Lez Miserable: "Here's my second coming out: I hate music festivals"

Live music is great. But you know what's also great? Bands not sounding like they’re shouting into saucepans.

With light seeping in from outside, I can just about see my breath in front of me. My head is a pulsating hurt orb. Need painkillers. Now. Torch in mouth, I rummage around the tent, through bags of fermented socks. So many socks. No sign of pills. I think they’re socks now. Everything is socks. I drop the torch (my only non-sock possession) and sit in the dark with my head in my hands. Then the shivering starts. Uncontrollable shivering. I need to put on more layers, but I only have socks. I put socks on my hands. It’s a start. Swampy water has seeped in from somewhere and my sleeping bag is a giant, flaccid slug. The wind carries in the stench of raw sewage. Then come the Outside People. Grotesque human/traffic cone hybrids, silhouetted against the walls of my tent. They’re shouting something about burgers. Sweet Jesus: they’re hungry.

What kind of post-apocalyptic, dystopian nightmare is this? One I paid nearly £200 for, actually. The gangrenous trench foot-like smell of festival season is beginning to pollute the air. And I’ve realised that it’s about time I stop telling my friends that I’d love to go with them to Beefstival/Dick Party/Green Bidet. So here’s my second coming out: I hate music festivals.

One day, when I was seven, a filth-encrusted spectre waded in through the door. It spoke little and when it did, it was in grunts. Its hair was matted, its eyes were glazed and reddish. It was only when my mum addressed The Thing as “Ruth” that I realised it was my big sister. I learnt that she’d returned from something called “Glastonbury”. I vowed never to go there.

But I eventually forgot about my sister’s haunting, post-Glasto thousand yard stare. Nine years later, I went to my first festival. And my God did I pretend to love it. I pretended so hard, in fact, that I continued to go to festivals for many years. See, festivals have us all by the balls. Their organisers and sponsors have come up with a genius business model where they get young people with low self-esteem to spend hundreds of their parents’ pounds on living like medieval peasants for a weekend – wallowing in actual faeces – while vehemently declaring that they’re having “OMIGOD-THE-BEST-TIME-EVERRRRR”.

But what about the music? Sure, I love hearing live bands. You know what else I love? Them not sounding like they’re shouting into saucepans. Let’s face it; outdoor gigs sound atrocious. Imagine an hour of saucepan shouting. Imagine seven hours of saucepan shouting. Imagine three freaking days of saucepan shouting. Throw in some rancid, ersatz falafel and an armpit-load of anonymous bodily fluids and you have yourself a festival. Plus, in one of this year’s viral videos, attendees at the Californian festival Coachella-goers feign  interest in bands that don’t exist. This just goes to show that a lot of festival-goers don’t even know what they’re doing there – “Music? Yeah, great, I guess. I like that band with the guitars.”

These people have been inexplicably lured into a three-day-long masochism fest, worthy of de Sade. I’m beginning to wonder if festivals are manifestations of middle class guilt. Therapeutic weekend-long sessions in which we abandon comfort, in order to feel slightly better about spending £6.99 on single loaves of quinoa bread.  What results is an uncanny circus of young humans in animal onesies and “aren’t I adorably ditsy” flower headbands; each and every one of them pretending to have a fantastic time. To be fair, I hear that the ones on enough MDMA to get a giraffe doing the Harlem Shake are genuinely enjoying themselves. Isn’t it telling that in order to have real-life fun at a festival, you need to self-medicate with a delicious cocktail of class As? For me, drug-taking usually culminates in curling into a foetal position and/or being convinced that Robin Williams is going to murder me. So no help there.

When I got home from Field Day (a day-long festival in Victoria Park) last month I had sunstroke and about nineteen “Where are you???” texts from friends I’d lost in the heaving crowds. What seems like the entire day was spent on the phone to these friends, saying things like, “Err, I’m by a thing that looks like a thing.” Even safe in the knowledge that I’d sleep in my bed and not a soggy tent that night, I came to a life-changing conclusion: I’m too old for this shit. So, mates who invited me to Bestival this summer, here’s my honest RSVP: Not even if I get to share a tent with Natalie Portman.

Let's be honest - no one is really having fun here. Photograph: Getty Images

Eleanor Margolis is a freelance journalist, whose "Lez Miserable" column appears weekly on the New Statesman website.

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