - hardly the most popular novelist - received around a $1m for Good As Gold.

- Ernest Hemingway is not an example of "the kind of essayist that the British press had not previously countenanced", and which Amis hoped to become.

- Philip Roth (b. 1933) and John Updike (b. 1932) are not "near contemporaries" of Vladimir Nabokov (b. 1899).

- Saul Bellow had not "three turbulent, and failed, marriages" but four.

- "Shortly after Money was published Martin wrote an essay for Atlantic Monthly on Bellow's The Adventures of Augie March". It was written more than a decade later.

- George Steiner's The Portage to San Cristobal of A.H. was published in 1981, not 1979. Malcolm Bradbury, in one of his numerous books about fiction, described it as a "long novella", and recalls that it was one of the books - Amis's Other People was another - considered for that year's Booker Prize, on which he was chair of judges. The prize eventually went to Midnight's Children.

- In Groundhog Day, Bill Murray's character does not awake "in full knowledge of what fate has in store for him for the next twenty-four hours."

- Peter Hitchens doesn't contribute articles to "the Daily Mail that made Thatcherism seem spinelessly irresolute by comparison" - he did so for the Express and then the Mail on Sunday.

Leo Robson is the lead fiction reviewer for the New Statesman.

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