So, farewell then, 10 O'Clock Live

Even though I liked it, I have to admit it was a flop. But why did it fail?

Do you remember the heady days of January, when every billboard in the country was graced by the beatific smiles of Charlie Brooker, David Mitchell, Lauren Laverne and Jimmy Carr?

Back then, 10 O'Clock Live was Channel 4's white-hot hope. How could it go wrong? Four well-loved television personalities, each bringing along a pre-existing fanbase. A Tory-led government to boo at. The full might of the Channel 4 PR machine. Hell, More 4 even scrapped its nightly broadcast of The Daily Show so there was no stablemate to overshadow it (probably).

Despite all this, we have to conclude that 10 O'Clock Live, which ended its run last Thursday, was a flop. The programme which inspired it, the Alternative Election Night, attracted 1.4 million viewers. By its eighth show, 10OCL, as I've arbitrarily decided to call it now to save wear and tear on my typing finger, attracted 631,900 viewers (a 4 per cent audience share). There has been a conspicious lack of chatter about a second season.

What went wrong? Here are five answers.

1. Overhype

As I pointed out here, The Daily Show (my benchmark for a good satirical show) was rubbish for years. Jon Stewart's been doing his thing there for more than a decade now, so it's no wonder that he's got it down to a fine art.

10OCL, on the other hand, was given the poisoned chalice of wall-to-wall publicity in the weeks before its launch. Yes, they did several non-broadcast pilots, but that's very different from the real thing.

As CNN found to their cost when they tried a similar strategy for the launch of Piers Morgan's chatshow, whipping up this kind of hysteria means that anything less than the televisual Second Coming will feel like a disappointment.

2. The Twitter backlash

The producers had clearly read the Big Book of Social Media Publicity, too, because they decided early on to pitch for the show as a Twitter "event", complete with its own hashtag.

But -- and I don't mean to shock anyone here -- Twitter can be quite mean. In fact, one of its less winning qualities is its capacity to turn into an extended kick-a-thon for anything the hivemind finds wanting.

The instavitriol hobbled the show, giving many people I follow the feeling that judgement had been passed, and there was no need to return for future episodes (which improved dramatically).

3. The Question Time switch-off

The show's audience was presumably intended to be politically engaged youngish people, the kind who read Mitchell or Brooker's newspaper columns and might conceivably care about AV. But those people were already watching something made for them on a Thursday night: Question Time.

It boggles my mind to say it, but QT is huge on Twitter, and attracts a much more varied audience than other political shows. By scheduling 10OCL against it, Channel 4 ensured that a decent chunk of their audience only ever watched the first half of the show, then flipped over to see who Kelvin McKenzie was shouting at this week.

4. Going Live

What, exactly, was the point of it being broadcast live? I hardly count myself as one of the yoof any more, but even I rarely watch TV programmes when they're scheduled.

To prove my point, it's worth noting that 10OCL did very good business on Channel 4's online viewing service, 4OD -- something the broadcaster itself wheeled out when questioned about the disappointing TV ratings.

As far I can see, broadcasting it live simply increased the potential for cock-ups, rogue camera swoops (there were usually a few of these per episode) and stilted filler chat.

All we'd have lost if it had been pre-recorded on a Thursday afternoon is the chance for Brooker and Mitchell to take the piss out of the first editions of the rightwing papers, but that's not exactly a scarce resource given that I seem to hear their opinions more often than my closest family's.

5. Bitesized

In my review of the first episode, I wrote: "Next week, I hope they'll focus less on cramming loads of stuff into the show and let their undeniably talented line-up go off the cuff a bit more." Unfortunately, it didn't really happen. There was always a dichotomy between the bits (Carr's monologue, Listen To Mitchell) which were the right length for the format, and those which felt hopelessly compressed.

The panel discussions, chaired by Mitchell, were the worst offenders: most degenerated into: "Soundbite. Soundbite. Angry counter-soundbite. Tension-easing gag by David Mitchell. Chortling by the crowd. The end." At least one of the three guests usually ended up hardly saying anything at all.

So, farewell, then

So there you have it. Of course, there were other annoyances -- I never got used to seeing the crowd in shot, smirking behind the presenter's left ear, and Jimmy Carr's dressing-up sketches ploughed such depths of tastelessness I'm surprised they didn't end up drenched in magma.

But what makes the show's failure so annoying is that it was, despite all this, good. There isn't much topical comedy on telly, and after this, I doubt any broadcaster will be splashing cash around to try to change that.

I don't feel too bad for the presenters (they're hardly stuck for work), or the producers (the show was backed by Endemol, where I imagine the printer uses £50 notes instead of A4 paper). I do feel bad for the writers, who must be wondering why they slaved over a hot script for 14 hours a day to general indifference, as a result of someone else's bad decisions.

Anyway, it's gone now. And I, for one, will miss it.

UPDATE: Just heard from the Channel 4 press office, who say: "The series has just finished and no decision on its future has been made. Contrary to rumour, it hasn't been cancelled." Hardly cause for optimism among fans, but I suppose there's still a glimmer of hope.

Helen Lewis is deputy editor of the New Statesman. She has presented BBC Radio 4’s Week in Westminster and is a regular panellist on BBC1’s Sunday Politics.

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