Why we need quantitative sports history


Professor Wray Vamplew
University of Edinburgh

Individuals are important in sport but sports history should be more concerned with the collective and the countable. The biography of golfer Harry Vardon, the Tiger Woods of his day, contributes to the understanding of an early champion golfer troubled by tuberculosis and marital difficulties. Although interesting, it is more useful as sports history if it is contextualised into asking if tuberculosis was an industrial disease of professional golfers and whether the marriage problems emanated from the time away from home making a living as an elite professional designing courses and playing in championships. These are statistical issues: how many other golfers had tuberculosis and how did this relate to the general population; how much time did top professional golfers spend on the road? Qualitative history such as biographies at best supply examples with which to illustrate an argument and at worst provide the personal experience of one person without noting its typicality

Unfortunately in a host of academic areas there has been a move away from quantification to the qualitative in both epistemology and methods, a shift from which sports history has not been immune. An obvious reason for not using a quantitative approach is that some topics are not suited or relevant to a statistical slant. Numbers are the essence of that history which looks at collective experiences such as sports crowds or groups of professional players and counting might be seen as less necessary by those more concerned with the experience of the individual. However, argument by individual example is no real substitute for the use of hard, quantified data which enables us to determine what is typical and what is unusual, the whole basis of social science theory.

Another reason for the growth of qualitative history, however, is that counting often involves substantial hard work, something which too many sports historians shy away from. They have preferred the easier (which is not the same as saying ‘easy’) qualitative methodologies. Quantification has a high research time/word output ratio: counting can be a laborious, time-consuming, often ‘tedious’ process with hours of work resulting in just one table or even a mere sentence. In the same way that academe tends to distinguish between the hard sciences (science, technology, engineering and mathematics) and the soft ones (social sciences), perhaps it is time to distinguish between the hard (quantitative) and soft (qualitative) sports history.

It could be a lack of confidence in their ability to manipulate numbers in a meaningful way that deters some sports historians from venturing into the quantitative jungle. The author can accept that some sports historians will have difficulty in coping with higher order statistical operations, but not all quantified work needs to be complicated. Even those who believe that four out of three sports historians have trouble with math should, simply by the nature of studying sport, have at least a passing acquaintance with basic statistics. Knowing whether the mean, mode or median is the most appropriate calculation to make should not be beyond most of us. Even basic percentages can improve our understanding. Descriptive statistics, suitably organised, can add to our understanding and allow a great deal of informationto be given in summary form. Moreover statistical displays can have instant, eye-catching impact.

To turn away from the use of statistics is to reject the opportunity to produce papers that provide more specific answers than gut feeling. A recent study of jockeys in the United States, undertaken by creating a data base of 4,794 jockeys, was able to show that in 1880 African-American riders were over-represented in the jockey profession (22%) relative to the proportion they occupied in the general population (13%) and that the decline in African-American jockeys over time was less precipitous than had been conventionally assumed. By use of quantitative techniques they were able to offer more precision than those historians relying on intuition, emotion and non-statistical evidence. It was meticulous counting of the occupations of 500 players from the first two decades of the Gaelic Athletic Association in Ireland using census returns, land valuations, trade directories and other sources that destroyed the foundation myth that it comprised mainly landless labourers.

There are two situations where the use of numbers is almost inevitable. Any financial information must involve figures. The other is that the establishment of growth or decline in any variable requires figures to justify the direction of change.

Yet numbers are important more generally. Measurement can allow historians to be more precise in their answers and figures can add strength to an argument by providing a statistical basis for historical assertions. Statistics can be used descriptively to set the historical scene and show the (relative) importance of a particular incident, event or theme being studied; for, example, studying the environmental impact of golf will be enhanced by a preliminary discussion in statistical terms of the number of golfers, the growth rate in participation, and the consequent rise in demand for golf facilities. Researchers should consider comparative work and look at other sports, other venues, other countries so that [they] can put [their] own case study into context and distinguish what is specific and unique from what is general and measurement is crucial for comparisons. In the author’s own work counting enabled the relative dangers of flat and jump racing to be compared via rates of injury. Associated with comparison is the issue of perspective, of putting something to do with sport in the context of non-sporting matters so that its relative importance can be gauged. It is impossible to demonstrate the economic significance of a sporting event without resort to figures. The cost of staging the 2004 summer Olympics was in the region of $20-$40 billion, equal to about one twentieth of one per cent of annual global GDP and substantially less than the $2,000 billion required to bail out US banks in 2009.

Academic sports historians appreciate statistics when they appear as lists of their citations on Google Scholar and seem capable of understanding what is meant by an ‘h-index’ and an ‘i10-index’. So why don’t they take their quantitative sense into their actual research. In modern sport, analysts would not consider the impact of a policy to increase grassroots participation or the influence of a new manager on a team’s performance without resort to measurement. So it should be when looking at the past. Moreover if non-quantitative sports historians fail to educate themselves in basic statistical techniques or methodology, they run the risk of disenfranchising themselves from a corpus of knowledge within the subject.


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