Analysis of 2018 Olympic Figure Skating Scores

This repository contains the data and code that BuzzFeed News used to analyze figure skating scores at the 2018 Olympic Winter Games. The data and analyses are adapted from BuzzFeed News' original figure skating analyses, published February 8, 2018. At that link, you can find a longer explanation of the terminology, data, data-processing, and analyses presented below.

Data

Whereas the original analyses used data from 17 high-level competitions between October 2016 and December 2017, this repository uses data only from the 2018 Olympic Winter Games. The following files contain data extracted from the official Olympic score sheets:

• performances.csv
• judged-aspects.csv
• judge-scores.csv

You can find definitions of each column here.

The data directory also includes the following files:

• judge-goe.csv - The "translated Grade of Execution" for judgment of each performed technical element. See this notebook for more information on the translation process.
• judges.csv - A list of each judge at the 2018 Winter Olympic Games and each judge's home-country (as indicated on the International Skating Union's roster of officials).

Analyses

The notebooks directory contains two sets of analyses:

• points-versus-average calculates the difference between each individual judge's total scores (for a given performance) and the average of the remaining judges on the panel. This notebook calculates the overall home-country preference in the 2018 Olympic Winter Games, and identifies the largest disparities between a judge's scores and the average.

• alternative-scenarios calculates the total points and final standings of the ice dance and men's competitions under two alternative scenarios: (1) If the scores from certain countries' judges were replaced by scores from an "average" judge, and (2) if those judges' scores were removed entirely.

Technical Notes

All of the analyses above are coded in Python 3, using the libraries listed in requirements.txt.

Licensing

All code in this repository is available under the MIT License. All data files are available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Questions / Feedback

Contact John Templon at john.templon@buzzfeed.com.

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