data_clean_tot converts a match-wise Sackmann point-by-point dataset
into a game-wise dataaset with point-by-point records, the outcome of the
game, and accumulation scores set-wise and match-wise.
data_clean_tot(us_open, last_rownum, first_rownum = 1)
A Sackmann point-by-point dataset.
The last row to apply the cleaning procedure.
The first row to apply the cleaning procedure. All rows
A dataframe whose rows are the games of tennis matches with the following columns:
pbp_id: identification corresponding to that in the original dataset
match_num: counter of the matches cleaned
set_num: identifies the set in which the game is played
game_num: counter of the games in each set (resets to 1 after a new set)
pbp: point-by-point record of the game
server: points won by the server of the game
returner: points won by the returner of the game
winner: winner of the game i.e. server or returner
player1_serve: 1 if player1 is server, 0 otherwise
player1_game: 1 if player1 wins game, 0 otherwise
player2_game: 1 if player2 wins game, 0 otherwise
player1_game_acc_set: running total of number of games won by player1 in a given set
player2_game_acc_set: running total of number of games won by player2 in a given set
player1_game_acc_total: running total of number of games won by player1 in a given match
player2_game_acc_total: running total of number of games won by player2 in a given match
total_game_acc: running total of number of games in a given match
leading_set: denotes which player has won more games in a given set
player1_set_acc: number of sets player1 wins
player2_set_acc: number of sets player2 wins
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