Reviews round-up

The critics' verdicts on Amos Oz, Charles Emmerson and Michael Burleigh.

Between Friends by Amos Oz

 

In a collection of eight stories, Amos Oz uses his own experience of living on an Israeli kibbutz to explore the difficulties in striving for equality in communal living.

For Lucy Popescu of the Independent, “Oz brilliantly conveys the harsher side of kibbutz life”. Whilst Oz suggests no easy answers to the questions he raises, “he builds an evocative portrait of a 1950s kibbutz, the hopes and dreams of its inhabitants, and the successes and failures of communal living, using beautiful, spare prose”.

Similarly, for Alberto Manguel in the Guardian, the novel is a “lucid and heartbreaking chronicle of [a] well-intentioned and hard-working community of lonely souls”. Manguel argues that the novel makes salient points about the "Middle East conundrum”, as well as “the impossibility of utopia [as] ongoing proof of our determination to keep on trying.”

Although acknowledging that Oz “may have written more dazzling books”, Ben Lawrence in the Telegraph praises this "deeply affecting chamber piece”, suggesting it “draws on… the contradictory urges that lie at the heart of Israel’s psyche”.

All three reviewers praise Sondra Silverstein’s “deft” translation. 

 

1913: The World Before the Great War by Charles Emmerson

 

Charles Emmerson’s account paints a strikingly different picture of 1913 to more conventional tales of extravagant social endeavours undertaken in anticipation of looming destruction.

According to Kathryn Hughes writing in  the Guardian, Emmerson wants readers to experience what it felt like to be alive in 1913, “unaware of the coming rip in history”. She sees his work as an “ambitious, subtle account," noting that "Emmerson tries hard not to play the hindsight game. Still, he's honest enough to acknowledge the cheap pleasure that comes from knowing what happens next”.

David Crane, in the Spectator, is even more forthcoming in praise: “this is an immensely impressive book”. Emmerson turns 1913’s lack of headline events into a strength and “gives us a masterful, comprehensive portrait of the world at that last moment in its history when Europe was incontrovertibly ‘the centre of the universe’ and, within it, London ‘the centre of the world’”.

In contrast, Mark Damazer, reviewing the book for the New Statesman, feels Emmerson’s attempt at discussing painting, literature and architecture is “a bit half-hearted”. For Damazer, there are too many long quotations and too many important events that go untouched, although “occasionally, the world of 1913 throws up something satisfyingly contemporary”.

 

Small Wars, Far Away Places by Michael Burleigh

 

The historian Michael Burleigh's Small Wars, Far Away Places, is a document of the national liberation movements which sprang up in the two decades after the Second World War.

Although praising Burleigh’s ability to compose “pungent and pithy prose” and “bring history to life”, David Herman in the New Statesman is critical of some “puzzling absences” in the book, such as the Portugese colonial project. The reliance on Anglophone sources is also criticised, rendering the book “out of date and parochial”.

Historian John Lewis-Stempel, writing in the Express, sees Burleigh as “the don of elegant, historical writing and every vignette in this book is arresting”. However Lewis-Stempel similarly laments the gaps in knowledge and occasional errors, to him a product of Burleigh’s inability to remain a “dispassionate” historian.

Ben Shepard in the Guardian is more positive, arguing that the historical narratives Burleigh composes are “small masterpieces of lucidity and concision with complex political backcloths effortlessly painted in”. Nevertheless, Shepard argues that the “book never quite hangs together and the serial narrative method it uses gradually exhausts both writer and reader”.

The new work by Amos Oz has been praised as "a lucid and heartbreaking chronicle."
OLIVER BURSTON
Show Hide image

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