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Chess.com "Titled Tuesday" Statistical Analysis

This repository contains tools for statistical analysis of chess games played in "Titled Tuesday" events on chess.com between July 2022 and December 2023.

Dataset

  • ./data/titled-tuesday.csv: CSV-formatted "Titled Tuesday" dataset. You can use it if you don't want to run scraping script yourself.

  • scrape_and_save.py: This script retrieves game data from "Titled Tuesday" via chess.com API and web pages scraping, preprocesses it, and saves to MongoDB. The data includes games of all players who ranked 1-25 in any of the "Titled Tuesday" event.

  • generate_dataset.py: This script turns MongoDB players collection into Pandas DataFrame and then saves it as a .csv dataset.

Statistical Analysis

The analysis.py script contains code to perform various types of statistical analysis with chess data:

  • Descriptive statistics (mean, number of wins, losses, rank distribution).
  • Game accuracy distribution analysis between tournaments rounds to find differences in accuracy between initial and final rounds
  • K-means clustering and k-nearest neighbors analysis.
  • Linear regression to predict game results based on player accuracy.
  • Statistical tests (Kolmogorov-Smirnov test, Shapiro-Wilk normality test).
  • Kernel Density Estimation (KDE) and visualization
  • Maximum Likelihood Estimation of mean and standard deviation assuming chess data normality
  • Correlation analysis of score and accuracy (Spearman's rank corellation coefficient)