The “spring breakers” hit Cancun. Photo: Getty
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Escape to Mexico: the locals brace themselves for the arrival of the “spring breakers”

The horror, the horror.

Escape to Mexico
Overseas Radio Network
 

In the villages along the beaches of south-eastern Mexico, local people are bracing themselves for the Easter influx of young Americans known, with a shudder, as the “spring breakers”. My friend Clementino, who shines shoes in Cancún, swaps horror stories about it all day long and says even his mother back in Xcalak (population 375) has heard tales about “crazy people on the streets”. On the weekly show Escape to Mexico (Wednesdays, 4pm), the fiftysomething expat presenter, Henry Altman, retired from selling luxury golf course homes in Texas, ostensibly defends the hordes. “They’re nice kids, ya know! OK, some of them do get a little buzzed, get too loud and . . . stuff happens.”

Then he tells a long story – complex, meandering and quite possibly furious – about a bachelor party from New York that came to stay a few doors down from him in his gated community and invited him for a T-bone but got too drunk to spark up the barbecue until 1am, just as Henry was preparing to go to bed. “That was a pretty funny incident,” says Henry, sadly.

It’s the classic fiftysomething American-in-Mexico conundrum. Ah, to be Willem Dafoe in Born on the Fourth of July, staring adventure squarely in the eye, with a tequila worm between the teeth and a dusky chica unzipping one’s combats – instead of helplessly referring to fellow expats as “the private sector” and ordering room service to the condo where you enjoy jazz records and work on a painting that is provisionally entitled Moon Over the Dance Floor.

So the show goes on, turning every thought to the whys and wherefores of Colorado teenagers speeding along the Yucatán sands in ATVs at the tail end of a six-day bender, off their heads on coco locos and industrial solvents, with their feet hooked in the steering wheel and some blondes on the back peeling off their boob tubes.

Eventually, over an hour into the show, Henry changes the subject, turning to another of his favourite themes: guns, which he’s all for in theory, but then again . . . “Ya know, I ask myself sometimes, does a person actually need 10,000 rounds of ammunition in banana clips, just sitting around? They do not! Hey – here’s Ron, calling from Durable Goods in Tulum . . .”

Antonia Quirke is an author and journalist. She is a presenter on The Film Programme and Pick of the Week (Radio 4) and Film 2015 and The One Show (BBC 1). She writes a column on radio for the New Statesman.

This article first appeared in the 19 March 2014 issue of the New Statesman, Russia's Revenge

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