It’s a wrap! yorkr wraps up BBL, NTB, PSL and WBB!!!
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“Do not take life too seriously. You will never get out of it alive.” – Elbert Hubbard
“How many people here have telekenetic powers? Raise my hand.” – Emo Philips
Have you ever noticed that anybody driving slower than you is an idiot, and anyone going faster than you is a maniac?” – George Carlin
It’s a wrap!!! In my previous posts,Revitalizing yorkr, I showed how you can use yorkr functions for Intl. ODI, Intl. T20 and IPL. My next post yorkr rocks women’s ODI and women’s Intl T20 yorkr handled women’s ODI and Intl. T20. In this post, yorkr wraps the remaining T20 formats namely
- Big Bash League (BBL)
- Natwest Super T20 (NTB)
- Pakistan Super League (PSL)
- Women’s Big Bash League (WBB)
The data for all the above T20 formats are taken from Cricsheet.
-All the data has been converted and is available in Github at yorkrData2020 organized as below. You can use any of the 90+ yorkr functions on the converted data.
-This post has been published at RPubs at yorkrWrapUpT20formats
-You can download a PDF version of this file at yorkrWrapsUpT20Formats
- For ODI Matches men’s and women’ use
- ODI-Part1, 2. ODI-Part2,3. ODI-Part3, 4.ODI-Part 4
- For any of the T20s formats you can use the following posts
or you can use these templates Intl. T20, or similar to IPL T20
I am going to randomly pick 2 yorkr functions for each of the T20 formats BBL, NTB, PSL and WBB to demonstrate yorkr below, however you can use any of the 90+ yorkr functions
install.packages("../../../yorkrgit/yorkr_0.0.9.tar.gz",repos = NULL, type="source")
library(yorkr)
library(dplyr)
Note: In the following T20 formats I have randomly picked 2 of the 90+ yorkr functions
A. Big Bash League (BBL)
A1.Batting Scorecard
load("../../../yorkrData2020/bbl/bblMatches/Adelaide Strikers-Brisbane Heat-2017-12-31.RData")
as_bh <- overs
teamBattingScorecardMatch(as_bh,'Adelaide Strikers')
## Total= 139
## # A tibble: 9 x 5
## batsman ballsPlayed fours sixes runs
## <chr> <int> <dbl> <dbl> <dbl>
## 1 AT Carey 6 0 0 2
## 2 CA Ingram 21 2 0 23
## 3 J Weatherald 14 2 1 20
## 4 JS Lehmann 17 3 0 22
## 5 JW Wells 13 1 0 12
## 6 MG Neser 25 3 2 40
## 7 PM Siddle 1 0 0 1
## 8 Rashid Khan 2 0 1 6
## 9 TM Head 17 0 0 13
A2.Batting Partnership
load("../../../yorkrData2020/bbl/bblMatches2Teams/Melbourne Renegades-Sydney Sixers-allMatches.RData")
mr_ss_matches <- matches
m <-teamBatsmenPartnershiOppnAllMatches(mr_ss_matches,'Sydney Sixers',report="summary")
m
## # A tibble: 28 x 2
## batsman totalRuns
## <chr> <dbl>
## 1 MC Henriques 277
## 2 JR Philippe 186
## 3 NJ Maddinson 183
## 4 MJ Lumb 165
## 5 DP Hughes 158
## 6 JC Silk 141
## 7 SPD Smith 116
## 8 JM Vince 97
## 9 TK Curran 68
## 10 J Botha 33
## # … with 18 more rows
B. Natwest Super League
B1.Team Match Partnership
load("../../../yorkrData2020/ntb/ntbMatches/Derbyshire-Nottinghamshire-2019-07-26.RData")
db_nt <-overs
teamBatsmenPartnershipMatch(db_nt,"Derbyshire","Nottinghamshire")
B2.Batsmen vs Bowlers
load("../../../yorkrData2020/ntb/ntbMatches2Teams/Birmingham Bears-Leicestershire-allMatches.RData")
bb_le_matches <- matches
teamBatsmenVsBowlersOppnAllMatches(bb_le_matches,"Birmingham Bears","Leicestershire",top=3)
C. Pakistan Super League (PSL)
C1.Individual performance of Babar Azam
library(grid) library(gridExtra) babar <- getBatsmanDetails(team="Karachi Kings",name="Babar Azam",dir="../../../yorkrData2020/psl/pslBattingBowlingDetails/") ## [1] "../../../yorkrData2020/psl/pslBattingBowlingDetails//Karachi Kings-BattingDetails.RData" print(dim(babar)) ## [1] 40 15 p1 <-batsmanRunsVsStrikeRate(babar,"Babar Azam") p2 <-batsmanMovingAverage(babar,"Babar Azam") p3 <- batsmanCumulativeAverageRuns(babar,"Babar Azam") grid.arrange(p1,p2,p3, ncol=2)
C2.Bowling performance against all oppositions
load("../../../yorkrData2020/psl/pslMatches2Teams/Lahore Qalandars-Multan Sultans-allMatches.RData")
lq_ms_matches <- matches
teamBowlingPerfOppnAllMatches(lq_ms_matches,"Lahore Qalanders","Multan Sultans")
## # A tibble: 40 x 5
## bowler overs maidens runs wickets
## <chr> <int> <int> <dbl> <dbl>
## 1 Shaheen Shah Afridi 11 1 134 11
## 2 Junaid Khan 5 0 154 8
## 3 Imran Tahir 5 0 74 6
## 4 Mohammad Ilyas 5 0 93 4
## 5 Haris Rauf 7 0 154 3
## 6 D Wiese 7 0 92 3
## 7 Mohammad Irfan 5 0 91 3
## 8 S Lamichhane 5 0 74 3
## 9 SP Narine 8 0 48 3
## 10 MM Ali 3 0 30 3
## # … with 30 more rows
D. Women Big Bash League
D1.Bowling scorecard
load("../../../yorkrData2020/wbb/wbbMatches/Hobart Hurricanes-Brisbane Heat-2018-12-30.RData")
hh_bh_match <- overs
teamBowlingScorecardMatch(hh_bh_match,'Brisbane Heat')
## # A tibble: 6 x 5
## bowler overs maidens runs wickets
## <chr> <int> <int> <dbl> <dbl>
## 1 DM Kimmince 3 0 31 2
## 2 GM Harris 4 0 23 3
## 3 H Birkett 1 0 7 0
## 4 JL Barsby 3 0 21 0
## 5 JL Jonassen 4 0 33 0
## 6 SJ Johnson 4 0 17 0
D2.Team batsmen partnerships
load("../../../yorkrData2020/wbb/wbbAllMatchesAllTeams/allMatchesAllOpposition-Perth Scorchers.RData")
ps_matches <- matches
teamBatsmenPartnershipAllOppnAllMatchesPlot(ps_matches,"Perth Scorchers",main="Perth Scorchers")
As mentioned above, I have randomly picked 2 yorkr functions for each of the T20 formats. You can use any of the 90+ functions for analysis of matches, teams, batsmen and bowlers.
1a. Ranking Big Bash League (BBL) batsman
dir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/bbl/bblMatches" odir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/bbl/bblBattingBowlingDetails" rankBBLBatsmen(dir=dir,odir=odir,minMatches=30) ## # A tibble: 62 x 4 ## batsman matches meanRuns meanSR ## <chr> <int> <dbl> <dbl> ## 1 DJM Short 44 41.6 126. ## 2 SE Marsh 48 39.1 120. ## 3 AJ Finch 60 36.0 130. ## 4 AT Carey 36 35.9 129. ## 5 KP Pietersen 31 33.5 118. ## 6 UT Khawaja 40 31.5 112. ## 7 BJ Hodge 38 31.5 127. ## 8 CA Lynn 72 31.3 128. ## 9 MP Stoinis 53 30.7 112. ## 10 TM Head 45 30 131. ## # … with 52 more rows
1b. Ranking Big Bash League (BBL) bowlers
dir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/bbl/bblMatches" odir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/bbl/bblBattingBowlingDetails" rankBBLBowlers(dir=dir,odir=odir,minMatches=25) ## # A tibble: 53 x 4 ## bowler matches totalWickets meanER ## <chr> <int> <dbl> <dbl> ## 1 SA Abbott 60 90 8.42 ## 2 AJ Tye 45 69 7.32 ## 3 B Laughlin 48 66 7.96 ## 4 BCJ Cutting 71 63 8.87 ## 5 BJ Dwarshuis 54 62 7.87 ## 6 MG Neser 54 57 8.36 ## 7 Rashid Khan 40 55 6.32 ## 8 JP Behrendorff 41 53 6.55 ## 9 SNJ O'Keefe 53 52 6.76 ## 10 A Zampa 42 51 7.34 ## # … with 43 more rows
2a. Ranking Natwest T20 League (NTB) batsman
dir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/ntb/ntbMatches" odir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/ntb/ntbBattingBowlingDetails" rankNTBBatsmen(dir=dir,odir=odir,minMatches=20) ## # A tibble: 42 x 4 ## batsman matches meanRuns meanSR ## <chr> <int> <dbl> <dbl> ## 1 SR Hain 24 34.6 107. ## 2 M Klinger 26 34.1 118. ## 3 MH Wessels 26 33.9 122. ## 4 DJ Bell-Drummond 21 33.1 112. ## 5 DJ Malan 26 33 129. ## 6 T Kohler-Cadmore 23 33.0 118. ## 7 A Lyth 22 31.4 150. ## 8 JJ Cobb 26 30.7 110. ## 9 CA Ingram 25 30.5 153. ## 10 IA Cockbain 26 29.8 121. ## # … with 32 more rows
2b. Ranking Natwest T20 League (NTB) bowlers
dir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/ntb/ntbMatches" odir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/ntb/ntbBattingBowlingDetails" rankNTBBowlers(dir=dir,odir=odir,minMatches=20) ## # A tibble: 23 x 4 ## bowler matches totalWickets meanER ## <chr> <int> <dbl> <dbl> ## 1 HF Gurney 23 45 8.63 ## 2 AJ Tye 26 40 7.81 ## 3 TS Roland-Jones 26 37 8.10 ## 4 BAC Howell 20 35 6.89 ## 5 TT Bresnan 21 31 8.82 ## 6 MJJ Critchley 25 31 7.33 ## 7 LA Dawson 24 30 6.80 ## 8 TK Curran 23 28 8.19 ## 9 NA Sowter 25 28 8.09 ## 10 MTC Waller 25 27 7.59 ## # … with 13 more rows
3a. Ranking Pakistan Super League (PSL) batsman
dir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/psl/pslMatches" odir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/psl/pslBattingBowlingDetails" rankPSLBatsmen(dir=dir,odir=odir,minMatches=15) ## # A tibble: 47 x 4 ## batsman matches meanRuns meanSR ## <chr> <int> <dbl> <dbl> ## 1 Babar Azam 40 33.7 102. ## 2 L Ronchi 31 32.9 143. ## 3 DR Smith 24 30.8 111. ## 4 JJ Roy 15 30.6 123. ## 5 Kamran Akmal 46 30.1 112. ## 6 SR Watson 40 29.2 126. ## 7 Shoaib Malik 35 28.1 113. ## 8 Fakhar Zaman 38 27.6 119. ## 9 Imam-ul-Haq 15 27.4 115. ## 10 RR Rossouw 36 27.0 130. ## # … with 37 more rows
3b. Ranking Pakistan Super League (PSL) bowlers
dir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/psl/pslMatches" odir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/psl/pslBattingBowlingDetails" rankPSLBowlers(dir=dir,odir=odir,minMatches=15) ## # A tibble: 25 x 4 ## bowler matches totalWickets meanER ## <chr> <int> <dbl> <dbl> ## 1 Wahab Riaz 44 70 6.94 ## 2 Hasan Ali 41 61 7.43 ## 3 Faheem Ashraf 30 50 7.84 ## 4 Mohammad Amir 38 48 7.16 ## 5 Usman Shinwari 26 43 8.64 ## 6 Mohammad Sami 29 40 7.60 ## 7 Shadab Khan 40 38 7.57 ## 8 Shaheen Shah Afridi 24 34 7.88 ## 9 Rumman Raees 24 33 7.77 ## 10 Mohammad Hasnain 16 28 8.65 ## # … with 15 more rows
4a. Ranking Women’s Big Bash League (WBB) batsman
dir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/wbb/wbbMatches" odir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/wbb/wbbBattingBowlingDetails" rankWBBBatsmen(dir=dir,odir=odir,minMatches=15) ## # A tibble: 36 x 4 ## batsman matches meanRuns meanSR ## <chr> <int> <dbl> <dbl> ## 1 BL Mooney 27 46.7 129. ## 2 SFM Devine 22 43.5 111. ## 3 EA Perry 16 41.1 97.1 ## 4 MM Lanning 19 38 98.2 ## 5 JE Cameron 22 32.9 127. ## 6 DN Wyatt 24 32 112. ## 7 AE Jones 17 28.9 107. ## 8 AJ Healy 19 28.4 122. ## 9 M du Preez 19 27 101. ## 10 L Lee 18 26.9 98.9 ## # … with 26 more rows
4b. Ranking Women’s Big Bash League (WBB) bowlers
dir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/wbb/wbbMatches" odir="/Users/tvganesh/backup/software/cricket-package/yorkr-cricsheet/yorkrData2020/wbb/wbbBattingBowlingDetails" rankWBBBowlers(dir=dir,odir=odir,minMatches=15) ## # A tibble: 31 x 4 ## bowler matches totalWickets meanER ## <chr> <int> <dbl> <dbl> ## 1 M Strano 23 37 7.25 ## 2 DM Kimmince 24 36 7.46 ## 3 SJ Coyte 22 29 7.59 ## 4 JL Jonassen 24 28 6.81 ## 5 SJ Johnson 24 27 6.61 ## 6 ML Schutt 22 26 6.03 ## 7 SFM Devine 22 24 7.58 ## 8 M Brown 23 23 7.33 ## 9 M Kapp 19 23 5.05 ## 10 H Graham 19 22 7.68 ## # … with 21 more rows
Conclusion
yorkr can handle ODI and T20 matches in the format as represented in Cricsheet. In my posts, I have shown how yorkr can be used for Intl. ODI and Intl. T20 for both men and women. yorkr can also handle all T20 formats like IPL T20, BBL, Natwest T20, PSL and women’s BBL. Go ahead take yorkr for a ride and check out your favorite teams and players.
Hope you have fun!!!
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