Gilbey on Film: the Kevin Smith mystery

Why does the director of Red State dislike critics so much?

I like Kevin Smith. Not his films, necessarily (with the exception of the ones for which most people retain a residual fondness -- Clerks and Chasing Amy). But I have a lot of time for him. He's a genuinely riotous comic speaker who can be astonishingly dexterous with even the largest audience in the most cavernous venue, and he's also a stimulating thinker beneath that laddish exterior. He talks a really good film, but it's been a while since he got around to making one; his recent work has thrown up a few amusing moments but not much more. No matter. There are plenty of more successful filmmakers out there who have far less to offer.

But Kevin Smith doesn't like me. Well, not me personally, but film critics in general. A month ago, his horror film, Red State, was scheduled to be screened by its UK distributor, eOne, to London critics. Nothing controversial there. But Smith found out about the preview via Twitter, and got on the phone to the distributor to insist that it be cancelled. The official line was that he had to add an introduction to the movie before it could be shown. This, it seems, was news to eOne, but the preview was pulled with hours to go.

Smith's Twitter feed shone a new light on the story. What he wanted to do was to strike a sizable section of the critics -- or "whiners" as he called them -- from the screening list and give their places instead to 20 dyed-in-the-wool fans willing to suck up to him in the appropriate manner on Twitter. How many of them, I wonder, would have been honest when tweeting their reactions to a preview screening to which they had been granted entry by their hero? But that's not the point. No one expects impartiality from fans. Only from whiners.

Smith affixed the hashtag #OnlyPayingCustomersMatter to his tweets (prompting this pertinent interjection from UltraCulture: "now that they're no longer the aforementioned Paying Customers, those fans presumably cease to matter, in which case they don't get to go to the screening, in which case they're Paying Customers again, in which case they matter, in which case they do get to go to the screening after all, in which case AAAAARRRGGGH PARADOX"). You can read more about the fall-out here.

It's an unusual take on the critic/filmmaker relationship, and one which Smith seemed less eager to expound back when his debut film, Clerks, was being celebrated by critics such as Janet Maslin, one of the first and most vocal of Smith's champions. Here are some quotes from her 1994 review of Clerks in the New York Times:

A buoyant, bleakly funny comedy... an exuberant display of film-student ingenuity... a classic example of how to spin straw into gold... the two main actors are fresh and engaging... varied and wry... [Smith] has an uncommonly sure sense of deadpan comic timing... [he] keeps his film's improbable elements just loony enough to sustain energy... small and rough-edged, with all the earmarks of a first effort. But it's one of the good ones.

What a whiner! Jeez...

I have no axe to grind with Smith; I wasn't intending to go to that Red State screening, so I was not in any way inconvenienced. I interviewed Smith in 2006 when Clerks II was released and found him to be personable, engaging and intelligent, as well as disarmingly honest about how bruised he felt to be out in the cold now that Judd Apatow and his contemporaries were ruling Hollywood:

I see The Wedding Crashers or The 40-Year Old Virgin and it's like these dudes are making movies like I made. But they're doing them with famous people and making shitloads of money. I feel like I invented the wheel and forgot how to use it - or didn't use it the way other people learned to.

There is more honesty and self-awareness in that one paragraph than most people will give you over the course of an entire interview. So why the aversion to the honesty of critics? I don't buy the paying customers line. Smith did not pay to see an early cut of Kick-Ass or Scott Pilgrim Vs the World, and yet he was happy to be paid a fee to rave about the former on BBC2's Review Show, and to go to town encouraging his Twitter followers to see the latter. So is it okay to rave if you haven't bought a ticket? Is it just that you shouldn't say negative things about a movie if you haven't paid the full ticket price? I think that's the gist: if you haven't got anything nice to say, don't say anything at all. Hmm. What a stimulating and enriched culture we'd have if we all followed that philosophy.

But I'm confused. Smith knows his film history. He must remember that even the greatest directors sometimes listen to critics or call on them for help. Coppola reportedly made The Godfather Part II a more morally searching work in response to complaints that its predecessor had been too enamoured of its characters' violent lifestyles. Spielberg lightened up the Indiana Jones series after Indiana Jones and the Temple of Doom was accused of being too dark and nasty. (I happen to think he got it wrong there -- Indiana Jones and the Last Crusade can't hold a candle to Temple of Doom. But I'm just whining.) And where would Terry Gilliam's Brazil have been without the film critics of Los Angeles? When Universal was refusing to release the film, Gilliam arranged secret screenings for the LA critics, who ended up awarding it their Best Film prize -- thereby forcing Universal's hand and getting the picture released. Not bad for a bunch of whiners.

Red State is released on 30 September.

Ryan Gilbey is the New Statesman's film critic. He is also the author of It Don't Worry Me (Faber), about 1970s US cinema, and a study of Groundhog Day in the "Modern Classics" series (BFI Publishing). He was named reviewer of the year in the 2007 Press Gazette awards.

OLIVER BURSTON
Show Hide image

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