densityplot: Computes and plots kernel density estimation of shots with...

Description Usage Arguments Details Value Author(s) References Examples

View source: R/densityplot.r

Description

Computes and plots kernel density estimation of shots with respect to a concurrent variable

Usage

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densityplot(
  data,
  var,
  shot.type = "field",
  thresholds = NULL,
  best.scorer = FALSE,
  period.length = 12,
  bw = NULL,
  title = NULL
)

Arguments

data

a data frame whose rows are shots and with the following columns: ShotType, player, points and at least one of playlength, periodTime, totalTime, shot_distance (the column specified in var, see Details).

var

character, a string giving the name of the numerical variable according to which the shot density is estimated. Available options: "playlength", "periodTime", "totalTime", "shot_distance".

shot.type

character, a string giving the type of shots to be analyzed. Available options: "2P", "3P", "FT", "field".

thresholds

numerical vector with two thresholds defining the range boundaries that divide the area under the density curve into three regions. If NULL default values are used.

best.scorer

logical; if TRUE, displays the player who scored the highest number of points in the corresponding interval.

period.length

numeric, the length of a quarter in minutes (default: 12 minutes as in NBA).

bw

numeric, the value for the smoothing bandwidth of the kernel density estimator or a character string giving a rule to choose the bandwidth (see density).

title

character, plot title.

Details

The data data frame could also be a play-by-play dataset provided that rows corresponding to events different from shots have NA in the ShotType variable.

Required columns:

Value

A ggplot2 plot

Author(s)

Marco Sandri, Paola Zuccolotto, Marica Manisera (basketballanalyzer.help@unibs.it)

References

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

Examples

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PbP <- PbPmanipulation(PbP.BDB)
data.team  <- subset(PbP, team=="GSW" & result!="")
densityplot(data=data.team, shot.type="2P", var="playlength", best.scorer=TRUE)
data.opp <- subset(PbP, team!="GSW" & result!="")
densityplot(data=data.opp, shot.type="2P", var="shot_distance", best.scorer=TRUE)

BasketballAnalyzeR documentation built on July 2, 2020, 2:14 a.m.