SL_points.R

library(ggplot2)
library(reshape2)

# Load data, and rerank teams by points
data = read.table("SL_points.txt", sep="\t", header=T)
data$old_rank = rank(-data$Old, ties.method="first")
data$bonus_rank = rank(-data$Bonus, ties.method="first")
data$penalty_rank = rank(-data$Penalty, ties.method="first")

# New dataframe of ranked teams under each scheme
tables = data.frame(old = data$Team[order(data$Old, decreasing=T)],
                    bonus = data$Team[order(data$Bonus, decreasing=T)],
                    penalty = data$Team[order(data$Penalty, decreasing=T)])
  
# Melt data for plotting
mdata = melt(data, id='Team', measure.vars=c('Old', 'Bonus', 'Penalty'))

# Plot data
p = ggplot(mdata, aes(x=variable, y=value, group=Team, color=Team))
p + geom_line(size=1) + labs(title="SL 2013 Points", x="Points Scheme",
                             y="Points")

SL_points.txt

Team	W	D	L	L close	Old	Bonus	Penalty
Huddersfield	21	0	6	2	42	65	38
Warrington	20	1	6	4	41	66	39
Leeds	18	1	8	6	37	62	35
Wigan	17	1	9	5	35	58	31
St Helens	15	1	11	8	31	55	28
Hull FC	13	2	12	5	28	48	21
Catalan	13	2	12	6	28	49	22
Hull KR	13	0	14	5	26	44	17
Bradford	10	2	15	5	22	39	12
Widnes	10	2	15	8	22	42	15
Wakefield	10	1	16	8	21	40	13
Castleford	9	2	16	4	20	35	8
London	5	2	20	3	12	22	-5
Salford	6	1	20	5	13	25	-2

Data and R file in support of a blog post about Super League table points schemes.