Hyperquantifying Athletes: Opportunities and Problems in Modern Collegiate Sports
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Date
2022
Authors
Heckman, Amelia
Journal Title
Journal ISSN
Volume Title
Publisher
University of Oregon
Abstract
In recent years, collegiate sports have started turning to data analysis to assist in improving performance and training tactics. There are many opportunities in utilizing data-driven – or “hyperquantified” –approaches, such as talent identification, injury reduction, in-game decision making, and increasing profits. Many universities and professional organizations utilize models to predict success. While there are many benefits, there is less emphasis on the broader wellbeing of the athlete—which “success” in this context does not include. This thesis investigated one specific example of creating a predictive model of success at the University of Oregon as well as the issues that arise from using such a model. Three ethical implications that arise from hyperquantifying athletes discussed in this thesis include data reliability, data security, and athlete autonomy. Further research is recommended into how athlete wellbeing can be emphasized at the collegiate sport levels.
Description
Keywords
Sports, Track and field, Hyperquantification, Autonomy, Python