Description Usage Format See Also

This dataset has lagging-leading differences in player statistics and renames descriptions of the game in terms of lagging and leading player as opposed to player1 and player2.

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A data frame with 17680 rows and 107 variables; only variables not in `tennis`

are explained below. Note that differences were calculated by subtracting leading numbers from lagging numbers.

- see
`tennis`

- lagging_serve
1 if lagging player serves, 0 otherwise

- leading_serve
1 if leading player serves, 0 otherwise

- lagging_points
points scored by lagging player in the game

- leading_points
points scored by leading player in the game

- lagging_game
1 if lagging player wins game, 0 otherwise

- leading_game
1 if leading player wins game, 0 otherwise

- lagging_game_acc_set
number of games won by the lagging player in the given set thus far

- leading_game_acc_set
number of games won by the leading player in the given set thus far

- lagging_game_acc_tot
number of games won by the lagging player in entire match thus far

- leading_game_acc_tot
number of games won by the leading player in entire match thus far

- lagging_set
1 if lagging player wins set, 0 otherwise

- leading_set
1 if leading player wins set, 0 otherwise

- lagging_set_acc
number of sets won by the lagging player thus far

- leading_set_acc
number of sets won by the leading player thus far

- lagging_match_win
1 if lagging player wins match

- leading_match_win
1 if leading player wins match

- diff_game_tot
match-wise game deficit

- diff_set
match-wise set deficit

- lagging_hand
1 if lagging player is right-hand dominant, 0 otherwise

- leading_hand
1 if leading player is right-hand dominant, 0 otherwise

- diff_hand
1 if players are dominant in different hands, 0 otherwise

- diff_rank
difference in the players' ranks

- diff_serve_won
difference in the service games won

- diff_ret_won
difference in return games won

- lagging_age
age of lagging player

- leading_age
age of leading player

- diff_age
difference in the players' ages

`tennis_cleaned`

for a player1/player2-defined dataset; `tennis_data`

for child set

Other final files: `tennis_data`

,
`tennis`

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