Slow-burn revolutionary: Princip in prison. Photo: Getty
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Gavrilo Princip: the assassin who triggered the First World War

Princip was a slow-burn revolutionary, identifying himself with all Bosnians and committing himself to the ideal of winning freedom for all local Bosnians, not just local Serbs.

Gavrilo Princip was not the best-trained of assassins, or the best-equipped, nor was he the most ruthless. But he was, perhaps, the luckiest, shooting dead Archduke Franz Ferdinand through a series of strokes of serendipity and fortune. It was the rest of the world’s bad luck that his actions triggered the first global conflict.

Princip was born in 1894, a serf’s son from the wild west of Bosnia. His father, Petar, earned extra income by delivering letters around the hamlet of Obljaj, where Princips had eked a hardscrabble existence for generations.

Petar was later described as an “entrepreneur” by his infamous son, but in reality his life was a continuation of a centuries-old tradition of feudal peasantry, battling to live off the land, obliged to surrender earnings and produce to overlords.

From the mid-15th century those overlords were installed by the occupying Otto­man empire before its withdrawal was finally confirmed by the 1878 Congress of Berlin. But the removal of one occupier did not mean freedom for the local Slav population, because another, Austria-Hungary, then staked Bosnia as the newest tessera in the polyglot mosaic of the Habsburg empire.

Austria-Hungary presented this coup of colonialism – the Scramble for Africa was taking place at roughly the same time – as a project of enlightened occidentalism that would bring light to a part of Europe long benighted by orientalism. This was largely guff, as the Austro-Hungarians set about plundering the natural resources of Bosnia  – mostly timber from its rich forests – and failed to carry out land reform and left alone the system of feudal exploitation.

For peasants like the Princips, life hardly changed. Petar married a woman called Maria from the hamlet next door and set up home in a single-room hovel with a beaten-earth floor, set into a hillside. They had nine children but only three, all boys, survived. Gavrilo was the middle son, his early life a cycle of domestic chores and learning his three Rs. He shone at school, his ability to read and write marking him out in Bosnia where, after 30 years of supposedly enlightened Habsburg occupation, the illiteracy rate stood at 88 per cent.

The local Slav community shared the same bloodline although they had been cleaved by faith over the ages into three groups: early Christians who followed Eastern Orthodoxy were known as Bosnia’s Serbs, Christians who followed Rome were Croats and those who converted to Islam under Ottoman rule were Muslims. The Princips were part of Bosnia’s Serb community, and Obljaj an entirely Serb settlement of co-religionists who lived, worked, married and died together.

The big change for Gavrilo came in 1907 when, aged 13, he left this insular little world and set off for the capital city, Sarajevo, to pursue his secondary education. Here he shone, excelling in his early years as a hard-working and dutiful student. But he did not just learn his lessons, he also learned to think the unthinkable, discussing with other students how Bosnia might be liberated from the occupier.

Princip was a slow-burn revolutionary, consistently identifying himself with all Bosnians and committing himself to the south Slav or Jugoslav nationalist ideal of winning freedom for all local Bosnians, not just local Serbs. His thinking was woolly and naive but he did not give in to the chauvinism of some Serbs who wanted a single Greater Serbia.

After four years of study he left for the neighbouring country of Serbia, another part of the Balkans peopled by south Slavs. Serbia had won independence from the Ottomans in the late 19th century, and Princip lived there on and off from 1912.

With his fellow Bosnian radicals – from all three faith groups – he settled on a plan to assassinate a senior Austro-Hungarian figure as a symbolic act that they hoped would be a catalyst and would spur others into demanding liberation. When they read in newspaper announcements that Franz Ferdinand was due to visit Sarajevo to oversee military manoeuvres, they settled on him as the perfect target.

Princip struck on the morning of Sunday 28 June during the archduke’s ceremonial visit into Sarajevo city centre. His wife, the duchess Sophie, was killed at his side: an accident, according to Princip, as he had intended to kill only the archduke or members of his officer cadre.

At two weeks short of his 20th birthday, Princip was too young to be executed; under Austro-Hungarian law, the death sentence could be given only to criminals aged 20 or more. Instead, he was jailed, sentenced to 20 years in solitary confinement, with the condition that one day a month he was to receive no food.

Princip died in a prison hospital on 28 April 1918, his body so ravaged by skeletal tuberculosis that his right arm had been amputated. He was buried in an unmarked grave but later disinterred, and his remains were moved in the 1920s to Sarajevo, where they lie to this day. 

Tim Butcher is the author of “The Trigger: Hunting the Assassin Who Brought the World to War” (Chatto & Windus, £18.99)

This article first appeared in the 25 June 2014 issue of the New Statesman, Who was Franz Ferdinand?

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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