cricketdata

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 cricketdata from github with:

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

Bowling Data

# Fetch all Women's T20 data
wt20 <- fetch_cricinfo("T20", "Women", "Bowling")
wt20 %>% head() %>% knitr::kable()

wt20 %>% 
  filter(
    Wickets > 20,
    !is.na(Country)
  ) %>%
  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()

menODI %>% 
  ggplot(aes(y = Runs, x = Date)) +
    geom_point(alpha=0.2, col='red') +
    geom_smooth() +
    ggtitle("Australia Men ODI: Runs per Innings")
#> `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
#> Warning: Removed 2496 rows containing non-finite values (stat_smooth).
#> Warning: Removed 2496 rows containing missing values (geom_point).

Fielding Data

Indfielding <- fetch_cricinfo("Test", "Men", "Fielding", country="India")
Indfielding %>% head() %>% knitr::kable()

Indfielding %>%
  mutate(wktkeeper = (CaughtBehind > 0) | (Stumped > 0)) %>%
  ggplot(aes(x=Matches, y=Dismissals, col=wktkeeper)) +
    geom_point() +
    ggtitle("Indian Men Test Fielding")

Individual player data

MegLanning <- fetch_player_data(329336, "ODI") %>%
  mutate(NotOut = (Dismissal=="not out"))
MLave <- summarise(MegLanning,
    Innings = sum(!is.na(Runs)),
    Average = sum(Runs, na.rm=TRUE) / (Innings - sum(NotOut))
  ) %>%
  pull(Average)
names(MLave) <- paste("Average =", round(MLave,2))

ggplot(MegLanning) + 
  geom_point(aes(x = Start_Date, y = Runs, col = NotOut)) +
  ggtitle("Meg Lanning ODI Scores") +
  geom_hline(aes(yintercept=MLave)) +
  scale_y_continuous(sec.axis = sec_axis(~ ., breaks=MLave))