Description Usage Arguments Details Value Author(s) References Examples
Computes and plots kernel density estimation of shots with respect to a concurrent variable
1 2 3 4 5 6 7 8 9 10 |
data |
a data frame whose rows are shots and with the following columns: |
var |
character, a string giving the name of the numerical variable according to which the shot density is estimated. Available options: |
shot.type |
character, a string giving the type of shots to be analyzed. Available options: |
thresholds |
numerical vector with two thresholds defining the range boundaries that divide the area under the density curve into three regions. If |
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. |
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:
ShotType
, a factor with the following levels: "2P"
, "3P"
, "FT"
(and NA
for events different from shots)
player
, a factor with the name of the player who made the shot
points
, a numeric variable (integer) with the points scored by made shots and 0
for missed shots
playlength
, a numeric variable with time between the shot and the immediately preceding event
periodTime
, a numeric variable with seconds played in the quarter when the shot is attempted
totalTime
, a numeric variable with seconds played in the whole match when the shot is attempted
shot_distance
, a numeric variable with the distance of the shooting player from the basket (in feet)
A ggplot2
plot
Marco Sandri, Paola Zuccolotto, Marica Manisera (basketballanalyzer.help@unibs.it)
P. Zuccolotto and M. Manisera (2020) Basketball Data Science: With Applications in R. CRC Press.
1 2 3 4 5 | 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)
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