Why is everybody laughing at Dan Brown? That's what he wants

Dan Brown has been shortlisted for a National Book Award. He is often mocked by critics, but is a powerful and influential author, whose goals may be more complicated than Clive James or Peter Conrad suspect.

On Monday morning, the National Book Awards shortlist was announced, and there among the nominees for International Author of the Year – sandwiched between Eleanor Catton and Donna Tartt – was Dan Brown.

Now, Brown gets a lot of stick – and some of it’s deserved. At his worst, he writes like a severely concussed Tom Clancy. His grasp of historical fact seems loose in the same way that London in 1666 seemed on fire. But what if we’ve got Dan Brown wrong? What if he’s smarter and more playful than we’ve thought? And what if, when we laugh at Dan Brown, it turns out he’s laughing right back at us?

Like it or not, Brown’s an influential man: for millions of people, his books are their first introduction to Dante or Da Vinci. Even the Louvre offers a Brown-themed visitor trail, primly titled "The Da Vinci Code, Between Fiction and Fact". In response to Angels and Demons, the plot of which hinges on an "antimatter bomb" stolen from CERN and primed to destroy the Vatican, the international research institute issued an almost painfully patient FAQ for readers wishing to learn more (a sample: "Does CERN own an X-33 spaceplane? No."). In Florence, you can walk in the footsteps of Brown’s hero, Robert Langdon, on a day-long tour which – some might say fittingly – stops for a lunch of tripe.

With this kind of global influence, it’s bizarre that more people don’t stop to consider how the man thinks. Jumping from painting to poem and back again, Brown wants us to see him as a renaissance man. But Dan Brown’s renaissance is no cultural revolution: it’s a machine to be broken down for spare parts. In his novels, every piece of knowledge is only valuable insofar as it can be directly applied to the solution of a problem. Da Vinci’s paintings offer handy clues to solve a murder. Bernini’s sculptures point the way to a conspiracy at the heart of the Church.

Even Washington DC’s architecture is only of interest as evidence in a Masonic mystery. Like some bizarre cross between Michael Gove and the gobbet-obsessed Irwin from The History Boys, Dan Brown wants us to see knowledge not as abstract, but as a key with which we unlock the present. And when the key doesn’t fit, it gets discarded. Behind his Harris tweed and Mickey Mouse watch, Robert Langdon is less Mary Beard and more Niall Ferguson.

Brown’s critics like to mock his uneasy relationship with historical fact. The Langdon novels all open with a statement assuring readers that what follows is based on the truth. Antimatter bombs, ancient Illuminati conspiracies, heirs of Christ – these, a sober note informs us, are all founded on real, reliable research.

Ridiculous, of course. But ask yourself: is it really possible that Brown is as naive as his critics think? Starting a Robert Langdon book, I’m reminded of Pierre Choderlos de Laclos’ Les Liaisons Dangereuses, a novel whose multiple prefaces carefully muddy the question of whether what you’re about to read is the God’s honest truth or "just a novel". There’s nothing new in an author’s playing with truth and, at the same time, playing with their audience. Brown’s had his butterflies broken on the wheel by critics like Clive James and Peter Conrad, but nobody seems to have thought for a moment that maybe he’s in on the joke. And once you start to think this, it’s hard to read his po-faced insistence that he’s only dealing in facts as anything other than a prank – a glorious two fingers to the academics, preachers, and critics who love to tear him apart. If Brown’s appeal to facts enrages us, it just might be because we’ve fallen for it – hook, line, and blood-crazed albino monk.

Still, he’s only Dan Brown. If I was Eleanor Catton, I wouldn’t be worried. But as Brown, ever the New England gent, flashes his "gracious loser" smile, we could do worse than wonder at what might be going on in the mind behind it.

Dan Brown (and Dante) at the launch of "Inferno". Photograph: AFP/Getty Images.

John Gallagher is writing a history PhD at Emmanuel College, Cambridge. He is a BBC/AHRC New Generation Thinker for 2013/2014. You can follow him on Twitter at @earlymodernjohn.

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