Top T20 Cricket International Fielders

Author

Joe McCune

Getting the Data

library(tidyverse) 
library(scales)
library(cricketdata)

This is how I scraped the data, and then saved it. It can take repeated attempts and considerable time to finish this process.

crick_fielders <- fetch_cricinfo("t20", "men", "fielding", "career", country = NULL)
all_fielders <- saveRDS(crick_fielders, "all_fielders")

The saved data can be used to extract the data on the ten fielders who have the most dismissals in their international T20 careers.

t20_fielders <- readRDS("all_fielders") 
top_fielders <- t20_fielders |> dplyr::slice_max(order_by = Dismissals, n = 10) 
top_fielders$Player[top_fielders$Player == "DA Miller (SA/World)"] <- "DA Miller"
top_fielders$Country[top_fielders$Country == "BAN"] <- "Bangladesh"
top_fielders$Country[top_fielders$Country == "RWN"] <- "Rwanda"
top_fielders$Country[is.na(top_fielders$Country)] <- "South Africa"
# Country and player names have been corrected

Top Ten Fielders: Career Totals

Figure 1 shows the simple story of who has the most dismissals. The columns are color coded by the countries of the respective batters.

ggplot(top_fielders, aes(x = fct_reorder(Player, Dismissals), y = Dismissals)) +
  geom_col(aes(fill = Country)) +
  scale_x_discrete(labels = label_wrap(2)) +
  labs(title = "Top Ten T20 International Fielders", x = "Fielders", y = "Dismissals", caption = "Source: ESPNcricinfo")
Figure 1

Top Ten Fielders: Career Progress

Figure 2 shows dismissals in proportion to the total number of innings. This gives us an idea of progress each has made when compared to the length of their career.

ggplot(top_fielders, aes(x = Innings, y = Dismissals, label = Player)) +
  geom_point() + geom_text(hjust=0.25, vjust=-0.5) +
  xlim(60, 140) +
  # X axis has been extended to make it easier for prevent the player names from being "cut off"
  labs(title = "Top Fielders: Career Progress", x = "Innings", y = "Dismissals Taken", caption = "Source: ESPNcricinfo")
Figure 2

De Kock stands out as having the most dismissals despite having fielded for fewer innings than many others. Karim stands out for having accumulated many dismissals in a short time.

Cricket fans usually think of wicket keepers as a category in their own right, even though technically speaking they are fielders. AFAICS the cricketdata package has no available data for wicket keepers.

It is possible to deduce which players here are wicket keepers because certain actions such as stumping and caught behind are unique to wicket keepers. But it would still be awkward to rank them without being sure how many innings they were actually playing as wicket keepers.

It could be interesting to use another data set to visualize data for the top ten wicket keepers.