The Data Analyst: Elite Sport Performance and Precarious Work

In January 2017, the online publication Paste Magazine, in its regular ‘Secret Soccer Analyst’ column, featured a frank and forewarning confessional on the work and life of a sports data analyst. Writing under the clever heading, ‘Mo Moneyball Mo Problems’, the anonymous author lamented everything from the isolating nature of the data analyst role, to the immense time commitment data analytics require, to the low standards of pay that characterize the industry – the last of these deemed a function of the large pool of labourers from which employers can draw. “I’ve been depressed for a few years now and I’ve just started to get professional help,” the secret author revealed. “Every day I wonder if my job is a glimmer of hope in my life, or my worst enemy” (https://www.pastemagazine.com/articles/2017/01/the-secret-soccer-analyst-mo-moneyball-mo-problems.html). As knowledge labourers situated in an economy increasingly characterized by precarious (i.e., flexible, insecure, low pay) work, and, more specifically, as skilled but increasingly abundant workers in an elite sporting context dependent on time-sensitive insights into ever larger pools of performance data, the sports data analyst role indeed seems ripe for the types of problems outlined in the secret analyst’s confessional. This presentation seeks to interrogate the twin premises that, in an age of Big Data, data analysts are growing more important to elite sport performance while at the same time experiencing work and life conditions that are marked by precarity. The presentation contextualizes the role of the data analyst in relation to the wider Big Data moment before discussing the presenters’ empirical work on Big Data in sport, which includes preliminary insight into the challenging and in some ways precarious nature of data analysis work.