Undercover by Rob Evans and Paul Lewis: The best kind of argument for a free press

If these stories about undercover police weren't plucked from the pages of our newspapers, you'd think you were reading an airport thriller. This sort of classic, long-form investigative journalism is why we must retain a truly free press.

Undercover: the True Story of Britain’s Secret Police
Rob Evans and Paul Lewis
Faber & Faber, 256pp, £12.99

The Guardian’s revelations about undercover police from the Special Demonstration Squad (and more recently the National Public Order Intelligence Unit) have unfolded rather like one of its other great exclusives, on phonehacking. The steady drip of unsavoury information has culminated in the allegation that the Met Police used undercover officers to smear the family of the murder victim Stephen Lawrence.

The issue of sex is most discomforting. Nearly every officer described in the book had passionate, long-term relationships with women from the groups they were investigating. At least one, Bob Lambert, went so far as to get a woman pregnant. Shortly afterwards, Lambert, with whom this woman had expected to live for the rest of her life, faked his emigration and left her a single parent, bereft of any kind of emotional or financial support.

Lambert, who was a special branch detective between 1980 and 2006, later became a tweedy academic (he is now a lecturer in terrorism studies at St Andrews University). In 2011, while he was giving a talk, Greenpeace campaigners burst into the lecture hall and demanded answers. Like many officers, Lambert was married with children while the affairs were taking place. Another had two relationship counsellors: one to see with his wife and one to see with the woman he was having an affair with.

Most readers will find clear evidence of exploitation in these descriptions – young, idealistic activists in their early twenties were fair game to the older undercover police officers, whatever the police may claim. Others might note just how deeply the men (and one woman) in this book had to embed themselves.

Yet it’s hardly the only morally questionable decision that these officers made. They took on the names of dead children to protect their identities. Some committed crimes and lied in court. Many seemed to be not only movers and shakers in the ecological and political circles in which they were embedded but instigators of direct action.

During the “McLibel” trial (a multi - million-pound libel suit filed by McDonald’s against the environmental activists Helen Steel and David Morris, which this book alleges was at least in part instigated by Lambert), there were sometimes more spies among the activists’ group than there were activists, as a result of the combined efforts of McDonald’s and the police.

The process of infiltration, repeated for nearly 40 years, seems more often than not to have severely damaged both the police officers’ mental well-being and that of the friends and lovers they gained and discarded. Throughout this period, there was a pattern of officers who had infiltrated groups returning to desk duty and then threatening to go rogue – or doing so.

This is perhaps why Scotland Yard has not co-operated with Rob Evans and Paul Lewis. Because of this, there’s another side to the story we don’t hear – could all this pain and suffering be worth it? At one of the most significant trials mentioned here that resulted from the actions of these officers (that of the Ratcliffe-on-Soar power station protesters who were arrested in 2009 because of the work of Mark Kennedy, a notorious undercover operator), the guilty were spared jail. The judge declared that the protesters had acted “with the highest possible motives”.

The phrase “domestic extremism” is, as the authors point out, “as meaningless as it [is] useful”. At various points here, the police apply it to the anti-roads movement, the Lawrence family, activists exposing allegations of police corruption and a 69-year-old retired physicist campaigning to protect a local beauty spot. The women with whom these officers had affairs hardly seem major threats to national security. Indeed, many seem to have done nothing illegal at all.

Were these stories not real, they would read like an airport thriller. More often than not, they end in tragedy for both their protagonists and the people who they deceived. Undercover compels the reader throughout, which is a testament to the investigative and writing skills of Evans and Lewis. The authors’ huge amount of research does not burden the narrative and is marshalled expertly.

The result is an example of the kind of classic, long-haul journalism that has, over recent years, produced scoops that have rattled the establishment, provoked multiple police inquiries and offered up an extraordinary series of revelations. The work of these authors is one of the best arguments in favour of a free press you’ll ever read.

Alan White writes for newstatesman.com and, as John Heale, is the author of “One Blood” (Simon & Schuster, £7.99)

Sleeper cell: Undercover cop Mark Kennedy. Photograph: Philipp Ebeling/Guardian News & Media LTD.

Alan White's work has appeared in the Observer, Times, Private Eye, The National and the TLS. As John Heale, he is the author of One Blood: Inside Britain's Gang Culture.

This article first appeared in the 15 July 2013 issue of the New Statesman, The New Machiavelli

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