In the Critics this week

A History Special featuring David Cesarani on Holocaust studies, John Gray on the history of political violence and Sherard Cowper-Coles on Aghanistan.

Much of the Critics section of this week’s New Statesman is devoted to our annual history special. In his “Critic at large essay”, the historian David Cesarani surveys the changing face of Holocaust historiography. “Holocaust studies” as we recognise them today were born, Cesarani argues, in the aftermath of the trial in Jerusalem of Adolf Eichmann in 1961. The work of Jewish historians who’d either been interned in the camps or had fought as partisans shattered forever “the stereotype of Jews passively accepting their fate”. Nevertheless, Cesarani concludes, “the ‘lessons of the Holocaust’ seem no clearer” than they did 50 years ago, and “efforts to comprehend the Jewish tragedy continue to provoke as much controversy as reflection”.

In the lead book review, John Gray considers the long and bloody history of political violence. Reviewing Max Boot’s history of guerrilla warfare, Invisible Armies, and Martin A Miller’s The Foundations of Modern Terrorism, Gray argues that “lumping together every kind of irregular warfare into the category of terrorism, as is often done today, blurs the difference between those who have terror as a tactic in guerrilla warfare … and networks such as al-Qaeda that have opted for terror as their sole strategy.” Happily, Gray concludes, “we hear little these days of the absurd ‘war on terror’”.

Also in Books: Britain’s former special representative in Afghanistan, Sherard Cowper-Coles, reviews Return of a King: the Battle for Afghanistan by William Dalrymple and Games Without Rules: the Often Interrupted History of Afghanistan by Tamim Ansary (“if those who have directed [the latest war in Afghanistan] had applied the lessons that leap from the pages of both these books, the Afghan people might have harvested a more enduring dividend from the spilled blood and squandered millions of the last, lost decade”); Juliet Gardiner reviews Engineers of Victory by Paul Kennedy (“[Kennedy shows that] a greater understanding of the vital contribution of logistics and supply lines, plus the imagination, practical ability and dogged hard work of the ‘problem solvers’, … eventually coalesced to achieve an Allied victory”); Daniel Swift reviews The Pike, Lucy Hughes-Hallett’s biography the Italian nationalist poet and later fascist sympathiser Gabriele D’Annunzio (“In fashioning himself into a public figure, D’Annunzio prefigured both mid-20th century fascism and our modern cult of celebrity”); Connor Kilpatrick, managing editor of Jacobin magazine, reviews Freedom National, James Oakes’s book about the destruction of slavery in the United States (“it was not the inevitable march of progress that destroyed American slavery – it was a political movement”).

PLUS:

Jonathan Derbyshire talks to the historian Norman Stone about his latest book on the Second World War, his admiration for AJP Taylor and the future of secularism in Turkey, where he lives and teaches: “[Syrian refugees] make sure their little girls and little boys are doing their Quran lessons separately. But that’s precisely the kind of thing that secular Turkey was set up stop. This is fantastically dangerous …”

Elsewhere in the Critics:

Ryan Gilbey reviews Pablo Larrain’s film No (“No is an inspiring watch”); Kate Mossman reviews new albums by Anais Mitchell and Jackie Oates (“much of the thrill of this music lies in [Mitchell’s] fresh utterance of attitudes and ideas that have slipped out of view …”); Thomas Calvocoressi visits “Light Show”, a new exhibition at the Hayward Gallery in London; Rachel Cooke is not convinced by Stephen Poliakoff’s latest magnum opus on BBC2; Antonia Quirke is delighted to hear some frank discussion of sex on Radio 4; plus Will Self’s Madness of Crowds.

 

Afghan children play in a street in Herat. [Photo: Aref Karimi/Getty Images]
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