How did Ben Elton's "The Wright Way" get it so wrong?

The old comedy adage says that if there's nothing funny left to say, make a penis joke. Perhaps this explains why <em>The Wright Way</em> is just one big knob gag, then.

Ben Elton’s new sitcom, The Wright Way, was likely doomed from the moment the first scathing review went online. Coming from a widely-disliked figure like Elton - the turncoat, the sell-out - its reputation preceded it, other critics bundled on, and pretty soon everybody knew for certain that it was going to be a stinker. (At the time of writing, Wikipedia lists its genre as “Anti-comedy”.) The Twitter LOL-vultures circled.

As fun as the Twitter competition for the most cutting put-down was, there’s also reason to be slightly wary of this feedback loop of mass instant criticism. While online word-of-mouth can propel slow-burn, boxset-ready series to hit status, the real-time rush-to-judgement also has the potential to condemn shows before they’ve had a chance to find their feet.

Sitcoms are especially vulnerable to this; they’re notoriously hard to get right straight away. Test audiences hated the first episode of Friends; Men Behaving Badly had to lose its star and move to a different broadcaster before audiences embraced it; Blackadder didn’t reach its comic potential until they brought in a bold young talent called Ben something-or-other to shake up the second series. Quite simply, it’s a flat-out foolhardy and ignorant act to pass judgement on a sitcom’s true worth just a few episodes in.

Unless it’s The Wright Way, of course, because it’s utter, utter crap.

The second episode landed with a sickly thud on our televisions last night, and might have - somehow – managed to be worse than the first episode. A shockingly lazy calamity of a show, its many, many superficial failures serve only as a light and fluffy distraction from the vast, gaping flaws at its core. (The central character, David Haig’s health and safety officer Gerald Wright, is a crudely Frankensteined composite of Victor Meldrew and Gordon Brittas, who splits his time evenly between furiously railing against the petty annoyances of modern life and taking great pleasure in causing the petty annoyances of modern life. This is because Ben Elton only had so many jokes to go round and nobody could be bothered to tell him that it made absolutely no sense.)

Two episodes in, we can now start to sense the shape of the show’s broader trends. For example, some of the characters have catchphrases! David Haig’s catchphrase is “don’t get me started”. His daughter’s lesbian lover’s catchphrase is “this is such a YouTube moment” (because that is totes what all the young people say). Mina Anwar’s catchphrase is shouting.

If something wasn’t funny once, try repeating it. An entire section of dialogue about chest waxing is replicated, beat for beat, in both episodes. A plot about Wright’s ex-wife coming over for tea somehow takes two episodes to set up (possibly this counts as a “story arc”?) A character says the title of the show. Twice.

In what is clearly intended to be the series’ signature comic riff, each episode features a scene in which Wright constructs a series of tortuous acronyms on a whiteboard, unwittingly spelling out a rude phrase. These phrases, it turns out, also handily serve as the show’s epitaph:

As these demonstrate, above all else, the show hews tightly to the comic rule that if there’s nothing funny left to say, make a penis joke. Penis. Penis. Words that mean penis. Things that look like penises. Penis. At one point a character talks about vaginas, just to keep the audience guessing. Then back to penis. Penis. Penis acronyms. Actions that look like a character is using his penis. Penis.

Now: David Haig is a fine comic actor, and both he and his groin are veterans of many classically bawdy British comedies. His is a grizzled, old-timey groin that’s been the punchline to many a set-up, the prat of many falls, the penis ex machina that plugged a hundred plot holes. Like Rutger Hauer’s replicant in Blade Runner, this groin has seen things you people wouldn’t believe. And yet, there was a moment last night, as Haig’s battle-hardened, farce-calloused groin wearily humped a dustbin for the second time that episode, when - if you were watching in HD, perhaps - you could just about see his groin embracing the inevitability of death.

This sense of resignation in the face of doom pervades the whole shooting match. Elton could perhaps be forgiven for having lost his hunger, living as he does in a giant fort made of money and Queen CDs. But everywhere you look there are signs that nobody involved in the show gave much of a toss. Characters drinking out of mugs that are obviously empty. Haig spending most of a scene sitting at table where his face isn’t properly lit. Camera placements that can’t quite remember who was supposed to be in shot. And a dead-eyed cast, mechanically mugging their way through the script in the hope that if they just do everything loudly enough, their agents might return their children unharmed.

(My personal favourite is Beattie Edmonson’s increasingly desperate expressions while hanging around in the back of shots, trying to find something plausible to do with her face as she waits for her next line to stagger into view. Seriously, try re-watching it with the sound off, just focusing on her. It’s such a YouTube moment.)

So, bad show is bad. What of it? The problem here is not so much that somebody made a lousy TV show, it’s what they didn’t make instead. TV commissions are a zero-sum game - there are only so many pilots that can be ordered, only so many series made. And there are too many young writers desperate for a chance to try things out, to learn and fail and get better, for the BBC to be easily forgiven for shovelling time and money towards complacent, will-that-do dross like The Wright Way.

There’s no formula to comedy. Any commissioning policy worth a damn will produce as many failures as successes. But at least fail by trying.

This is why the Twitter hate-watchalong, entertaining as it was, was doomed to run out of steam long before episode two was halfway through. The Wright Way is not so bad it’s good, it’s so bad it’s simply exhausting. How can you work up the energy to mock something for missing the target when nobody involved seems to have cared enough to even aim for it? The sheer number of ungiven fucks have a profoundly enervating, soul-sapping quality. It’s like J K Rowling’s Dementors, sucking all the joy from a room. There’s just nothing funny left to say.

Penis.

 

The cast of Ben Elton's "The Wright Way", making serious faces while wearing hard hats. Photograph: BBC
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