Project 1_Chess Tournament

Load the Tournament Data

# Read the chess tournament text file
tournament <- readLines("tournamentinfo.txt", warn = FALSE)


# Display the first 20 lines
head(tournament, 20)

##  [1] "-----------------------------------------------------------------------------------------" 
##  [2] " Pair | Player Name                     |Total|Round|Round|Round|Round|Round|Round|Round| "
##  [3] " Num  | USCF ID / Rtg (Pre->Post)       | Pts |  1  |  2  |  3  |  4  |  5  |  6  |  7  | "
##  [4] "-----------------------------------------------------------------------------------------" 
##  [5] "    1 | GARY HUA                        |6.0  |W  39|W  21|W  18|W  14|W   7|D  12|D   4|" 
##  [6] "   ON | 15445895 / R: 1794   ->1817     |N:2  |W    |B    |W    |B    |W    |B    |W    |" 
##  [7] "-----------------------------------------------------------------------------------------" 
##  [8] "    2 | DAKSHESH DARURI                 |6.0  |W  63|W  58|L   4|W  17|W  16|W  20|W   7|" 
##  [9] "   MI | 14598900 / R: 1553   ->1663     |N:2  |B    |W    |B    |W    |B    |W    |B    |" 
## [10] "-----------------------------------------------------------------------------------------" 
## [11] "    3 | ADITYA BAJAJ                    |6.0  |L   8|W  61|W  25|W  21|W  11|W  13|W  12|" 
## [12] "   MI | 14959604 / R: 1384   ->1640     |N:2  |W    |B    |W    |B    |W    |B    |W    |" 
## [13] "-----------------------------------------------------------------------------------------" 
## [14] "    4 | PATRICK H SCHILLING             |5.5  |W  23|D  28|W   2|W  26|D   5|W  19|D   1|" 
## [15] "   MI | 12616049 / R: 1716   ->1744     |N:2  |W    |B    |W    |B    |W    |B    |B    |" 
## [16] "-----------------------------------------------------------------------------------------" 
## [17] "    5 | HANSHI ZUO                      |5.5  |W  45|W  37|D  12|D  13|D   4|W  14|W  17|" 
## [18] "   MI | 14601533 / R: 1655   ->1690     |N:2  |B    |W    |B    |W    |B    |W    |B    |" 
## [19] "-----------------------------------------------------------------------------------------" 
## [20] "    6 | HANSEN SONG                     |5.0  |W  34|D  29|L  11|W  35|D  10|W  27|W  21|"

Extract Player Information

# Keep only the lines that contain the main player records
player_lines <- tournament[grepl("^\\s*[0-9]+\\s*\\|", tournament)]

# Display the first few player records
head(player_lines)

## [1] "    1 | GARY HUA                        |6.0  |W  39|W  21|W  18|W  14|W   7|D  12|D   4|"
## [2] "    2 | DAKSHESH DARURI                 |6.0  |W  63|W  58|L   4|W  17|W  16|W  20|W   7|"
## [3] "    3 | ADITYA BAJAJ                    |6.0  |L   8|W  61|W  25|W  21|W  11|W  13|W  12|"
## [4] "    4 | PATRICK H SCHILLING             |5.5  |W  23|D  28|W   2|W  26|D   5|W  19|D   1|"
## [5] "    5 | HANSHI ZUO                      |5.5  |W  45|W  37|D  12|D  13|D   4|W  14|W  17|"
## [6] "    6 | HANSEN SONG                     |5.0  |W  34|D  29|L  11|W  35|D  10|W  27|W  21|"

Separate Player Number, Name, and Points

# Split each player record using the | symbol
player_split <- strsplit(player_lines, "\\|")

# Extract player number
player_number <- as.numeric(trimws(sapply(player_split, `[`, 1)))

# Extract player name
player_name <- trimws(sapply(player_split, `[`, 2))

# Extract total points
total_points <- as.numeric(trimws(sapply(player_split, `[`, 3)))

# Preview the results
head(data.frame(
  Player_Number = player_number,
  Player_Name = player_name,
  Total_Points = total_points
))

##   Player_Number         Player_Name Total_Points
## 1             1            GARY HUA          6.0
## 2             2     DAKSHESH DARURI          6.0
## 3             3        ADITYA BAJAJ          6.0
## 4             4 PATRICK H SCHILLING          5.5
## 5             5          HANSHI ZUO          5.5
## 6             6         HANSEN SONG          5.0

Extract Player State and Pre-Rating

# Get the second line for each player record
detail_lines <- tournament[grepl("^\\s*[A-Z]{2}\\s*\\|", tournament)]

# Display the first few detail lines
head(detail_lines)

## [1] "   ON | 15445895 / R: 1794   ->1817     |N:2  |W    |B    |W    |B    |W    |B    |W    |"
## [2] "   MI | 14598900 / R: 1553   ->1663     |N:2  |B    |W    |B    |W    |B    |W    |B    |"
## [3] "   MI | 14959604 / R: 1384   ->1640     |N:2  |W    |B    |W    |B    |W    |B    |W    |"
## [4] "   MI | 12616049 / R: 1716   ->1744     |N:2  |W    |B    |W    |B    |W    |B    |B    |"
## [5] "   MI | 14601533 / R: 1655   ->1690     |N:2  |B    |W    |B    |W    |B    |W    |B    |"
## [6] "   OH | 15055204 / R: 1686   ->1687     |N:3  |W    |B    |W    |B    |B    |W    |B    |"

Separate State and Pre-Rating

# Split each detail line using the | symbol
detail_split <- strsplit(detail_lines, "\\|")

# Extract state
state <- trimws(sapply(detail_split, `[`, 1))

# Extract the rating section
rating_text <- trimws(sapply(detail_split, `[`, 2))

# Extract the pre-tournament rating after "R:"
pre_rating <- as.numeric(
  sub(".*R:\\s*([0-9]+).*", "\\1", rating_text)
)

# Preview the results
head(data.frame(
  State = state,
  Pre_Rating = pre_rating
))

##   State Pre_Rating
## 1    ON       1794
## 2    MI       1553
## 3    MI       1384
## 4    MI       1716
## 5    MI       1655
## 6    OH       1686

Create Player Data Table

# Combine the extracted player information into one data frame
players <- data.frame(
  Player_Number = player_number,
  Player_Name = player_name,
  State = state,
  Total_Points = total_points,
  Pre_Rating = pre_rating
)

# Preview the first few rows
head(players)

##   Player_Number         Player_Name State Total_Points Pre_Rating
## 1             1            GARY HUA    ON          6.0       1794
## 2             2     DAKSHESH DARURI    MI          6.0       1553
## 3             3        ADITYA BAJAJ    MI          6.0       1384
## 4             4 PATRICK H SCHILLING    MI          5.5       1716
## 5             5          HANSHI ZUO    MI          5.5       1655
## 6             6         HANSEN SONG    OH          5.0       1686

Extract Opponent Numbers

# Extract opponent numbers from each player's round results
opponents <- lapply(player_split, function(x) {
  
  # Round information begins after player number, name, and total points
  round_results <- x[4:length(x)]
  
  # Extract the numeric opponent number from each round
  opponent_numbers <- as.numeric(
    unlist(regmatches(
      round_results,
      gregexpr("[0-9]+", round_results)
    ))
  )
  
  # Remove missing values
  opponent_numbers <- opponent_numbers[!is.na(opponent_numbers)]
  
  return(opponent_numbers)
})

# Preview opponent numbers for the first six players
head(opponents)

## [[1]]
## [1] 39 21 18 14  7 12  4
## 
## [[2]]
## [1] 63 58  4 17 16 20  7
## 
## [[3]]
## [1]  8 61 25 21 11 13 12
## 
## [[4]]
## [1] 23 28  2 26  5 19  1
## 
## [[5]]
## [1] 45 37 12 13  4 14 17
## 
## [[6]]
## [1] 34 29 11 35 10 27 21

Calculate Average Opponent Pre-Rating

# Calculate the average pre-rating of each player's opponents
average_opponent_rating <- sapply(opponents, function(opponent_ids) {
  
  # Match opponent numbers to the player table
  opponent_ratings <- players$Pre_Rating[
    match(opponent_ids, players$Player_Number)
  ]
  
  # Calculate the average opponent pre-rating
  mean(opponent_ratings, na.rm = TRUE)
})

# Add the average opponent rating to the player table
players$Average_Opponent_Pre_Rating <- round(average_opponent_rating)

# Preview the first few rows
head(players)

##   Player_Number         Player_Name State Total_Points Pre_Rating
## 1             1            GARY HUA    ON          6.0       1794
## 2             2     DAKSHESH DARURI    MI          6.0       1553
## 3             3        ADITYA BAJAJ    MI          6.0       1384
## 4             4 PATRICK H SCHILLING    MI          5.5       1716
## 5             5          HANSHI ZUO    MI          5.5       1655
## 6             6         HANSEN SONG    OH          5.0       1686
##   Average_Opponent_Pre_Rating
## 1                        1605
## 2                        1469
## 3                        1564
## 4                        1574
## 5                        1501
## 6                        1519

Create Final Dataset

# Keep only the columns required for the final project output
final_data <- players[, c(
  "Player_Name",
  "State",
  "Total_Points",
  "Pre_Rating",
  "Average_Opponent_Pre_Rating"
)]

# Preview the final dataset
head(final_data)

##           Player_Name State Total_Points Pre_Rating Average_Opponent_Pre_Rating
## 1            GARY HUA    ON          6.0       1794                        1605
## 2     DAKSHESH DARURI    MI          6.0       1553                        1469
## 3        ADITYA BAJAJ    MI          6.0       1384                        1564
## 4 PATRICK H SCHILLING    MI          5.5       1716                        1574
## 5          HANSHI ZUO    MI          5.5       1655                        1501
## 6         HANSEN SONG    OH          5.0       1686                        1519

Export Final Dataset

# Export the cleaned tournament data to a CSV file
write.csv(
  final_data,
  "Project1_Chess_Tournament_Results.csv",
  row.names = FALSE
)

file.exists("Project1_Chess_Tournament_Results.csv")

## [1] TRUE

Project 1_Chess Tournament_Code Base

Lakeranie Boodram

2026-09-23

Load the Tournament Data

Extract Player Information

Separate Player Number, Name, and Points

Extract Player State and Pre-Rating

Separate State and Pre-Rating

Create Player Data Table

Extract Opponent Numbers

Calculate Average Opponent Pre-Rating

Create Final Dataset

Export Final Dataset