Childlike in the best way – The Gigantic Beard That Was Evil

Stephen Collins' debut graphic novel, reviewed.

The Gigantic Beard That Was Evil
Stephen Collins
Jonathan Cape, 240pp, £16.99

Stephen Collins is the creator of what is perhaps my favourite newspaper cartoon ever. Published in the Guardian last year, it features Michael Gove and David Cameron arguing about how best to respond to an alien invasion. The caricatures are spot-on, the "acting" (as it were) tells as much as the words, and the humour is a finely balanced mixture of political satire and nonsensical lunacy. It's what I imagine Steve Bell's If… feels like for people who've been reading it non-stop for thirty years, the only subsection of society able to get the the byzantine in-jokes, and well-enough inured against the scatological puns to survive them.

So I was excited to see Collins' debut graphic novel arrive on my desk. It's less political than some of his strips, focusing instead on the absurdist humour that makes pieces like I tried to cancel my gym membership and Don't wake up work so well; but despite the fact that there's no politicians caricatured, it still reads as a fable for our times.

Dave lives Here. The important thing about Here is that it's an island in the middle of The Sea, and somewhere past the edge of The Sea is There. The people of Here don't like There. Because Here is orderly, neat, and predictable, and There is everything Here isn't.

But Here is also beardless. So when Dave – Dave who makes charts for a company whose business he doesn't understand, Dave who is completely bald save for one thick hair on his lip, Dave who has listened to the Bangles' Eternal Flame 427,096,483 times – suddenly sprouts an enormous beard that can't be cut, won't stop growing, and just seems slightly evil, Here goes mad over it.

The book is rendered in soft pencil, black and white throughout, but printed to a huge size (almost bookshelf-busting, so be warned there), which gives Collins a chance to express tremendous versatility. The orderly nature of Here in the early half of the book is expressed with a high – almost Chris-Ware-high at times – panel count, and as the squares of the panels blur into the lines of the grid system of houses, the sort of world Dave lives in becomes apparent. And then, after one full-page spread early on shows the windowless walls of the houses on the coast of Here facing out to the sea, we see our first glimpse of There. The panel boarders drop away, and drawn in black on top of black is the chaos the residents fear.

As well as high panel counts, the huge book allows Collins to use another effect to great success: a couple of pages in the book are nearly blank, except for one speech balloon or caption. It's a relatively standard technique, except that as the pages get bigger, the text has been shrunk – leading to a feeling of the reader drowning in the absence of information. Something which Dave, faced with his inexplicable beard, knows only too well.

The obligatory art paragraphs also can't end without a mention of the book's coda. It's hard to discuss in too much detail – the story's not plot-heavy, but it still wouldn't do to give away the ending – but as a character leaves hand-drawn pictures behind on their journey, we see the last few notes found, pasted into a scrapbook and illustrating, maddeningly vaguely, what came next for them. The pictures fade to black, and then, in the very last one, a hint of something else appears…

Taken overall, it reminds me of nothing so much as a Roald Dahl novel: a surreal premise, presented as matter-of-factly as possible, which, if you buy into it – as children do naturally, and adults who know whats-what do too – presents the opportunity for a piece of strong character work. This isn't a book for children, the oblique references to the Bangles and self-help gurus make that clear, but it is childlike in the best way. Which is what you'd expect from a man who drew a cartoon about the High Speed Beyoncé, really.

Alex Hern is a technology reporter for the Guardian. He was formerly staff writer at the New Statesman. You should follow Alex on Twitter.

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