Reviewed: 1913 - the World Before the Great War by Charles Emmerson

In search of lost time.

1913: the World Before the Great War
Charles Emmerson
Bodley Head, 544pp, £25

Not many saw the bloodbath coming and it wasn’t inevitable. One of the great merits of Charles Emmerson’s global panorama is to show events in the months leading up to the summer of 1914 as something other than a precursor to mass slaughter. You didn’t have to be quite as mistaken as the University of California president Benjamin Ide Wheeler, who in 1911 nominated Kaiser Wilhelm II for the Nobel Peace Prize, to think that things were going well enough.

The three kingly cousins who ruled a third of the world –Wilhelm II, Tsar Nicholas II and King George V –met in Berlin and the crowds cheered. A few years earlier, Britain and France had replaced their deeply entrenched rivalry with an entente cordiale. The Economist, never frightened of a bit of prediction, thought that it was “an expression of tendencies which are slowly but surely making war between the civilised communities of the world an impossibility”. Note the civilised world bit – because virtually nobody in power in Europe on the eve of a European-made war thought that the continent’s empires were anything other than a reflection of moral superiority, as well as military power.

Emmerson starts with a tour of Europe’s major cities but this is largely a device for a series of potted and fairly orthodox histories of each country, stretching back 50 years or so – Germany and Italy since their respective unifications, France under the Third Republic, the Habsburg empire since Hungary and Austria formed the dual monarchy, and so on. The obvious neuroses, as well as the complacencies, of the mighty are described and analysed. Britain, though still top dog, was weakening fast, enervated by the Irish Home Rule crisis and suffragette violence that posed a serious enough threat in 1913 to close many of London’s major tourist attractions. France, meanwhile, was obsessed with its declining population and Berlin’s modernity. Emmerson also points out that some of the more reactionary regimes – notably Russia and the Ottoman empire – were enjoying an economic boom. Their crises were born as much out of growth as political decrepitude.

Emmerson sprays his book with quotations, many of them too long. Some hit the mark, however, such as this from Walter Hines Page, the US ambassador to Britain, in a letter to Woodrow Wilson: “We are in the international game . . . in the inevitable way to leadership and to cheerful mastery in the future; and everybody knows that we are in it but us.” That is acute. Then there’s this from Lenin: “Capitalism has triumphed all over the world.” (Perhaps in the long term he had a point.)

There are other surprises. Argentina was seen by many as a new United States, with Buenos Aires a world city adored by City of London investors and brimming with artistic life; its engineers lectured around the Old World on the back of the construction of a spanking new underground system. Winnipeg, the largest grain centre in the Americas, was a cosmopolitan hub and similarly poised for greatness. By contrast, Tehran is described as a hellhole, in a much worse state than Bombay, Algiers or even Mexico City, then in the grip of civil war.

There is some attempt at discussing painting, literature and architecture but it’s a bit half-hearted: 1913 was the year of the riot in Paris on the opening night of Stravinsky’s Rite of Spring but Emmerson barely mentions it. Proust published the first volume of À la recherche du temps perdu and Freud’s Interpretation of Dreams was translated into English. Yet we are none the wiser about their impact.

Emmerson, reasonably enough, does not peddle an overarching thesis to link his individual portraits of cities, states and empires but he is good on racial fears and tensions – and not only in the context of European colonialism. Wilson, who could do sanctimony on a grand scale, presided willingly over a deterioration of the position of African Americans in the federal government. Gandhi, who was still in South Africa, fought his first big successful campaign of passive resistance on behalf of the country’s Indians but was not much concerned with the plight of the black population, whose limited land rights were eroded even further in 1913.

In California, ethnic Japanese similarly found their property rights curtailed but, back in Tokyo, the Japanese were only too keen to insult, at the highest level, the Chinese or Mongolians.

Naturally, the shadow of 1914 is present much of the time – it could hardly be otherwise. Yet, occasionally, the world of 1913 throws up something satisfyingly contemporary – and none better than this from a French author arriving in New York who noted the questioning style of US customs and immigration. “Are you an anarchist? Are you a polygamist? Are you an idiot? Have you ever shown signs of mental alienation?” The war changed most things – but not everything.

Mark Damazer is the Master of St Peter’s College, Oxford and a former controller of BBC Radio 4

An "electric brougham" in Waterloo Place in London in 1913. Photograph: Getty Images

This article first appeared in the 12 April 2013 issue of the New Statesman, Centenary Special Issue

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