Gail Rebuck and Victoria Barnsley: The dethroned queens of the publishing industry

It's just like when Thatcher was toppled - only nobody is cheering.

Recent times have felt like publishing’s equivalent of the week Margaret Thatcher was toppled, but with fewer cheers. On 1 July Gail Rebuck abdicated after 22 years as queen of Random House UK. The following day the chief executive of HarperCollins UK, Victoria Barnsley, was dethroned after 13 years. Suddenly, women have a lot less power in publishing.

Rebuck’s move from chief executive to chair was a not unexpected consequence of the merger of Penguin and Random House, announced last October and cleared by regulators with remarkable speed. The new UK head of the combined group is Tom Weldon, whose hunger to lead Penguin led to the premature retirement of Helen Fraser in 2009. It’s a big job for Weldon, a 47-year-old whose success owes less to literary distinction than to the sales of Jamie Oliver, Jeremy Clarkson and Paul Burrell, Diana’s butler.

Still, the publishing world consoles itself, at least Weldon has spent his life in books. At HarperCollins, the new chief executive, Charlie Redmayne, cut his teeth at BSkyB and has lately led J K Rowling’s Pottermore website.

The two dethroned queens were inevitably seen as rivals, and when a nanny ricocheted between them it upped the ante. Rebuck’s damehood in the 2009 Birthday Honours took the shine off Barnsley’s OBE, awarded six months earlier.

Rebuck was always regarded as the heavyweight – her portfolio included Chatto & Windus and Jonathan Cape, arguably Britain’s most literary imprints. Yet her roots are commercial. She first made her mark with Susie Orbach at Hamlyn, and life came full circle with the publication in 2012 of Fifty Shades of Grey, as she began her career with Ralph Stokes, who published erotica.

Meanwhile, Barnsley was just 30 when she founded the determinedly upmarket Fourth Estate, where she presided over the publication of Carol Shields (whom everyone had turned down) and Dava Sobel’s Longitude. Fourth Estate never made any money, but HarperCollins bought it in 2000 to instal Barnsley as CEO and it has since thrived.

Inevitably, the focus this past week has been on how two powerful women who care passionately about books are being succeeded by two young(ish) men fixated on celebrity, brand and technology – on product, a word too tidy and businesslike to describe a proper book. Moreover, Penguin – that most British of companies, founded by Allen Lane in 1935 to bring high-quality books to the mass market – will now be headquartered in New York City, a mere imprint of Penguin Random House. Markus Dohle, the global head of Penguin Random House, comes from the printing business and when he was appointed five years ago the New York Times observed that it was “roughly akin to putting the head mechanic in charge of an entire airline”.

Liz Thomson is co-editor of bookbrunch.co.uk

Book of Dave: Victoria Barnsley, ex-chief executive of HarperCollins, pictured in 2004. Photograph: Harry Borden/National Portrait Gallery.

Liz Thomson edited, with Patrick Humphries, the revised and updated edition of Robert Shelton’s “No Direction Home: the Life and Music of Bob Dylan”

This article first appeared in the 15 July 2013 issue of the New Statesman, The New Machiavelli

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