威少爺的投籃命中率

• 2020 年 3 月 3 日
• 筆記

資深籃球評論員蘇群老師的公眾號今天分享的文章是《威少投籃慘不忍睹，但他把MVP給喬治》，其中用表格形式展示了威少爺11年職業生涯出手距離投籃命中率和出手距離所佔比重的變化，個人認為這類數據用折線圖看起來更為直觀，本文記錄整理蘇群老師文章中用到的數據後使用ggplot2製作折線圖的程式碼

數據整理

不同出手距離的命中率

不同出手距離比重

繪圖

1、 出手距離與命中率

library(ggplot2)  library(reshape2)  df1<-read.table("clipboard",header=T)  colnames(df1)<-c("Season","0~1","1~3","3~5","5~7","7~")  mydata1<-melt(df1,id.vars = "Season",variable.name = "shooting_distance",value.name = "Percentage")  ggplot(mydata1,aes(x=Season,y=Percentage,group=shooting_distance,color=shooting_distance))+    geom_line()+scale_color_brewer(name="Shooting Distance(m)",palette="Set1")+    geom_point()+theme_bw()+labs(x="")+    scale_y_continuous(breaks = seq(0,1000,by=100),labels=seq(0,100,by=10),                       limits = c(0,1000))+    theme(legend.key=element_blank(),          legend.background = element_blank(),          axis.text.x = element_text(angle=90,vjust=0.5))

從上圖可以看出1-5米內出手命中率近兩個賽季明顯下降，1米內出手命中率生涯最佳

2、出手距離比例

df2<-read.table("clipboard",header=T)  df2  mydata2<-melt(df2,id.vars = "Season",variable.name = "shooting_distance",value.name = "Proportion")  mydata2$shooting_distance<-factor(mydata2$shooting_distance,levels=c("E","D","C","B","A"))  ggplot(mydata2,aes(x=Season,y=Proportion,fill=shooting_distance))+    geom_bar(stat="identity")+theme_bw()+    scale_fill_brewer(name="Shooting Distance(m)",palette="Set1",                      breaks=c("E","D","C","B","A"),                      labels=c("7~","5~7","3~5","1~3","~1"))+    scale_y_continuous(breaks = seq(0,1000,by=100),labels=seq(0,10,by=1),                       limits = c(0,1000))+    theme(axis.title = element_blank(),          axis.text.x = element_text(angle=90,vjust=0.5))

由上圖可以看出，威少本賽季較上個賽季的進攻方式的變化：略微增加了三分球，減少了長兩分，其他沒有明顯變化

參考文獻

• R語言ggplot2包畫折線圖
• Legends(ggplot2)
• ggplot2 legend : Easy steps to change the position and the appearance of a graph legend in R software