Twas brillig, and the slithy toves
Did gyre and gimble in the wabe:
All mimsy were the borogoves,
And the mome raths outgrabe.
Jabberwocky by Lewis Carroll
No analysis of cricket is complete, without determining how players would perform in the host country. Playing Test cricket on foreign pitches, in the host country, is a ‘real test’ for both batsmen and bowlers. Players, who can perform consistently both on domestic and foreign pitches are the genuinely ‘class’ players. Player performance on foreign pitches lets us differentiate the paper tigers, and home ground bullies among batsmen. Similarly, spinners who perform well, only on rank turners in home ground or pace bowlers who can only swing and generate bounce on specially prepared pitches are neither genuine spinners nor real pace bowlers.
So this post, helps in identifying those with real strengths, and those who play good only when the conditions are in favor, in home grounds. This post brings a certain level of finality to the analysis of players with my R package ‘cricketr’
Besides, I also meant ‘final analysis’ in the literal sense, as I intend to take a long break from cricket analysis/analytics and focus on some other domains like Neural Networks, Deep Learning and Spark.
If you are passionate about cricket, and love analyzing cricket performances, then check out my racy book on cricket ‘Cricket analytics with cricketr and cricpy – Analytics harmony with R & Python’! This book discusses and shows how to use my R package ‘cricketr’ and my Python package ‘cricpy’ to analyze batsmen and bowlers in all formats of the game (Test, ODI and T20). The paperback is available on Amazon at $21.99 and the kindle version at $9.99/Rs 449/-. A must read for any cricket lover! Check it out!!
Important note 1: The latest release of ‘cricketr’ now includes the ability to analyze performances of teams now!! See Cricketr adds team analytics to its repertoire!!!
Important note 2 : Cricketr can now do a more fine-grained analysis of players, see Cricketr learns new tricks : Performs fine-grained analysis of players
Important note 3: Do check out the python avatar of cricketr, ‘cricpy’ in my post ‘Introducing cricpy:A python package to analyze performances of cricketers”
Important note: Do check out my other posts using cricketr at cricketr-posts
For getting data of a player against a particular country for the match played in the host country, I just had to add 2 extra parameters to the getPlayerData() function. The cricketr package has been updated with the changed functions for getPlayerData() – Tests, getPlayerDataOD() – ODI and getPlayerDataTT() for the Twenty20s. The updated functions will be available in cricketr Version -0.0.14
The data for the following players have already been obtained with the new, changed getPlayerData() function and have been saved as *.csv files. I will be re-using these files, instead of getting them all over again. Hence the getPlayerData() lines have been commented below
1. Performance of a batsman against a host ountry in the host country
For e.g We can the get the data for Sachin Tendulkar for matches played against Australia and in Australia Here opposition=2 and host =2 indicate that the opposition is Australia and the host country is also Australia
All cricketr functions can be used with this data frame, as before. All the charts show the performance of Tendulkar in Australia against Australia.
par(mfrow=c(2,3)) par(mar=c(4,4,2,2)) batsman4s("./data/tendulkarVsAusInAus.csv","Tendulkar") batsman6s("./data/tendulkarVsAusInAus.csv","Tendulkar") batsmanRunsRanges("./data/tendulkarVsAusInAus.csv","Tendulkar") batsmanDismissals("./data/tendulkarVsAusInAus.csv","Tendulkar") batsmanAvgRunsGround("./data/tendulkarVsAusInAus.csv","Tendulkar") batsmanMovingAverage("./data/tendulkarVsAusInAus.csv","Tendulkar")
## null device ## 1
2. Relative performances of international batsmen against England in England
While we can analyze the performance of a player against an opposition in some host country, I wanted to compare the relative performances of players, to see how players from different nations play in a host country which is not their home ground.
The following lines gets player’s data of matches played in England and against England.The Oval, Lord’s are famous for generating some dangerous swing and bounce. I chose the following players
- Sir Don Bradman (Australia)
- Steve Waugh (Australia)
- Rahul Dravid (India)
- Vivian Richards (West Indies)
- Sachin Tendulkar (India)
#tendulkarEng=getPlayerData(35320,opposition=1,host=1,file="tendulkarVsEngInEng.csv",type="batting") #bradmanEng=getPlayerData(4188,opposition=1,host=1,file="bradmanVsEngInEng.csv",type="batting") #srwaughEng=getPlayerData(8192,opposition=1,host=1,file="srwaughVsEngInEng.csv",type="batting") #dravidEng=getPlayerData(28114,opposition=1,host=1,file="dravidVsEngInEng.csv",type="batting") #vrichardEng=getPlayerData(52812,opposition=1,host=1,file="vrichardsEngInEng.csv",type="batting")
frames <- list("./data/tendulkarVsEngInEng.csv","./data/bradmanVsEngInEng.csv","./data/srwaughVsEngInEng.csv", "./data/dravidVsEngInEng.csv","./data/vrichardsEngInEng.csv") names <- list("S Tendulkar","D Bradman","SR Waugh","R Dravid","Viv Richards")
The Lords and the Oval in England are some of the best pitches in the world. Scoring on these pitches and weather conditions, where there is both swing and bounce really requires excellent batting skills. It can be easily seen that Don Bradman stands heads and shoulders over everybody else, averaging close a cumulative average of 100+. He is followed by Viv Richards, who averages around ~60. Interestingly in English conditions, Rahul Dravid edges out Sachin Tendulkar.
# The other 2 plots on relative strike rate and cumulative average strike rate, shows Viv Richards really blasts the bowling. Viv Richards has a strike rate of 70, while Bradman 62+, followed by Tendulkar. relativeBatsmanSR(frames,names)
3. Relative performances of international batsmen against Australia in Australia
The following players from these countries were chosen
- Sachin Tendulkar (India)
- Viv Richard (West Indies)
- David Gower (England)
- Jacques Kallis (South Africa)
- Alastair Cook (Emgland)
frames <- list("./data/tendulkarVsAusInAus.csv","./data/vrichardsVAusInAus.csv","./data/dgowerVsAusInAus.csv", "./data/kallisVsAusInAus.csv","./data/ancookVsWIInWI.csv") names <- list("S Tendulkar","Viv Richards","David Gower","J Kallis","AN Cook")
Alastair Cook of England has fantastic cumulative average of 55+ on the pitches of Australia. There is a dip towards the end, but we cannot predict whether it would have continued. AN Cook is followed by Tendulkar who has a steady average of 50+ runs, after which there is Viv Richards.
#With respect to cumulative or relative strike rate Viv Richards is a class apart.He seems to really #tear into bowlers. David Gower has an excellent strike rate and is followed by Tendulkar relativeBatsmanSR(frames,names)
4. Relative performances of international batsmen against India in India
While England & Australia are famous for bouncy tracks with swing, Indian pitches are renowed for being extraordinary turners. Also India has always thrown up world class spinners, from the spin quartet of BS Chandraskehar, Bishen Singh Bedi, EAS Prasanna, S Venkatraghavan, to the times of dangerous Anil Kumble, and now to the more recent Ravichander Ashwon and Harbhajan Singh.
A batsmen who can score runs in India against Indian spinners has to be really adept in handling all kinds of spin.
While Clive Lloyd & Alvin Kallicharan had the best performance against India, they have not been included as ESPN Cricinfo had many of the columns missing.
So I chose the following international players for the analysis against India
- Hashim Amla (South Africa)
- Alastair Cook (England)
- Matthew Hayden (Australia)
- Viv Richards (West Indies)
frames <- list("./data/amlaVsIndInInd.csv","./data/ancookVsIndInInd.csv","./data/mhaydenVsIndInInd.csv", "./data/vrichardsVsIndInInd.csv") names <- list("H Amla","AN Cook","M Hayden","Viv Riachards")
Excluding Clive Lloyd & Alvin Kallicharan the next best performer against India is Hashim Amla,followed by Alastair Cook, Viv Richards.
#With respect to strike rate, there is no contest when Viv Richards is around. He is clearly the best #striker of the ball regardless of whether it is the pacy wickets of #Australia/England or the spinning tracks of the subcontinent. After #Viv Richards, Hayden and Alastair Cook have good cumulative strike rates #in India relativeBatsmanSR(frames,names)
5. All time greats of Indian batting
I couldn’t resist checking out how the top Indian batsmen perform when playing in host countries So here is a look at how the top Indian batsmen perform against different host countries
6. Top Indian batsmen against Australia in Australia
The following Indian batsmen were chosen
- Sunil Gavaskar
- Sachin Tendulkar
- Virat Kohli
- Virendar Sehwag
- VVS Laxman
frames <- list("./data/tendulkarVsAusInAus.csv","./data/gavaskarVsAusInAus.csv","./data/kohliVsAusInAus.csv", "./data/sehwagVsAusInAus.csv","./data/vvslaxmanVsAusInAus.csv") names <- list("S Tendulkar","S Gavaskar","V Kohli","V Sehwag","VVS Laxman")
Virat Kohli has the best overall performance against Australia, with a current cumulative average of 60+ runs for the total number of innings played by him (15). With 15 matches the 2nd best is Virendar Sehwag, followed by VVS Laxman. Tendulkar maintains a cumulative average of 48+ runs for an excess of 30+ innings.
# Sehwag leads the strike rate against host Australia, followed by # Tendulkar in Australia and then Kohli relativeBatsmanSR(frames,names)
7. Top Indian batsmen against England in England
The top Indian batmen’s performances against England are shown below
- Rahul Dravid
- Dilip Vengsarkar
- Rahul Dravid
- Sourav Ganguly
- Virat Kohli
frames <- list("./data/tendulkarVsEngInEng.csv","./data/dravidVsEngInEng.csv","./data/vengsarkarVsEngInEng.csv", "./data/gangulyVsEngInEng.csv","./data/gavaskarVsEngInEng.csv","./data/kohliVsEngInEng.csv") names <- list("S Tendulkar","R Dravid","D Vengsarkar","S Ganguly","S Gavaskar","V Kohli")
Rahul Dravid has the best performance against England and edges out Tendulkar. He is followed by Tendulkar and then Sourav Ganguly. Note:Incidentally Virat Kohli’s performance against England in England so far has been extremely poor and he averages around 13-15 runs per innings. However he has a long way to go and I hope he catches up. In any case it will be an uphill climb for Kohli in England.
#Tendulkar, Ganguly and Dravid have the best strike rate and in that order. relativeBatsmanSR(frames,names)
8. Top Indian batsmen against West Indies in West Indies
frames <- list("./data/tendulkarVsWInWI.csv","./data/dravidVsWInWI.csv","./data/vvslaxmanVsWIInWI.csv", "./data/gavaskarVsWIInWI.csv") names <- list("S Tendulkar","R Dravid","VVS Laxman","S Gavaskar")
Against the West Indies Sunil Gavaskar is heads and shoulders above the rest. Gavaskar has a very impressive cumulative average against West Indies
# VVS Laxman followed by Tendulkar & then Dravid have a very # good strike rate against the West Indies relativeBatsmanCumulativeStrikeRate(frames,names)
9. World’s best spinners on tracks suited for pace & bounce
In this part I compare the performances of the top 3 spinners in recent years and check out how they perform on surfaces that are known for pace, and bounce. I have taken the following 3 spinners
- Anil Kumble (India)
- M Muralitharan (Sri Lanka)
- Shane Warne (Australia)
#kumbleEng=getPlayerData(30176 ,opposition=3,host=3,file="kumbleVsEngInEng.csv",type="bowling") #muraliEng=getPlayerData(49636 ,opposition=3,host=3,file="muraliVsEngInEng.csv",type="bowling") #warneEng=getPlayerData(8166 ,opposition=3,host=3,file="warneVsEngInEng.csv",type="bowling")
10. Top international spinners against England in England
frames <- list("./data/kumbleVsEngInEng.csv","./data/muraliVsEngInEng.csv","./data/warneVsEngInEng.csv") names <- list("Anil KUmble","M Muralitharan","Shane Warne")
Against England and in England, Muralitharan shines with a cumulative average of nearly 5 wickets per match with a peak of almost 8 wickets. Shane Warne has a steady average at 5 wickets and then Anil Kumble.
# The order relative cumulative Economy rate, Warne has the best figures,followed by Anil Kumble. Muralitharan # is much more expensive. relativeBowlerCumulativeAvgEconRate(frames,names)
11. Top international spinners against South Africa in South Africa
frames <- list("./data/kumbleVsSAInSA.csv","./data/muraliVsSAInSA.csv","./data/warneVsSAInSA.csv") names <- list("Anil Kumble","M Muralitharan","Shane Warne")
In South Africa too, Muralitharan has the best wicket taking performance averaging about 4 wickets. Warne averages around 3 wickets and Kumble around 2 wickets
# Muralitharan is expensive in South Africa too, while Kumble and Warne go neck-to-neck in the economy rate. # Kumble edges out Warne and has a better cumulative average economy rate relativeBowlerCumulativeAvgEconRate(frames,names)
11. Top international pacers against India in India
As a final analysis I check how the world’s pacers perform in India against India. India pitches are supposed to be flat devoid of bounce, while being terrific turners. Hence Indian pitches are more suited to spin bowling than pace bowling. This is changing these days.
The best performers against India in India are mostly the deadly pacemen of yesteryears
For this I have chosen the following bowlers
- Courtney Walsh (West Indies)
- Andy Roberts (West Indies)
- Malcolm Marshall
- Glenn McGrath
#cawalshInd=getPlayerData(53216 ,opposition=6,host=6,file="cawalshVsIndInInd.csv",type="bowling") #arobertsInd=getPlayerData(52817 ,opposition=6,host=6,file="arobertsIndInInd.csv",type="bowling") #mmarshallInd=getPlayerData(52419 ,opposition=6,host=6,file="mmarshallVsIndInInd.csv",type="bowling") #gmccgrathInd=getPlayerData(6565 ,opposition=6,host=6,file="mccgrathVsIndInInd.csv",type="bowling")
frames <- list("./data/cawalshVsIndInInd.csv","./data/arobertsIndInInd.csv","./data/mmarshallVsIndInInd.csv", "./data/mccgrathVsIndInInd.csv") names <- list("C Walsh","A Roberts","M Marshall","G McGrath")
Courtney Walsh has the best performance, followed by Andy Roberts followed by Andy Roberts and then Malcom Marshall who tips ahead of Glenn McGrath
#On the other hand McGrath has the best economy rate, followed by A Roberts and then Courtney Walsh relativeBowlerCumulativeAvgEconRate(frames,names)
12. ODI performance of a player against a specific country in the host country
This gets the data for MS Dhoni in ODI matches against Australia and in Australia
13. Twenty 20 performance of a player against a specific country in the host country
All the ODI and Twenty20 functions of cricketr can be used on the above dataframes of MS Dhoni.
Some key observations
Here are some key observations
- At the top of the batting spectrum is Don Bradman with a very impressive average 100-120 in matches played in England and Australia. Unfortunately there weren’t matches he played in other countries and different pitches. 2.Viv Richard has the best cumulative strike rate overall.
- Muralitharan strikes more often than Kumble or Warne even in pitches at ENgland, South Africa and West Indies. However Muralitharan is also the most expensive
- Warne and Kumble have a much better economy rate than Muralitharan.
- Sunil Gavaskar has an extremely impressive performance in West Indies.
- Rahul Dravid performs much better than Tendulkar in both England and West Indies.
- Virat Kohli has the best performance against Australia so far and hope he maintains his stellar performance followed by Sehwag. However Kohli’s performance in England has been very poor
- West Indies batsmen and bowlers seem to thrive on Indian pitches, with Clive Lloyd and Alvin Kalicharan at the top of the list.
You may like my Shiny apps on cricket
- Inswinger- Analyzing International. T20s
- GooglyPlus – An app for analyzing IPL
- Sixer – App based on R package cricketr
- Exploring Quantum Gate operations with QCSimulator
- Neural Networks: The mechanics of backpropagation
- Re-introducing cricketr! : An R package to analyze performances of cricketers
- yorkr crashes the IPL party ! – Part 1
- cricketr and yorkr books – Paperback now in Amazon
- Hand detection through Haartraining: A hands-on approach
To see all my posts see Index of posts