Portrait of a Party by Stuart Ball: The devil's in the detail

A detailed history of the Conservative Party's domination between the First and Second World Wars.

Portrait of a Party: the Conservative Party in Britain, 1918-45
Stuart Ball
Oxford University Press, 608pp, £85

The Conservatives were by far the dominant party between the wars, winning more votes than any other party at every general election between 1918 and 1935 – in 1929, Labour won more seats but fewer votes. Few would have predicted such success for a party of the right so soon after the advent of a democratic franchise – universal suffrage was enacted for men in 1918 and for women in 1928 – in a dark age, dominated by mass unemployment and the rise of fascism in Europe.

Historians and political scientists, preoccupied with the decline of the Liberals and Ramsay MacDonald’s supposed betrayal of Labour, have been slow to analyse the Conservatives. Stuart Ball seeks to fill this gap in Portrait of a Party. He adopts the thematic approach of the political scientist, looking at Conservative beliefs, electoral support and constituency organisation, as well as the party machine at national level and the leadership. He has consulted a vast range of primary sources – not only the papers of Conservative ministers and MPs but also the rich archival records of the party at all levels, including the minutes of no fewer than 215 constituency associations. He must have a high boredom threshold.

Ball is a highly accomplished historian, the author of two fine books on the Conservatives between the wars and numerous scholarly articles, yet Portrait of a Party promises more than it provides. Much of it does little more than tell us in great detail what we know already and much that we did not know turns out to be uninteresting. Are we any the wiser for being told, “In Sheffield, the Hillsborough and Park divisions were worked from the city headquarters, but the other divisions had separate offices, as did all four of the Hull constituencies,” or, “In the later 1930s, the Harborough division of Leicestershire had 19 men’s, 34 women’s and 19 joint branches”?

Portrait of a Party will prove more of a compendium and a quarry than a classic. Ball has been overwhelmed by his material. He seems to have forgotten the first law of historical research: that, after completing his work, he must throw much of it away. The book is far too long and the price exorbitant.

The meat of the book lies in the chapter on the electoral performance of the party. But Conservative success is not difficult to explain to anyone whose vision has not been distorted by ideological spectacles. In John Buchan’s novel Mr Standfast, Richard Hannay declares that, in 1914, he had been fighting for “peace, deep and holy and ancient”, and that the war had made him understand “what a precious thing this little England was, how old and kindly and comforting, how wholly worth striving for”.

Conservatism appealed to nostalgia for the pre-war era and to a desire for “tranquillity”, the party’s electoral slogan in 1922. The newly enfranchised female voters seemed particularly susceptible to these feelings and the Tories seemed to understand the needs of female voters better than Labour, even though Conservative local associations were unwilling to select female candidates. Just four women were elected as Conservative MPs between 1918 and 1931. All were chosen for constituencies that had previously been represented by their husbands. Once elected, they were not allowed to enter the smoking room unless invited.

Nevertheless, in every interwar election and until the 1980s, it appears that women were more likely to vote Conservative than men were. “Organised working-class life,” Ball suggests, “was heavily masculine in focus, excluded women from power and often from employment and placed the husband and father even more authoritatively in the centre of the picture than did the middle or upper classes. Trade union and Labour politics at local level were often tinged with misogyny and could seem aggressive and confrontational.” Things are different today, of course.

Ball makes much of a distinctive Conservative ethos and set of beliefs but these seem to be mainly window dressing. The prime motivation seems to have been fear – of modernity, of the trade unions, of Bolshevism and of socialism, held in a Conservative poster to be an acronym for “State Ownership Confiscated Incomes All Liberty Imperilled Security Menaced”.

The Conservatives appreciated that, in the words of Neville Chamberlain in 1928, “We are not strong enough to win alone. In fact, we are a minority of the country.” They needed to appeal beyond their core vote. Fear was usually sufficient. Lord Salisbury, the Victorian prime minister, said that the Conservative Party had no more utility than the policeman and would be needed only so long as there were burglars.

Ball dresses up these instincts in a sophisticated and detailed psephological analysis. But perhaps we do not need sophisticated and detailed psephology. Perhaps the best explanation was given by the children’s author Richmal Crompton, the creator of Just William, in her story “William, Prime Minister”, published in 1930. William believed:

“There’s four sorts of people tryin’ to get to be rulers. They all want to make things better, but they want to make ’em better in different ways. There’s Conservatives an’ they want to make things better by keepin’ ’em jus’ like what they are now. An’ there’s Lib’rals an’ they want to make things better by alterin’ them jus’ a bit, but not so’s anyone’d notice, an’ there’s Socialists, an’ they want to make things better by takin’ everyone’s money off ’em, an’ there’s Communists an’ they want to make things better by killin’ everyone but themselves.”

Henry is the Socialist candidate and Douglas is the Liberal, promising presents to all those voting for him. But William, the Conservative, is elected unanimously.

Vernon Bogdanor is professor of government at the Institute for Contemporary British History, King’s College London

Neville Chamberlain while Minister for Health in 1932. Photograph: Getty Images

This article first appeared in the 24 June 2013 issue of the New Statesman, Mr Scotland

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