Introduction
“So in war, the way is to avoid what is strong, and strike at what is weak.”
“Thus the expert in battle moves the enemy, and is not moved by him.”
“Appear weak when you are strong, and strong when you are weak.”
The Art of War - Sun Tzu
This post is a continuation of my 2 earlier posts based on the enhancement of my R package yorkr to includ functions to handle Twenty20 matches. This is the 3rd part of the Twenty20 based functions, the 2 earlier ones were
- yorkr pads up for the Twenty20s: Part 1- Analyzing team“s match performance.
- yorkr pads up for the Twenty20s: Part 2-Head to head confrontation between teams
This post deals with Class 3 functions, namely the performances of a team in all T20 matches against all oppositions for e.g India/Australia/South Africa against all oppositions in all matches. In other words it is the performance of the team against the rest of the world.
If you are passionate about cricket, and love analyzing cricket performances, then check out my 2 racy books on cricket! In my books, I perform detailed yet compact analysis of performances of both batsmen, bowlers besides evaluating team & match performances in Tests , ODIs, T20s & IPL. You can buy my books on cricket from Amazon at $12.99 for the paperback and $4.99/$6.99 respectively for the kindle versions. The books can be accessed at Cricket analytics with cricketr and Beaten by sheer pace-Cricket analytics with yorkr A must read for any cricket lover! Check it out!!
This post has also been published at RPubs [yorkrT20-Part3]http://rpubs.com/tvganesh/yorkrT20-Part3) and can also be downloaded as a PDF document from yorkrT20-Part3.pdf.
You can clone/fork the code for the package yorkr from Github at yorkr-package
Checkout my interactive Shiny apps GooglyPlus (plots & tables) and Googly (only plots) which can be used to analyze IPL players, teams and matches.
Note: To do similar analysis you can use my yorkrT20templates. See my post Analysis of International T20 matches with yorkr templates
Important note 1: Do check out all the posts on the python avatar of yorkr, namely ‘yorkpy’ in my post ‘Pitching yorkpy … short of good length to IPL – Part 1
The list of functions in Class 3 are
- teamBattingScorecardAllOppnAllMatches()
- teamBatsmenPartnershipAllOppnAllMatches()
- teamBatsmenPartnershipAllOppnAllMatchesPlot()
- teamBatsmenVsBowlersAllOppnAllMatchesRept()
- teamBatsmenVsBowlersAllOppnAllMatchesPlot()
- teamBowlingScorecardAllOppnAllMatchesMain()
- teamBowlersVsBatsmenAllOppnAllMatchesRept()
- teamBowlersVsBatsmenAllOppnAllMatchesPlot()
- teamBowlingWicketKindAllOppnAllMatches()
- teamBowlingWicketRunsAllOppnAllMatches()
Note 1: The yorkr package in its current avatar only supports ODI & Twenty20 matches. I will be upgrading the package to handle IPL in the months to come.
Note 2: As in the previous parts the plots usually have the plot=TRUE/FALSE parameter. This is to allow the user to get a return value of the desired dataframe. The user can choose to plot this, in any way he/she likes for e.g in interactive charts using rcharts, ggvis,googleVis,plotly etc
1. Install the package from CRAN
The yorkr package can be installed directly from CRAN now! Install the yorkr package.
if (!require("yorkr")) {
install.packages("yorkr")
library("yorkr")
}
rm(list=ls())
2. Get data for all matches against all oppositions for a team
We can get all matches against all oppositions for a team/country using the function below. The dir parameter should point to the folder in which the RData files where the individual T20 matches exist. This function creates a data frame of all the matches and also saves the resulting dataframe as RData
setwd("C:/software/cricket-package/york-test/yorkrData/Twenty20/T20-team-allmatches-allOppositions")
matches <-getAllMatchesAllOpposition("India",dir=".",save=TRUE)
dim(matches)
## [1] 14380 25
“`
3. Save data for all matches against all oppositions
This can be done locally using the function below. This function gets all the T20 matches of the country/team against all other countrioes//teams and combines them into a single dataframe and saves it in the current folder. The current implementation expects that the the RData files of individual matches are in ../data folder. Since I already have converted this I will not be running this again
4. Load data directly for all matches between 2 teams
As in my earlier posts (yorkr-Part1 & yorkr-Part2) I have however already saved the data, for all matches of the individual countries, against all oppositons. The data for these matches for the individual teams/countries can be downloaded directly from Github folder at T20-team-allmatches-allOppositions
Note: The dataframe for the different for all the matches of a country against all oppositons can be loaded directly into your code.Feel free to download the zip of the data and to perform any data mining on them.
If you do come up with interesting insights, I would appreciate if attribute the source to Cricsheet(http://cricsheet.org), and my package yorkr and my blog Giga thoughts, besides dropping me a note.*
As in my earlier post I will be directly loading the saved files. For the illustration of the functions, I will use India in all the functions, (for obvious reasons) and will randomly use the data from the rest of the top 8 teams
setwd("C:/software/cricket-package/york-test/yorkrData/Twenty20/T20-team-allmatches-allOppositions")
load("allMatchesAllOpposition-India.RData")
ind_matches <- matches
load("allMatchesAllOpposition-Australia.RData")
aus_matches <- matches
load("allMatchesAllOpposition-New Zealand.RData")
nz_matches <- matches
load("allMatchesAllOpposition-Pakistan.RData")
pak_matches <- matches
load("allMatchesAllOpposition-England.RData")
eng_matches <- matches
load("allMatchesAllOpposition-Sri Lanka.RData")
sl_matches <- matches
load("allMatchesAllOpposition-West Indies.RData")
wi_matches <- matches
load("allMatchesAllOpposition-South Africa.RData")
sa_matches <- matches
5. Team T20 Batting Scorecard (all matches with opposition)
The following functions shows the batting scorecards in each country. It returns a dataframe with the top batsmen in each country
m <-teamBattingScorecardAllOppnAllMatches(ind_matches,theTeam="India")
## Total= 8663
m
## Source: local data frame [46 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 V Kohli 882 124 27 1215
## 2 SK Raina 806 102 39 1114
## 3 RG Sharma 800 91 37 1053
## 4 Yuvraj Singh 656 59 60 933
## 5 G Gambhir 739 110 10 911
## 6 MS Dhoni 723 60 24 864
## 7 V Sehwag 228 36 13 330
## 8 AM Rahane 256 28 6 302
## 9 RV Uthappa 204 26 6 249
## 10 S Dhawan 193 28 8 248
## .. ... ... ... ... ...
m <-teamBattingScorecardAllOppnAllMatches(aus_matches,theTeam="Australia")
## Total= 11743
m
## Source: local data frame [70 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 DA Warner 1030 139 67 1465
## 2 SR Watson 888 103 76 1315
## 3 CL White 726 71 44 984
## 4 AJ Finch 566 95 36 874
## 5 DJ Hussey 615 41 34 756
## 6 MEK Hussey 518 58 25 721
## 7 MJ Clarke 467 29 10 488
## 8 GJ Bailey 331 37 20 470
## 9 BJ Haddin 342 30 13 402
## 10 RT Ponting 294 42 11 401
## .. ... ... ... ... ...
m <-teamBattingScorecardAllOppnAllMatches(pak_matches,theTeam="Pakistan")
## Total= 12943
m
## Source: local data frame [58 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 Umar Akmal 1184 112 48 1506
## 2 Mohammad Hafeez 1254 156 36 1466
## 3 Shahid Afridi 812 89 63 1255
## 4 Shoaib Malik 1068 101 23 1206
## 5 Ahmed Shehzad 799 102 24 941
## 6 Kamran Akmal 705 88 27 871
## 7 Misbah-ul-Haq 685 46 26 770
## 8 Imran Nazir 338 55 21 468
## 9 Salman Butt 410 58 6 467
## 10 Younis Khan 331 32 12 427
## .. ... ... ... ... ...
m <-teamBattingScorecardAllOppnAllMatches(nz_matches,theTeam="New Zealand")
## Total= 11656
m
## Source: local data frame [62 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 BB McCullum 1501 199 89 2106
## 2 MJ Guptill 1259 155 68 1665
## 3 LRPL Taylor 900 76 45 1126
## 4 KS Williamson 650 101 10 844
## 5 SB Styris 443 38 25 554
## 6 JEC Franklin 371 28 23 463
## 7 JDP Oram 318 37 20 451
## 8 JD Ryder 336 45 16 434
## 9 C Munro 227 23 27 377
## 10 RJ Nicol 283 33 11 327
## .. ... ... ... ... ...
m <-teamBattingScorecardAllOppnAllMatches(eng_matches,theTeam="England")
## Total= 11215
m
## Source: local data frame [65 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 EJG Morgan 938 108 53 1285
## 2 KP Pietersen 810 119 32 1176
## 3 AD Hales 790 116 35 1111
## 4 LJ Wright 540 68 31 759
## 5 RS Bopara 588 54 17 711
## 6 PD Collingwood 451 38 24 583
## 7 JC Buttler 410 43 23 562
## 8 MJ Lumb 394 64 21 552
## 9 C Kieswetter 456 47 23 526
## 10 OA Shah 276 26 13 347
## .. ... ... ... ... ...
m <-teamBattingScorecardAllOppnAllMatches(wi_matches,theTeam="West Indies")
## Total= 9292
m
## Source: local data frame [54 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 CH Gayle 958 122 87 1406
## 2 DJ Bravo 792 57 43 979
## 3 MN Samuels 764 76 46 952
## 4 LMP Simmons 633 68 25 732
## 5 KA Pollard 453 50 36 664
## 6 DR Smith 463 62 31 582
## 7 DJG Sammy 330 43 27 526
## 8 J Charles 382 59 12 456
## 9 ADS Fletcher 341 26 19 387
## 10 S Chanderpaul 337 34 5 343
## .. ... ... ... ... ...
m <-teamBattingScorecardAllOppnAllMatches(sl_matches,theTeam="Sri Lanka")
## Total= 9572
m
## Source: local data frame [54 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 TM Dilshan 1235 186 26 1556
## 2 DPMD Jayawardene 1005 157 28 1346
## 3 KC Sangakkara 1088 132 18 1320
## 4 AD Mathews 640 54 24 794
## 5 MDKJ Perera 435 60 23 596
## 6 ST Jayasuriya 428 70 21 581
## 7 NLTC Perera 310 38 22 480
## 8 CK Kapugedera 329 36 16 417
## 9 LD Chandimal 371 31 7 380
## 10 HDRL Thirimanne 240 26 5 277
## .. ... ... ... ... ...
6. Team Batting Scorecard in Twenty20 matches against all oppositions
The following functions show the best batsmen from the opposition ‘theTeam’ in the ‘matches’. For e.g. when the matches=ind_matches and theTeam=“England” then the returned dataframe shows the best English batsmen against India
m <-teamBattingScorecardAllOppnAllMatches(matches=ind_matches,theTeam="England")
## Total= 1169
m
## Source: local data frame [26 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 EJG Morgan 96 15 10 176
## 2 KP Pietersen 107 18 5 171
## 3 AD Hales 112 14 6 149
## 4 RS Bopara 94 9 2 103
## 5 SR Patel 73 6 2 79
## 6 JC Buttler 54 2 4 69
## 7 C Kieswetter 47 8 3 65
## 8 LJ Wright 50 4 3 62
## 9 MJ Lumb 39 6 2 51
## 10 VS Solanki 30 5 1 43
## .. ... ... ... ... ...
m <-teamBattingScorecardAllOppnAllMatches(matches=ind_matches,theTeam="Australia")
## Total= 1767
m
## Source: local data frame [40 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 SR Watson 173 16 20 284
## 2 AJ Finch 164 33 5 249
## 3 DA Warner 134 14 14 204
## 4 MS Wade 93 6 5 125
## 5 DJ Hussey 81 5 6 101
## 6 ML Hayden 63 5 6 79
## 7 RT Ponting 52 13 NA 76
## 8 MJ Clarke 54 3 1 65
## 9 A Symonds 43 4 2 63
## 10 AC Gilchrist 38 7 3 59
## .. ... ... ... ... ...
m <-teamBattingScorecardAllOppnAllMatches(aus_matches,theTeam="New Zealand")
## Total= 727
m
## Source: local data frame [27 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 BB McCullum 138 22 12 228
## 2 SB Styris 54 9 3 84
## 3 JDP Oram 34 5 6 67
## 4 GJ Hopkins 30 5 3 57
## 5 JEC Franklin 52 3 2 53
## 6 MJ Guptill 47 7 NA 47
## 7 NT Broom 26 6 NA 36
## 8 NL McCullum 13 2 2 25
## 9 GD Elliott 26 2 NA 23
## 10 SP Fleming 13 3 NA 18
## .. ... ... ... ... ...
m <-teamBattingScorecardAllOppnAllMatches(wi_matches,theTeam="Sri Lanka")
## Total= 1225
m
## Source: local data frame [21 x 5]
##
## batsman ballsPlayed fours sixes runs
## (fctr) (int) (int) (int) (dbl)
## 1 TM Dilshan 224 42 4 334
## 2 DPMD Jayawardene 149 21 5 202
## 3 KC Sangakkara 119 12 3 135
## 4 ST Jayasuriya 91 14 3 111
## 5 AD Mathews 52 6 7 98
## 6 MDKJ Perera 52 10 3 78
## 7 DSNFG Jayasuriya 52 5 3 66
## 8 HDRL Thirimanne 42 3 2 48
## 9 LD Chandimal 20 4 2 41
## 10 KMDN Kulasekara 18 3 1 30
## .. ... ... ... ... ...
7. Team Batting Partnerships in Twenty20 matches against all oppositions
This gives the top batting partnerships in each team in all its matches against all oppositions. The report can either be a ‘summary’ or a ‘detailed’ breakup of the batting partnerships.
m <- teamBatsmenPartnershipAllOppnAllMatches(ind_matches,theTeam='India')
m
## Source: local data frame [46 x 2]
##
## batsman totalRuns
## (fctr) (dbl)
## 1 V Kohli 1215
## 2 SK Raina 1114
## 3 RG Sharma 1053
## 4 Yuvraj Singh 933
## 5 G Gambhir 911
## 6 MS Dhoni 864
## 7 V Sehwag 330
## 8 AM Rahane 302
## 9 RV Uthappa 249
## 10 S Dhawan 248
## .. ... ...
m <- teamBatsmenPartnershipAllOppnAllMatches(matches,theTeam='India',report="detailed")
head(m,30)
## batsman nonStriker partnershipRuns totalRuns
## 1 RG Sharma G Gambhir 26 309
## 2 RG Sharma SK Raina 25 309
## 3 RG Sharma Yuvraj Singh 41 309
## 4 RG Sharma MS Dhoni 31 309
## 5 RG Sharma V Sehwag 0 309
## 6 RG Sharma V Kohli 110 309
## 7 RG Sharma AM Rahane 24 309
## 8 RG Sharma S Dhawan 33 309
## 9 RG Sharma RV Uthappa 13 309
## 10 RG Sharma IK Pathan 6 309
## 11 SK Raina RG Sharma 37 250
## 12 SK Raina Yuvraj Singh 50 250
## 13 SK Raina MS Dhoni 73 250
## 14 SK Raina YK Pathan 51 250
## 15 SK Raina KD Karthik 16 250
## 16 SK Raina V Kohli 21 250
## 17 SK Raina AR Patel 0 250
## 18 SK Raina AT Rayudu 2 250
## 19 V Kohli RG Sharma 70 146
## 20 V Kohli SK Raina 11 146
## 21 V Kohli Yuvraj Singh 37 146
## 22 V Kohli MS Dhoni 9 146
## 23 V Kohli M Vijay 2 146
## 24 V Kohli V Sehwag 2 146
## 25 V Kohli AM Rahane 15 146
## 26 MS Dhoni RG Sharma 45 124
## 27 MS Dhoni SK Raina 53 124
## 28 MS Dhoni Yuvraj Singh 5 124
## 29 MS Dhoni Harbhajan Singh 8 124
## 30 MS Dhoni V Kohli 0 124
9. More Team Batting Partnerships in Twenty20 matches against all oppositions
When we use the dataframe ind_matches (matches of India against all opoositions) and choose another country in the theTeam then we will get the names of those top batsmen against India.
m <- teamBatsmenPartnershipAllOppnAllMatches(ind_matches,theTeam='England')
m
## Source: local data frame [26 x 2]
##
## batsman totalRuns
## (fctr) (dbl)
## 1 EJG Morgan 176
## 2 KP Pietersen 171
## 3 AD Hales 149
## 4 RS Bopara 103
## 5 SR Patel 79
## 6 JC Buttler 69
## 7 C Kieswetter 65
## 8 LJ Wright 62
## 9 MJ Lumb 51
## 10 VS Solanki 43
## .. ... ...
m <- teamBatsmenPartnershipAllOppnAllMatches(ind_matches,theTeam='South Africa', report="detailed")
m[1:30,]
## batsman nonStriker partnershipRuns totalRuns
## 1 AB de Villiers GC Smith 28 208
## 2 AB de Villiers JP Duminy 40 208
## 3 AB de Villiers MV Boucher 19 208
## 4 AB de Villiers JA Morkel 11 208
## 5 AB de Villiers JH Kallis 17 208
## 6 AB de Villiers F du Plessis 24 208
## 7 AB de Villiers HM Amla 49 208
## 8 AB de Villiers JM Kemp 6 208
## 9 AB de Villiers MN van Wyk 14 208
## 10 JP Duminy AB de Villiers 20 173
## 11 JP Duminy MV Boucher 4 173
## 12 JP Duminy F du Plessis 33 173
## 13 JP Duminy F Behardien 88 173
## 14 JP Duminy DA Miller 28 173
## 15 JP Duminy MN van Wyk 0 173
## 16 F du Plessis AB de Villiers 45 143
## 17 F du Plessis JP Duminy 86 143
## 18 F du Plessis HM Amla 12 143
## 19 JH Kallis GC Smith 59 140
## 20 JH Kallis AB de Villiers 8 140
## 21 JH Kallis LE Bosman 12 140
## 22 JH Kallis CA Ingram 59 140
## 23 JH Kallis RE Levi 2 140
## 24 JA Morkel AB de Villiers 12 109
## 25 JA Morkel MV Boucher 34 109
## 26 JA Morkel J Botha 8 109
## 27 JA Morkel F Behardien 16 109
## 28 JA Morkel DW Steyn 7 109
## 29 JA Morkel JM Kemp 3 109
## 30 JA Morkel JJ van der Wath 28 109
10. Team Batting partnerships of other countries in Twenty20 matches against all oppositions
m <- teamBatsmenPartnershipAllOppnAllMatches(eng_matches,theTeam='India',report="detailed")
head(m,30)
## batsman nonStriker partnershipRuns totalRuns
## 1 V Kohli G Gambhir 78 184
## 2 V Kohli RV Uthappa 4 184
## 3 V Kohli Yuvraj Singh 10 184
## 4 V Kohli RG Sharma 2 184
## 5 V Kohli SK Raina 42 184
## 6 V Kohli AM Rahane 3 184
## 7 V Kohli S Dhawan 45 184
## 8 MS Dhoni RV Uthappa 5 167
## 9 MS Dhoni Yuvraj Singh 4 167
## 10 MS Dhoni IK Pathan 2 167
## 11 MS Dhoni RG Sharma 9 167
## 12 MS Dhoni SK Raina 71 167
## 13 MS Dhoni RA Jadeja 11 167
## 14 MS Dhoni YK Pathan 36 167
## 15 MS Dhoni AT Rayudu 18 167
## 16 MS Dhoni R Ashwin 11 167
## 17 G Gambhir V Sehwag 51 162
## 18 G Gambhir RV Uthappa 7 162
## 19 G Gambhir Yuvraj Singh 2 162
## 20 G Gambhir IK Pathan 11 162
## 21 G Gambhir RG Sharma 25 162
## 22 G Gambhir SK Raina 10 162
## 23 G Gambhir RA Jadeja 15 162
## 24 G Gambhir AM Rahane 18 162
## 25 G Gambhir V Kohli 23 162
## 26 SK Raina G Gambhir 2 161
## 27 SK Raina MS Dhoni 80 161
## 28 SK Raina RG Sharma 16 161
## 29 SK Raina V Kohli 34 161
## 30 SK Raina P Kumar 0 161
m <- teamBatsmenPartnershipAllOppnAllMatches(sa_matches,theTeam='South Africa', report="detailed")
head(m,30)
## batsman nonStriker partnershipRuns totalRuns
## 1 JP Duminy LE Bosman 3 1528
## 2 JP Duminy GC Smith 78 1528
## 3 JP Duminy JH Kallis 77 1528
## 4 JP Duminy AB de Villiers 207 1528
## 5 JP Duminy MV Boucher 93 1528
## 6 JP Duminy JA Morkel 143 1528
## 7 JP Duminy RE van der Merwe 12 1528
## 8 JP Duminy DW Steyn 10 1528
## 9 JP Duminy J Botha 34 1528
## 10 JP Duminy VB van Jaarsveld 50 1528
## 11 JP Duminy HH Gibbs 0 1528
## 12 JP Duminy HM Amla 104 1528
## 13 JP Duminy ND McKenzie 20 1528
## 14 JP Duminy F Behardien 117 1528
## 15 JP Duminy RJ Peterson 32 1528
## 16 JP Duminy Q de Kock 13 1528
## 17 JP Duminy DA Miller 284 1528
## 18 JP Duminy RR Hendricks 15 1528
## 19 JP Duminy R McLaren 1 1528
## 20 JP Duminy WD Parnell 5 1528
## 21 JP Duminy D Wiese 6 1528
## 22 JP Duminy F du Plessis 119 1528
## 23 JP Duminy JL Ontong 17 1528
## 24 JP Duminy CA Ingram 67 1528
## 25 JP Duminy HG Kuhn 6 1528
## 26 JP Duminy MN van Wyk 7 1528
## 27 JP Duminy AN Petersen 8 1528
## 28 AB de Villiers GC Smith 72 1167
## 29 AB de Villiers JH Kallis 81 1167
## 30 AB de Villiers JP Duminy 263 1167
m <- teamBatsmenPartnershipAllOppnAllMatches(sl_matches,theTeam='Sri Lanka',report="summary")
m
## Source: local data frame [54 x 2]
##
## batsman totalRuns
## (fctr) (dbl)
## 1 TM Dilshan 1556
## 2 DPMD Jayawardene 1346
## 3 KC Sangakkara 1320
## 4 AD Mathews 794
## 5 MDKJ Perera 596
## 6 ST Jayasuriya 581
## 7 NLTC Perera 480
## 8 CK Kapugedera 417
## 9 LD Chandimal 380
## 10 HDRL Thirimanne 277
## .. ... ...
m <- teamBatsmenPartnershipAllOppnAllMatches(eng_matches,theTeam='England',report="summary")
m
## Source: local data frame [65 x 2]
##
## batsman totalRuns
## (fctr) (dbl)
## 1 EJG Morgan 1285
## 2 KP Pietersen 1176
## 3 AD Hales 1111
## 4 LJ Wright 759
## 5 RS Bopara 711
## 6 PD Collingwood 583
## 7 JC Buttler 562
## 8 MJ Lumb 552
## 9 C Kieswetter 526
## 10 OA Shah 347
## .. ... ...
m <- teamBatsmenPartnershipAllOppnAllMatches(wi_matches,theTeam='Australia',report="summary")
m
## Source: local data frame [31 x 2]
##
## batsman totalRuns
## (fctr) (dbl)
## 1 DA Warner 311
## 2 SR Watson 240
## 3 MEK Hussey 147
## 4 BJ Haddin 146
## 5 GJ Bailey 135
## 6 DJ Hussey 57
## 7 AC Voges 51
## 8 SE Marsh 50
## 9 GJ Maxwell 45
## 10 L Ronchi 36
## .. ... ...
m <- teamBatsmenPartnershipAllOppnAllMatches(nz_matches,theTeam='England',report="summary")
m
## Source: local data frame [35 x 2]
##
## batsman totalRuns
## (fctr) (dbl)
## 1 LJ Wright 273
## 2 AD Hales 194
## 3 MJ Lumb 188
## 4 EJG Morgan 152
## 5 JC Buttler 140
## 6 KP Pietersen 112
## 7 OA Shah 91
## 8 PD Collingwood 86
## 9 IR Bell 73
## 10 JE Root 68
## .. ... ...
11. Team Batting Partnership plots in Twenty20 matches against all oppositions
Graphical plot of batting partnerships for the countries
teamBatsmenPartnershipAllOppnAllMatchesPlot(ind_matches,"India",main="India")
![]()
teamBatsmenPartnershipAllOppnAllMatchesPlot(pak_matches,"Pakistan",main="Pakistan")
![]()
teamBatsmenPartnershipAllOppnAllMatchesPlot(aus_matches,"Australia",main="Australia")
![]()
12. Top opposition batting partnerships in Twenty20 matches against all oppositions
This gives the best performance of the team against a specified country
teamBatsmenPartnershipAllOppnAllMatchesPlot(ind_matches,"India",main="West Indies")
![]()
teamBatsmenPartnershipAllOppnAllMatchesPlot(sl_matches,"Sri Lanka",main="India")
![]()
teamBatsmenPartnershipAllOppnAllMatchesPlot(nz_matches,"New Zealand",main="South Africa")
![]()
13. Batsmen vs Bowlers in Twenty20 matches against all oppositions
The function below gives the top performance of batsmen against the opposition countries
m <-teamBatsmenVsBowlersAllOppnAllMatchesRept(ind_matches,"India",rank=0)
m
## Source: local data frame [46 x 2]
##
## batsman runsScored
## (fctr) (dbl)
## 1 V Kohli 1215
## 2 SK Raina 1114
## 3 RG Sharma 1053
## 4 Yuvraj Singh 933
## 5 G Gambhir 911
## 6 MS Dhoni 864
## 7 V Sehwag 330
## 8 AM Rahane 302
## 9 RV Uthappa 249
## 10 S Dhawan 248
## .. ... ...
m <-teamBatsmenVsBowlersAllOppnAllMatchesRept(ind_matches,"India",rank=1,dispRows=30)
m
## Source: local data frame [30 x 3]
## Groups: batsman [1]
##
## batsman bowler runs
## (fctr) (fctr) (dbl)
## 1 V Kohli Shahid Afridi 43
## 2 V Kohli SR Watson 39
## 3 V Kohli Imran Tahir 34
## 4 V Kohli CJ Boyce 32
## 5 V Kohli Saeed Ajmal 32
## 6 V Kohli AJ Tye 31
## 7 V Kohli HMRKB Herath 29
## 8 V Kohli TT Bresnan 28
## 9 V Kohli KW Richardson 27
## 10 V Kohli SM Boland 27
## .. ... ... ...
m <-teamBatsmenVsBowlersAllOppnAllMatchesRept(ind_matches,"India",rank=2,dispRows=50)
m
## Source: local data frame [50 x 3]
## Groups: batsman [1]
##
## batsman bowler runs
## (fctr) (fctr) (dbl)
## 1 SK Raina RK Kleinveldt 33
## 2 SK Raina JH Kallis 31
## 3 SK Raina T Thushara 31
## 4 SK Raina AJ Tye 29
## 5 SK Raina TT Bresnan 29
## 6 SK Raina SR Watson 26
## 7 SK Raina JC Tredwell 26
## 8 SK Raina IE O'Brien 26
## 9 SK Raina Mohammad Nabi 22
## 10 SK Raina GP Swann 22
## .. ... ... ...
m <-teamBatsmenVsBowlersAllOppnAllMatchesRept(matches=ind_matches,theTeam="England",rank=1,dispRows=25)
m
## Source: local data frame [15 x 3]
## Groups: batsman [1]
##
## batsman bowler runs
## (fctr) (fctr) (dbl)
## 1 EJG Morgan R Ashwin 24
## 2 EJG Morgan AB Dinda 22
## 3 EJG Morgan KV Sharma 18
## 4 EJG Morgan RA Jadeja 17
## 5 EJG Morgan MM Sharma 16
## 6 EJG Morgan RG Sharma 15
## 7 EJG Morgan V Kohli 14
## 8 EJG Morgan Mohammed Shami 13
## 9 EJG Morgan Yuvraj Singh 11
## 10 EJG Morgan P Kumar 10
## 11 EJG Morgan PP Chawla 7
## 12 EJG Morgan P Awana 7
## 13 EJG Morgan IK Pathan 1
## 14 EJG Morgan MM Patel 1
## 15 EJG Morgan Harbhajan Singh 0
m <-teamBatsmenVsBowlersAllOppnAllMatchesRept(ind_matches,"Australia",rank=0)
m
## Source: local data frame [40 x 2]
##
## batsman runsScored
## (fctr) (dbl)
## 1 SR Watson 284
## 2 AJ Finch 249
## 3 DA Warner 204
## 4 MS Wade 125
## 5 DJ Hussey 101
## 6 ML Hayden 79
## 7 RT Ponting 76
## 8 MJ Clarke 65
## 9 A Symonds 63
## 10 AC Gilchrist 59
## .. ... ...
14. Batsmen vs Bowlers in Twenty20 matches against all oppositions (continued)
m <-teamBatsmenVsBowlersAllOppnAllMatchesRept(eng_matches,"India",rank=1,dispRows=30)
m
## Source: local data frame [13 x 3]
## Groups: batsman [1]
##
## batsman bowler runs
## (fctr) (fctr) (dbl)
## 1 V Kohli TT Bresnan 28
## 2 V Kohli LJ Wright 26
## 3 V Kohli CR Woakes 25
## 4 V Kohli JC Tredwell 21
## 5 V Kohli ST Finn 17
## 6 V Kohli MM Ali 15
## 7 V Kohli SCJ Broad 14
## 8 V Kohli JW Dernbach 10
## 9 V Kohli RS Bopara 9
## 10 V Kohli SC Meaker 7
## 11 V Kohli HF Gurney 6
## 12 V Kohli GP Swann 5
## 13 V Kohli DR Briggs 1
m <-teamBatsmenVsBowlersAllOppnAllMatchesRept(aus_matches,"Sri Lanka",rank=0)
m
## Source: local data frame [24 x 2]
##
## batsman runsScored
## (fctr) (dbl)
## 1 TM Dilshan 247
## 2 DPMD Jayawardene 209
## 3 KC Sangakkara 177
## 4 NLTC Perera 80
## 5 LD Chandimal 55
## 6 BMAJ Mendis 55
## 7 J Mubarak 49
## 8 AD Mathews 48
## 9 MDKJ Perera 48
## 10 WPUJC Vaas 21
## .. ... ...
m <-teamBatsmenVsBowlersAllOppnAllMatchesRept(sa_matches,"England",rank=0)
m
## Source: local data frame [30 x 2]
##
## batsman runsScored
## (fctr) (dbl)
## 1 EJG Morgan 145
## 2 C Kieswetter 117
## 3 KP Pietersen 116
## 4 PD Collingwood 90
## 5 IJL Trott 84
## 6 OA Shah 74
## 7 JC Buttler 72
## 8 AD Hales 60
## 9 MJ Prior 42
## 10 RS Bopara 39
## .. ... ...
15. Batsmen vs Bowlers Plot in Twenty20 matches against all oppositions
The following functions plot the performances of the batsman based on the rank chosen against opposition bowlers. Note: The rank has to be >0
d <- teamBatsmenVsBowlersAllOppnAllMatchesRept(ind_matches,"India",rank=1,dispRows=50)
d
## Source: local data frame [50 x 3]
## Groups: batsman [1]
##
## batsman bowler runs
## (fctr) (fctr) (dbl)
## 1 V Kohli Shahid Afridi 43
## 2 V Kohli SR Watson 39
## 3 V Kohli Imran Tahir 34
## 4 V Kohli CJ Boyce 32
## 5 V Kohli Saeed Ajmal 32
## 6 V Kohli AJ Tye 31
## 7 V Kohli HMRKB Herath 29
## 8 V Kohli TT Bresnan 28
## 9 V Kohli KW Richardson 27
## 10 V Kohli SM Boland 27
## .. ... ... ...
teamBatsmenVsBowlersAllOppnAllMatchesPlot(d)
![]()
e <- teamBatsmenVsBowlersAllOppnAllMatchesPlot(d,plot=FALSE)
e
## Source: local data frame [50 x 3]
## Groups: batsman [1]
##
## batsman bowler runs
## (fctr) (fctr) (dbl)
## 1 V Kohli Shahid Afridi 43
## 2 V Kohli SR Watson 39
## 3 V Kohli Imran Tahir 34
## 4 V Kohli CJ Boyce 32
## 5 V Kohli Saeed Ajmal 32
## 6 V Kohli AJ Tye 31
## 7 V Kohli HMRKB Herath 29
## 8 V Kohli TT Bresnan 28
## 9 V Kohli KW Richardson 27
## 10 V Kohli SM Boland 27
## .. ... ... ...
d <- teamBatsmenVsBowlersAllOppnAllMatchesRept(ind_matches,"India",rank=2,dispRows=50)
teamBatsmenVsBowlersAllOppnAllMatchesPlot(d)
![]()
d <- teamBatsmenVsBowlersAllOppnAllMatchesRept(ind_matches,"South Africa",rank=1,dispRows=30)
d
## Source: local data frame [21 x 3]
## Groups: batsman [1]
##
## batsman bowler runs
## (fctr) (fctr) (dbl)
## 1 AB de Villiers Yuvraj Singh 27
## 2 AB de Villiers R Ashwin 21
## 3 AB de Villiers S Aravind 18
## 4 AB de Villiers RP Singh 14
## 5 AB de Villiers Harbhajan Singh 13
## 6 AB de Villiers B Kumar 13
## 7 AB de Villiers MM Sharma 12
## 8 AB de Villiers RA Jadeja 11
## 9 AB de Villiers YK Pathan 11
## 10 AB de Villiers Z Khan 9
## .. ... ... ...
teamBatsmenVsBowlersAllOppnAllMatchesPlot(d)
![]()
d <-teamBatsmenVsBowlersAllOppnAllMatchesRept(matches=ind_matches,"England",rank=1,dispRows=50)
d
## Source: local data frame [15 x 3]
## Groups: batsman [1]
##
## batsman bowler runs
## (fctr) (fctr) (dbl)
## 1 EJG Morgan R Ashwin 24
## 2 EJG Morgan AB Dinda 22
## 3 EJG Morgan KV Sharma 18
## 4 EJG Morgan RA Jadeja 17
## 5 EJG Morgan MM Sharma 16
## 6 EJG Morgan RG Sharma 15
## 7 EJG Morgan V Kohli 14
## 8 EJG Morgan Mohammed Shami 13
## 9 EJG Morgan Yuvraj Singh 11
## 10 EJG Morgan P Kumar 10
## 11 EJG Morgan PP Chawla 7
## 12 EJG Morgan P Awana 7
## 13 EJG Morgan IK Pathan 1
## 14 EJG Morgan MM Patel 1
## 15 EJG Morgan Harbhajan Singh 0
teamBatsmenVsBowlersAllOppnAllMatchesPlot(d)
![]()
15. Batsmen vs Bowlers Plot in Twenty20 matches against all oppositions (continued)
d <- teamBatsmenVsBowlersAllOppnAllMatchesRept(sa_matches,"South Africa",rank=1,dispRows=50)
d
## Source: local data frame [50 x 3]
## Groups: batsman [1]
##
## batsman bowler runs
## (fctr) (fctr) (dbl)
## 1 JP Duminy Saeed Ajmal 63
## 2 JP Duminy BAW Mendis 63
## 3 JP Duminy JR Hopes 58
## 4 JP Duminy DJ Hussey 48
## 5 JP Duminy KD Mills 46
## 6 JP Duminy TG Southee 43
## 7 JP Duminy CB Mpofu 42
## 8 JP Duminy Shahid Afridi 40
## 9 JP Duminy SW Tait 38
## 10 JP Duminy NL McCullum 32
## .. ... ... ...
teamBatsmenVsBowlersAllOppnAllMatchesPlot(d)
![]()
e <- teamBatsmenVsBowlersAllOppnAllMatchesPlot(d,plot=FALSE)
e
## Source: local data frame [50 x 3]
## Groups: batsman [1]
##
## batsman bowler runs
## (fctr) (fctr) (dbl)
## 1 JP Duminy Saeed Ajmal 63
## 2 JP Duminy BAW Mendis 63
## 3 JP Duminy JR Hopes 58
## 4 JP Duminy DJ Hussey 48
## 5 JP Duminy KD Mills 46
## 6 JP Duminy TG Southee 43
## 7 JP Duminy CB Mpofu 42
## 8 JP Duminy Shahid Afridi 40
## 9 JP Duminy SW Tait 38
## 10 JP Duminy NL McCullum 32
## .. ... ... ...
d <- teamBatsmenVsBowlersAllOppnAllMatchesRept(sl_matches,"Sri Lanka",rank=1,dispRows=50)
teamBatsmenVsBowlersAllOppnAllMatchesPlot(d)
![]()
d <- teamBatsmenVsBowlersAllOppnAllMatchesRept(eng_matches,"West Indies",rank=1,dispRows=50)
teamBatsmenVsBowlersAllOppnAllMatchesPlot(d)
![]()
16 Team bowling T20 scorecard against all opposition
The functions lists the top T20 bowlers of each country in matches. This function returns a dataframe when ‘matches’ is the matches of the country and ‘theTeam’ is the same country as in the functions below
teamBowlingScorecardAllOppnAllMatchesMain(matches=ind_matches,theTeam="India")
## Source: local data frame [41 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 R Ashwin 18 0 900 41
## 2 IK Pathan 16 0 618 29
## 3 Harbhajan Singh 18 0 622 27
## 4 Yuvraj Singh 13 0 418 24
## 5 RA Jadeja 17 0 635 23
## 6 A Nehra 11 0 373 22
## 7 RP Singh 8 0 225 19
## 8 Z Khan 16 0 448 18
## 9 AB Dinda 11 0 245 17
## 10 B Kumar 9 0 294 14
## .. ... ... ... ... ...
teamBowlingScorecardAllOppnAllMatchesMain(matches=aus_matches,theTeam="Australia")
## Source: local data frame [56 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 SR Watson 21 0 1062 49
## 2 MG Johnson 19 0 797 42
## 3 B Lee 13 0 714 30
## 4 SW Tait 15 0 589 30
## 5 DP Nannes 14 0 403 29
## 6 MA Starc 18 0 508 28
## 7 PJ Cummins 19 0 395 22
## 8 NW Bracken 12 0 438 21
## 9 DJ Hussey 13 1 392 21
## 10 SPD Smith 10 0 377 18
## .. ... ... ... ... ...
teamBowlingScorecardAllOppnAllMatchesMain(eng_matches,"England")
## Source: local data frame [47 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 SCJ Broad 21 0 1491 68
## 2 GP Swann 16 0 859 53
## 3 JW Dernbach 17 0 1020 45
## 4 ST Finn 16 0 583 30
## 5 TT Bresnan 11 0 887 27
## 6 RJ Sidebottom 13 0 437 26
## 7 JM Anderson 16 0 552 20
## 8 LJ Wright 11 0 465 18
## 9 RS Bopara 12 0 387 17
## 10 PD Collingwood 10 0 329 16
## .. ... ... ... ... ...
teamBowlingScorecardAllOppnAllMatchesMain(pak_matches,"Pakistan")
## Source: local data frame [37 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 Shahid Afridi 16 0 2095 96
## 2 Saeed Ajmal 17 0 1516 94
## 3 Umar Gul 20 0 1400 91
## 4 Sohail Tanvir 18 0 1212 53
## 5 Mohammad Hafeez 19 0 1093 47
## 6 Mohammad Amir 11 0 557 27
## 7 Abdul Razzaq 13 0 367 22
## 8 Shoaib Malik 12 0 435 19
## 9 Shoaib Akhtar 10 0 421 19
## 10 Wahab Riaz 14 1 392 19
## .. ... ... ... ... ...
teamBowlingScorecardAllOppnAllMatchesMain(sa_matches,"South Africa")
## Source: local data frame [40 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 DW Steyn 17 0 879 59
## 2 M Morkel 18 0 1022 52
## 3 WD Parnell 21 0 891 41
## 4 J Botha 18 0 823 40
## 5 JA Morkel 19 0 835 30
## 6 Imran Tahir 13 0 426 27
## 7 RJ Peterson 18 1 451 26
## 8 D Wiese 16 0 267 22
## 9 LL Tsotsobe 14 0 541 20
## 10 R McLaren 16 0 332 19
## .. ... ... ... ... ...
teamBowlingScorecardAllOppnAllMatchesMain(nz_matches,"New Zealand")
## Source: local data frame [48 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 NL McCullum 18 0 1240 59
## 2 TG Southee 20 0 1182 52
## 3 KD Mills 16 0 1190 49
## 4 DL Vettori 12 0 748 39
## 5 IG Butler 15 0 481 27
## 6 MJ McClenaghan 19 0 642 25
## 7 SE Bond 12 0 518 25
## 8 JEC Franklin 16 0 417 25
## 9 JDP Oram 17 0 793 21
## 10 SB Styris 11 0 349 20
## .. ... ... ... ... ...
teamBowlingScorecardAllOppnAllMatchesMain(sl_matches,"Sri Lanka")
## Source: local data frame [42 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 SL Malinga 19 0 1522 86
## 2 BAW Mendis 17 0 911 61
## 3 KMDN Kulasekara 15 0 1052 52
## 4 AD Mathews 17 0 814 35
## 5 NLTC Perera 17 0 769 35
## 6 SMSM Senanayake 16 0 442 26
## 7 ST Jayasuriya 13 0 415 20
## 8 CRD Fernando 16 0 377 16
## 9 HMRKB Herath 12 2 174 15
## 10 M Muralitharan 13 0 297 14
## .. ... ... ... ... ...
teamBowlingScorecardAllOppnAllMatchesMain(wi_matches,"West Indies")
## Source: local data frame [37 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 DJG Sammy 20 0 1037 49
## 2 DJ Bravo 18 0 1127 46
## 3 SP Narine 15 0 692 40
## 4 S Badree 11 0 464 34
## 5 R Rampaul 16 0 705 29
## 6 JE Taylor 14 0 529 28
## 7 MN Samuels 6 0 561 24
## 8 KA Pollard 16 0 598 23
## 9 FH Edwards 14 0 497 19
## 10 K Santokie 9 0 278 19
## .. ... ... ... ... ...
17 Team bowling T20 scorecard against all opposition (continued)
The function lists the top bowlers of a country (‘matches’) against the opposition country
teamBowlingScorecardAllOppnAllMatches(ind_matches,'Australia')
## Source: local data frame [26 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 R Ashwin 13 1 232 10
## 2 RA Jadeja 7 0 219 9
## 3 JJ Bumrah 6 0 103 6
## 4 R Vinay Kumar 1 0 79 6
## 5 Yuvraj Singh 3 0 72 5
## 6 R Sharma 1 0 56 5
## 7 A Nehra 5 0 127 4
## 8 IK Pathan 8 0 115 4
## 9 B Kumar 4 0 42 4
## 10 Harbhajan Singh 8 0 83 3
## .. ... ... ... ... ...
teamBowlingScorecardAllOppnAllMatches(aus_matches,'India')
## Source: local data frame [36 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 SR Watson 13 0 201 11
## 2 MG Johnson 5 0 54 5
## 3 B Lee 6 0 133 4
## 4 SW Tait 5 0 112 3
## 5 NW Bracken 6 0 68 3
## 6 DP Nannes 1 0 25 3
## 7 DJ Hussey 4 0 24 3
## 8 PJ Cummins 4 0 16 3
## 9 CJ McKay 1 0 75 2
## 10 GB Hogg 5 0 69 2
## .. ... ... ... ... ...
teamBowlingScorecardAllOppnAllMatches(nz_matches,'England')
## Source: local data frame [26 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 MJ McClenaghan 9 0 189 8
## 2 KD Mills 6 0 199 7
## 3 NL McCullum 15 0 281 5
## 4 TG Southee 3 0 183 5
## 5 CS Martin 5 0 116 5
## 6 DL Vettori 11 0 91 5
## 7 JEC Franklin 7 0 53 5
## 8 SE Bond 8 0 49 5
## 9 IG Butler 11 0 95 4
## 10 SB Styris 8 0 80 3
## .. ... ... ... ... ...
teamBowlingScorecardAllOppnAllMatches(sl_matches,"West Indies")
## Source: local data frame [16 x 5]
##
## bowler overs maidens runs wickets
## (fctr) (int) (int) (dbl) (dbl)
## 1 BAW Mendis 10 0 82 13
## 2 SL Malinga 12 0 217 12
## 3 AD Mathews 9 0 87 6
## 4 TAM Siriwardana 5 0 58 5
## 5 SMSM Senanayake 7 0 90 4
## 6 M Muralitharan 9 0 76 4
## 7 KMDN Kulasekara 11 0 158 3
## 8 PVD Chameera 4 0 66 2
## 9 I Udana 7 0 56 1
## 10 DSNFG Jayasuriya 2 0 38 1
## 11 BMAJ Mendis 1 0 32 1
## 12 A Dananjaya 1 0 16 1
## 13 S Prasanna 2 0 15 1
## 14 HMRKB Herath 5 0 43 0
## 15 ST Jayasuriya 3 0 34 0
## 16 NLTC Perera 2 0 13 0
18. Team Bowlers versus Batsmen (in T20 against all oppositions)
The functions below give the peformance of bowlers versus batsman. They give the best bowlers and the total runs conceded and against whom were the runs conceded
teamBowlersVsBatsmenAllOppnAllMatchesMain(ind_matches,theTeam="India",rank=0)
## Source: local data frame [10 x 2]
##
## bowler runs
## (fctr) (dbl)
## 1 R Ashwin 868
## 2 RA Jadeja 619
## 3 IK Pathan 598
## 4 Harbhajan Singh 591
## 5 Z Khan 424
## 6 Yuvraj Singh 415
## 7 YK Pathan 406
## 8 A Nehra 368
## 9 I Sharma 349
## 10 B Kumar 275
(rank=1)
## [1] 1
m <-teamBowlersVsBatsmenAllOppnAllMatchesMain(ind_matches,theTeam="India",rank=1)
m
## Source: local data frame [95 x 3]
## Groups: bowler [1]
##
## bowler batsman runsConceded
## (fctr) (fctr) (dbl)
## 1 R Ashwin AD Hales 43
## 2 R Ashwin AJ Finch 42
## 3 R Ashwin SR Watson 41
## 4 R Ashwin DA Warner 37
## 5 R Ashwin MS Wade 37
## 6 R Ashwin BB McCullum 26
## 7 R Ashwin JP Duminy 26
## 8 R Ashwin GJ Maxwell 24
## 9 R Ashwin EJG Morgan 24
## 10 R Ashwin CA Ingram 23
## .. ... ... ...
m <-teamBowlersVsBatsmenAllOppnAllMatchesMain(ind_matches,theTeam="India",rank=2)
m
## Source: local data frame [66 x 3]
## Groups: bowler [1]
##
## bowler batsman runsConceded
## (fctr) (fctr) (dbl)
## 1 RA Jadeja SR Watson 59
## 2 RA Jadeja AJ Finch 34
## 3 RA Jadeja MS Wade 32
## 4 RA Jadeja CK Kapugedera 24
## 5 RA Jadeja LMP Simmons 23
## 6 RA Jadeja AD Hales 22
## 7 RA Jadeja DA Warner 20
## 8 RA Jadeja JH Kallis 19
## 9 RA Jadeja EJG Morgan 17
## 10 RA Jadeja LD Chandimal 17
## .. ... ... ...
18. Team Bowlers versus Batsmen (in T20 matchesagainst all oppositions continued)
teamBowlersVsBatsmenAllOppnAllMatchesMain(sa_matches,theTeam="South Africa",rank=0)
## Source: local data frame [10 x 2]
##
## bowler runs
## (fctr) (dbl)
## 1 M Morkel 967
## 2 WD Parnell 858
## 3 DW Steyn 833
## 4 JA Morkel 807
## 5 J Botha 802
## 6 LL Tsotsobe 523
## 7 RJ Peterson 443
## 8 Imran Tahir 410
## 9 JP Duminy 406
## 10 KJ Abbott 353
teamBowlersVsBatsmenAllOppnAllMatchesMain(pak_matches,theTeam="Pakistan",rank=0)
## Source: local data frame [10 x 2]
##
## bowler runs
## (fctr) (dbl)
## 1 Shahid Afridi 2054
## 2 Saeed Ajmal 1475
## 3 Umar Gul 1330
## 4 Sohail Tanvir 1147
## 5 Mohammad Hafeez 1060
## 6 Mohammad Amir 546
## 7 Shoaib Malik 407
## 8 Shoaib Akhtar 402
## 9 Wahab Riaz 369
## 10 Abdul Razzaq 364
teamBowlersVsBatsmenAllOppnAllMatchesMain(sl_matches,theTeam="Sri Lanka",rank=1)
## Source: local data frame [168 x 3]
## Groups: bowler [1]
##
## bowler batsman runsConceded
## (fctr) (fctr) (dbl)
## 1 SL Malinga Shahid Afridi 66
## 2 SL Malinga MN Samuels 55
## 3 SL Malinga BB McCullum 38
## 4 SL Malinga MJ Guptill 37
## 5 SL Malinga G Gambhir 35
## 6 SL Malinga NL McCullum 35
## 7 SL Malinga JDP Oram 31
## 8 SL Malinga Shoaib Malik 31
## 9 SL Malinga MEK Hussey 30
## 10 SL Malinga ADS Fletcher 30
## .. ... ... ...
m <-teamBowlersVsBatsmenAllOppnAllMatchesMain(ind_matches,theTeam="India",rank=2)
m
## Source: local data frame [66 x 3]
## Groups: bowler [1]
##
## bowler batsman runsConceded
## (fctr) (fctr) (dbl)
## 1 RA Jadeja SR Watson 59
## 2 RA Jadeja AJ Finch 34
## 3 RA Jadeja MS Wade 32
## 4 RA Jadeja CK Kapugedera 24
## 5 RA Jadeja LMP Simmons 23
## 6 RA Jadeja AD Hales 22
## 7 RA Jadeja DA Warner 20
## 8 RA Jadeja JH Kallis 19
## 9 RA Jadeja EJG Morgan 17
## 10 RA Jadeja LD Chandimal 17
## .. ... ... ...
19. Team bowlers versus batsmen report (in T20 matches against all oppositions)
teamBowlersVsBatsmenAllOppnAllMatchesRept(matches=ind_matches,theTeam="India",rank=0)
## Source: local data frame [10 x 2]
##
## bowler runs
## (fctr) (dbl)
## 1 SR Watson 190
## 2 Shahid Afridi 180
## 3 Umar Gul 171
## 4 SCJ Broad 151
## 5 JW Dernbach 149
## 6 SL Malinga 144
## 7 TT Bresnan 135
## 8 JP Faulkner 127
## 9 B Lee 123
## 10 JA Morkel 121
a <- teamBowlersVsBatsmenAllOppnAllMatchesRept(ind_matches,theTeam="India",rank=1)
a
## Source: local data frame [12 x 3]
## Groups: bowler [1]
##
## bowler batsman runsConceded
## (fctr) (fctr) (dbl)
## 1 SR Watson RG Sharma 41
## 2 SR Watson V Kohli 39
## 3 SR Watson SK Raina 26
## 4 SR Watson Yuvraj Singh 23
## 5 SR Watson MS Dhoni 21
## 6 SR Watson IK Pathan 14
## 7 SR Watson S Dhawan 10
## 8 SR Watson Harbhajan Singh 7
## 9 SR Watson RA Jadeja 4
## 10 SR Watson R Ashwin 4
## 11 SR Watson AM Rahane 1
## 12 SR Watson B Kumar 0
20. Team bowlers versus batsmen report (in T20s against all oppositions continued)
teamBowlersVsBatsmenAllOppnAllMatchesRept(matches=ind_matches,theTeam="Sri Lanka",rank=0)
## Source: local data frame [10 x 2]
##
## bowler runs
## (fctr) (dbl)
## 1 A Nehra 140
## 2 YK Pathan 100
## 3 RA Jadeja 80
## 4 R Ashwin 74
## 5 I Sharma 60
## 6 SK Raina 58
## 7 IK Pathan 56
## 8 AB Dinda 53
## 9 Harbhajan Singh 35
## 10 JJ Bumrah 35
teamBowlersVsBatsmenAllOppnAllMatchesRept(ind_matches,"England",rank=0)
## Source: local data frame [10 x 2]
##
## bowler runs
## (fctr) (dbl)
## 1 R Ashwin 160
## 2 RA Jadeja 86
## 3 AB Dinda 86
## 4 P Awana 71
## 5 PP Chawla 68
## 6 Harbhajan Singh 61
## 7 Yuvraj Singh 58
## 8 Joginder Sharma 57
## 9 R Vinay Kumar 53
## 10 IK Pathan 52
21. Team T20 bowlers versus batsmen report (all oppositions coninued-1)
teamBowlersVsBatsmenAllOppnAllMatchesRept(nz_matches,theTeam="New Zealand",rank=0)
## Source: local data frame [10 x 2]
##
## bowler runs
## (fctr) (dbl)
## 1 Shahid Afridi 333
## 2 M Morkel 283
## 3 SCJ Broad 279
## 4 SL Malinga 260
## 5 Umar Gul 240
## 6 KMDN Kulasekara 199
## 7 Mohammad Amir 192
## 8 BAW Mendis 190
## 9 Saeed Ajmal 170
## 10 P Utseya 159
teamBowlersVsBatsmenAllOppnAllMatchesRept(aus_matches,"Australia",rank=0)
## Source: local data frame [10 x 2]
##
## bowler runs
## (fctr) (dbl)
## 1 Saeed Ajmal 265
## 2 WD Parnell 254
## 3 Shahid Afridi 249
## 4 SCJ Broad 239
## 5 R Ashwin 222
## 6 Umar Gul 222
## 7 RA Jadeja 218
## 8 J Botha 210
## 9 Mohammad Hafeez 207
## 10 JW Dernbach 188
teamBowlersVsBatsmenAllOppnAllMatchesRept(sl_matches,"Sri Lanka",rank=0)
## Source: local data frame [10 x 2]
##
## bowler runs
## (fctr) (dbl)
## 1 Shahid Afridi 291
## 2 Sohail Tanvir 273
## 3 Saeed Ajmal 223
## 4 KD Mills 204
## 5 Umar Gul 179
## 6 DJ Bravo 173
## 7 Mohammad Hafeez 170
## 8 DL Vettori 160
## 9 JDP Oram 159
## 10 KA Pollard 157
22. Team bowlers versus batsmen report (in T20s against all oppositions) plot
This function can only be used for rank > 0 (rank=1,2,3..)
df <- teamBowlersVsBatsmenAllOppnAllMatchesRept(ind_matches,theTeam="India",rank=1)
teamBowlersVsBatsmenAllOppnAllMatchesPlot(df,"India","India")
![]()
df <- teamBowlersVsBatsmenAllOppnAllMatchesRept(ind_matches,theTeam="England",rank=1)
teamBowlersVsBatsmenAllOppnAllMatchesPlot(df,"India","England")
![]()
df <- teamBowlersVsBatsmenAllOppnAllMatchesRept(ind_matches,theTeam="West Indies",rank=1)
teamBowlersVsBatsmenAllOppnAllMatchesPlot(df,"India","West Indies")
![]()
27. Team Bowler Wicket Runs in Twenty20 matches against all oppositions(continued)
teamBowlingWicketRunsAllOppnAllMatches(pak_matches,t1="Pakistan",t2="All",plot=TRUE)
![]()
teamBowlingWicketRunsAllOppnAllMatches(wi_matches,t1="West Indies",t2="All",plot=TRUE)
![]()
teamBowlingWicketRunsAllOppnAllMatches(sl_matches,t1="Sri Lanka",t2="All",plot=TRUE)
![]()
teamBowlingWicketRunsAllOppnAllMatches(nz_matches,t1="New Zealand",t2="All",plot=TRUE)
![]()
Giga thoughts ... 