Here is the code with explanations and output: # Load necessary libraries library(dplyr) # Create a sample dataset nextouts <- data.frame( runner = c("C.Hottle", "D.Wottle", "J.J Watt"), race_number = 1:6, finish = c(1, 3, 2, 1, 3, 2), next_finish = c(2, 1, 3, 3, 1, 3), next_date = c("2017-03-04", "2017-03-29", "2017-04-28", "2017-05-24", "2017-06-15", NA) ) # Define a function to calculate the next-out winner next_out_winner <- function(x) { x$is_next_out_win <- ifelse(x$finish == x$next_finish, 1, 0) return(x) } # Apply the function to the dataset nextouts <- next_out_winner(nextouts) # Arrange the data by race number and find the next-out winner for each race nextoutsR <- nextouts %>% arrange(race_number) %>% group_by(race_number) %>% summarise(nextOutWinCount = sum(is_next_out_win)) # Print the results print(nextoutsR) Output:

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