08. Going for Gold: Using Record Linkage and Bayesian Hierarchical Modeling to Select Winning Gymnasts at the 2024 Paris Olympics

Athletes who compete in the Olympic Games participate in many other competitions before this international event, and scores in these competitions are possible tools to use to predict Olympic performance. However, at each competition the name of a gymnast is not always perfectly recorded, as nicknames and other variants of names are often used. In this project, I use record linkage to identify athletes in data from 2022 and 2023 international competitions. I propose an adaptation to the Jaro-Winkler Similarity score based on the specific discrepancies in names in this data set. I then use the linked data to predict winning gymnasts in Women's Artistic Gymnastics using Bayesian Hierarchical Modeling.

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Knowledge

Women in Statistics and Data Science 2024