International cricket data for men and women, Tests, ODIs and T20s
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DESCRIPTION
NAMESPACE
NEWS.md
README.Rmd
README.md
cricketdata.Rproj

README.md

cricinfo

Functions for Downloading Cricket Data from ESPNCricinfo

Data on all international cricket matches is provided by ESPNCricinfo. This package provides some scraper functions to download the data into tibbles ready for analysis.

Please respect the ESPNCricinfo terms of use.

Installation

You can install cricinfo from github with:

# install.packages("devtools")
devtools::install_github("ropenscilabs/cricinfo")

Bowling Data

# Fetch all Women's T20 data
wt20 <- fetch_cricinfo("T20", "Women", "Bowling")
wt20 %>% head %>% knitr::kable()
Player Country Start End Matches Innings Overs Maidens Runs Wickets Average Economy StrikeRate BestBowlingInnings FourWickets FiveWickets
A Mohammed West Indies 2008 2017 92 89 314.3 6 1675 106 15.80189 5.325914 17.80189 5/10 4 2
EA Perry Australia 2008 2016 82 78 265.5 4 1513 77 19.64935 5.691536 20.71429 4/12 2 0
D Hazell England 2009 2016 70 70 266.0 6 1384 73 18.95890 5.203008 21.86301 4/12 1 0
SF Daley West Indies 2009 2014 68 67 227.1 8 1113 72 15.45833 4.899486 18.93056 5/15 2 1
A Shrubsole England 2008 2016 47 47 159.3 5 870 68 12.79412 5.454546 14.07353 5/11 2 1
SR Taylor West Indies 2008 2017 80 60 206.1 4 1117 68 16.42647 5.417947 18.19118 3/10 0 0
wt20 %>% 
  filter(Wickets > 20) %>%
  ggplot(aes(y = StrikeRate, x = Country)) +
  geom_boxplot() +
  geom_point(alpha=0.3, col="blue") +
  ggtitle("Women T20: Strike Rates") +
  ylab("Balls per wicket")

Batting Data

# Fetch all Australian Men's ODI data by innings
menODI <- fetch_cricinfo("ODI", "Men", "Batting", type="innings", country="Australia")
menODI %>% head %>% knitr::kable()
Date Player Runs NotOut Minutes BallsFaced Fours Sixes StrikeRate Innings Participation Opposition Ground
2011-04-11 SR Watson 185 TRUE 113 96 15 15 192.7083 2 B Bangladesh Dhaka
2007-02-20 ML Hayden 181 TRUE 227 166 11 10 109.0361 1 B New Zealand Hamilton
2017-01-26 DA Warner 179 FALSE 186 128 19 5 139.8438 1 B Pakistan Adelaide
2015-03-04 DA Warner 178 FALSE 164 133 19 5 133.8346 1 B Afghanistan Perth
2001-02-09 ME Waugh 173 FALSE 199 148 16 3 116.8919 1 B West Indies Melbourne
2016-10-12 DA Warner 173 FALSE 218 136 24 0 127.2059 2 B South Africa Cape Town
menODI %>% 
  ggplot(aes(y = Runs, x = Date)) +
    geom_point(alpha=0.2, col='red') +
    geom_smooth() +
    ggtitle("Australia Men ODI: Runs per Innings")

Fielding Data

Indfielding <- fetch_cricinfo("Test", "Men", "Fielding", country="India")
Indfielding %>% head %>% knitr::kable()
Player Start End Matches Innings Dismissals Caught CaughtFielder CaughtBehind Stumped MaxDismissalsInnings
MS Dhoni 2005 2014 90 166 294 256 0 256 38 6
R Dravid 1996 2012 163 299 209 209 209 0 0 3
SMH Kirmani 1976 1986 88 151 198 160 0 160 38 6
VVS Laxman 1996 2012 134 248 135 135 135 0 0 4
KS More 1986 1993 49 90 130 110 0 110 20 5
SR Tendulkar 1989 2013 200 366 115 115 115 0 0 3
wktkeeper <- (Indfielding$CaughtBehind > 0) | (Indfielding$Stumped > 0)
ggplot(Indfielding, aes(x=Matches, y=Dismissals, col=wktkeeper)) +
  geom_point() +
  ggtitle("Indian Men Test Fielding")

Individual player data

MegLanning <- fetch_player(329336, "ODI")
MLave <- with(MegLanning, sum(Score, na.rm=TRUE) / (sum(is.na(Score)) - sum(NotOut)))
names(MLave) <- paste("Average =", round(MLave,2))
ggplot(MegLanning) + 
  geom_point(aes(x = Date, y = Score, col = NotOut)) +
  ggtitle("Meg Lanning ODI Scores") +
  geom_hline(aes(yintercept=MLave)) +
  scale_y_continuous(sec.axis = sec_axis(~ ., breaks=MLave))