Predict the runs for the batsman given the Balls Faced and Minutes in crease

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Description

Fit a linear regression plane between Runs scored and Minutes in Crease and Balls Faced. This will be used to predict the batsman runs for time in crease and balls faced

Usage

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batsmanRunsPredict(file, name="A Coverdrive", newdataframe)

Arguments

file

This is the <batsman>.csv file obtained with an initial getPlayerData()

name

Name of the batsman

newdataframe

This is a data frame with 2 columns BF(Balls Faced) and Mins(Minutes)

Details

More details can be found in my short video tutorial in Youtube https://www.youtube.com/watch?v=q9uMPFVsXsI

Value

Returns a data frame with the predicted runs for the Balls Faced and Minutes at crease

Note

Maintainer: Tinniam V Ganesh <tvganesh.85@gmail.com>

Author(s)

Tinniam V Ganesh

References

http://www.espncricinfo.com/ci/content/stats/index.html
https://gigadom.wordpress.com/

See Also

batsmanMovingAverage battingPerf3d batsmanContributionWonLost

Examples

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# Get or use the <batsman>.csv obtained with getPlayerData()
# tendulkar <- getPlayerData(35320,file="tendulkar.csv",type="batting", 
# homeOrAway=c(1,2), result=c(1,2,4))

# Use a single value for BF and Mins
BF <- 30
Mins <- 20

# retrieve the file path of a data file installed with cricketr
pathToFile <- system.file("data", "tendulkar.csv", package = "cricketr")
batsmanRunsPredict(pathToFile,"Sachin Tendulkar",newdataframe=data.frame(BF,Mins))

#or give a data frame
#BF <- seq(20,200, length=15)
#Mins <- seq(30,220,length=15)

#values <- batsmanRunsPredict("../cricketr/data/tendulkar.csv","Sachin Tendulkar",
    #newdataframe=data.frame(BF,Runs)
#print(values)

# Note: The above example uses the file tendulkar.csv from the /data directory. However
# you can use any directory as long as the data file exists in that directory.
# The general format is pkg-function(pathToFile,par1,...)

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