task-4.R

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

# Load IPL deliveries and matches datasets
deliveries <- read.csv("deliveries.csv")
matches <- read.csv("matches.csv")

# Calculate dot balls for each toss winner
dot_balls_by_toss_winner <- deliveries %>%
  group_by(match_id, batting_team) %>%
  summarise(dot_balls = sum(is.na(batsman_runs) | batsman_runs == 0)) %>%
  inner_join(matches, by = c("match_id" = "id")) %>%
  group_by(toss_winner) %>%
  summarise(total_dot_balls = sum(dot_balls), match_id = first(match_id)) # Keep the first match_id

## `summarise()` regrouping output by 'match_id' (override with `.groups` argument)

## `summarise()` ungrouping output (override with `.groups` argument)

# Find the toss winner with maximum dot balls
max_dot_balls_winner <- dot_balls_by_toss_winner %>%
  filter(total_dot_balls == max(total_dot_balls))

# Find the match details
max_dot_balls_match <- matches %>%
  filter(id == max_dot_balls_winner$match_id)

# Print the results
cat("Toss-winning team with maximum dot balls:", max_dot_balls_winner$toss_winner, "\n")

## Toss-winning team with maximum dot balls: Mumbai Indians

cat("Match number:", max_dot_balls_match$id, "\n")

## Match number: 7

cat("Opponent team:", max_dot_balls_match$team2, "\n")

## Opponent team: Mumbai Indians