histogram and box plot

"Data Wrangling"

This analysis evaluates player performance in a chess tournament by comparing actual scores to ELO-based expected scores using the USCF standard formula: Expected Score = 1 / (1 + 10^((Opponent Rating - Player Rating)/400)). Using R to process tournament data for 63 players, we calculated each player's expected score against their specific opponents and identified the five biggest overperformers and underperformers. The results revealed dramatic performance variations, with ADITYA BAJAJ (MI) showing the most remarkable overperformance at +3.14 points above expected (actual: 6.0, expected: 2.86), while LOREN SCHWIEBERT (MI) had the largest underperformance at -2.51 points below expected (actual: 3.5, expected: 6.01). The analysis demonstrates how ELO-based expectations can quantify tournament performance relative to pre-tournament ratings, providing valuable insights for chess rating systems and player assessment in competitive tournaments.