TOPboxes: Calculate Team, Opponents and Players box scores (Tbox, Obox...

In BasketballAnalyzeR: Analysis and Visualization of Basketball Data

Calculate Team, Opponents and Players box scores (Tbox, Obox and Pbox)

Description

Calculate Team, Opponents and Players box scores (Tbox, Obox and Pbox)

Usage

TOPboxes(data, team)

Arguments

data	a data frame containing play-by-play data (see Details)
team	character, indicating the name of the team

Details

To compute Tbox and Obox, the function needs the following variables: game_id, playlength, ShotType, points, result, team, oreb, dreb, PF, turnover, assist, block and steal. If any of these variables is missing, an error message is displayed.

To compute Pbox, also the variables player, a1 . . . a5, h1 . . . h5 and hometeam are needed. If any is omitted, only Tbox and Obox are given in output.

Note that the variables assist, block and steal can contain the logical indicator of whether the corresponding event has occurred (TRUE/FALSE or numerical 0/1) or the name of the involved player (character). In the former case, Tbox and Obox are fully computed, while the variables AST, BLK and STL are missing in the Pbox data frame. In the latter case, all the data frames Tbox, Obox and Pbox are fully computed.

TOPboxes omits the computation of the variables W (Games won) and L (Games lost). In fact, since we aim at computing box scores starting from whatever portion of play-by-play data (e.g., only a part of a game), in some cases, calculating the number of won and lost games does not make sense.

Value

A list with the following elements

• Tbox, the data frame of team box scores

• Obox, the data frame of opponents box scores

• Pbox, the data frame of player box scores

Author(s)

Marco Sandri, Paola Zuccolotto, Marica Manisera ([e-mail])

References

P. Zuccolotto, M. Manisera and M. Sandri (2026) Advanced Basketball Data Science: With Applications in R. CRC Press.

P. Zuccolotto and M. Manisera (2020) Basketball Data Science: With Applications in R. CRC Press.

See Also

PbPmanipulation

Examples

library(operators)
library(dplyr)
PbP <- PbPmanipulation(PbP.BDB)
PbP <- PbP %>%
  mutate(oreb = type %~% "rebound offensive",
         dreb = type %~% "rebound defensive",
                turnover = event_type=="turnover",
                PF = (event_type == "foul") & !(type %~% "technical") ) %>%
        mutate(across(c(player, assist, steal, block, h1:h5, a1:a5), as.character)) %>%
 as.data.frame()
out <- TOPboxes(PbP, team="GSW")

BasketballAnalyzeR documentation built on June 8, 2025, 10:12 a.m.