5 March 1938: Evelyn Waugh on the word "Fascist"

From our correspondence.

St James’ Club, Piccadilly, W1
5 March 1938

SIR,—I am moved to write to you on a subject that has long been in my mind, by an anecdote I have just heard.

A friend of mine met someone who—I am sure, both you and he himself would readily admit—represents the highest strata of “Left Wing” culture. The conversation turned on the “May-fair” jewel robbers and the Socialist remarked that they exhibited “typical Fascist mentality.” This seems to me an abuse of vocabulary so mischievous and so common, that it is worth discussing.

There was a time in the early twenties when the word “Bolshie” was current, it was used indiscriminately of refractory school children, employees who asked for a rise in wages, impertinent domestic servants, those who advocated an extension of the rights of property to the poor, and anything or anyone of whom the speaker disapproved. The only result was to impede reasonable discussion and clear thought.

I believe we are in danger of a similar, stultifying use of the word “Fascist.” There was recently a petition sent to English writers (by a committee few, if any of whom, were English professional writers), asking them to subscribe themselves, categorically, as supporters of the Republican Party in Spain, or as “Fascists.” When rioters are imprisoned it is described as a “Fascist sentence”; the Means Test is Fascist; colonisation is Fascist; military discipline is Fascist; patriotism is Fascist; Catholicism is Fascist; Buchmanism is Fascist; the ancient Japanese cult of their Emperor is Fascist; the Galla tribes’ ancient detestation of theirs is Fascist; fox-hunting is Fascist … Is it too late to call for order?

It is constantly said by those who observed the growth of Nazism, Fascism, and other dictatorial systems (not, perhaps, excluding USSR) that they were engendered and nourished solely by Communism. I do not know how true that is, but I am inclined to believe it when I observe the pitiable stampede of the “Left Wing Intellectuals” in our own country. Only once was there anything like a Fascist movement in England; that was in 1926 when the middle class took over the public services; it now does not exist at all except as a form of anti-Semitism in the slums. Those of us who can afford to think without proclaiming ourselves “intellectuals,” do not want or expect a Fascist regime. But there is a highly nervous and highly vocal party who are busy creating a bogy; if they persist in throwing the epithet about it may begin to stick. They may one day find that there is a Fascist party which they have provoked. They will, of course, be the chief losers, but it is because I believe we shall all lose by such a development that I am addressing this through your columns.

Evelyn Waugh

[Mr Waugh is very enigmatic about the author of the remark to which he objects, but a similar comment was made to us by a friend who based his opinion not upon political bias but upon a conversation he had had with two of the guilty men. Moreover, anyone who, like Mr Waugh, has studied the growth of Fascism and Nazism, knows that among the most active champions of these movements were a number of young men with tastes which a repugnance or disability for work prevented them from gratifying. These, too, did not stop short of either brutal assaults or common dishonesty in their efforts to improve their position, and they can now be seen alike in Italy and in Germany enjoying the agreeable sinecures which their violence has earned. We do not suggest that the mentality of the Mayfair gangsters is that of all Fascists, but it is a historical fact that Fascism attracted men with just such a mentality and just such an economic position. Finally it will not have escaped Mr Waugh's attention that at least one of the guilty men had been active in selling arms to General Franco. We agree, however, that to call fox-hunting “Fascist” is a gross abuse of language.—Ed. New Statesman and Nation]

An anti-fascist protester outside the Cambridge Union. Photograph: Getty Images.

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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