Import libraries and dataset.

library(tidyverse)
library(readr) # Read in datasets.
options(scipen = 9999)

ffhistory <- read_csv(file = "C:/Users/chris/Documents/Datasets/FFL/ff_scores.csv", 
                      show_col_types = FALSE)

Invert table by swapping team_1 and team_2, and inverting win column data.

ffhistory_inverse <- ffhistory
team_1 <- ffhistory$team_1
team_1_score <- ffhistory$team_1_score
team_2 <- ffhistory$team_2
team_2_score <- ffhistory$team_2_score

ffhistory_inverse$team_1 <- team_2
ffhistory_inverse$team_1_score <- team_2_score
ffhistory_inverse$team_2 <- team_1
ffhistory_inverse$team_2_score <- team_1_score
ffhistory_inverse$win <- ifelse(ffhistory_inverse$win == 0, 1, 0)

Join tables vertically. Save and export as CSV.

ffhistory_inverted <- rbind(ffhistory, ffhistory_inverse) %>%
    arrange(date)

head(ffhistory_inverted[,1:9])

A tibble: 6 × 9

year	week	team_1	team_1_score	team_2	team_2_score	win	reg	playoffs
<dbl>	<chr>	<chr>	<dbl>	<chr>	<dbl>	<dbl>	<dbl>	<dbl>
2014	01	CHRIS	119.68	CARLEN	126.34	0	1	0
2014	01	ANDREW	106.28	KYLE	145.94	0	1	0
2014	01	STEVE	103.46	DREW	101.92	1	1	0
2014	01	MATT	125.50	NATHAN	99.86	1	1	0
2014	01	CARLEN	126.34	CHRIS	119.68	1	1	0
2014	01	KYLE	145.94	ANDREW	106.28	1	1	0

write.csv(ffhistory_inverted,"C:\\Users\\chris\\Desktop\\ffscores_inverted.csv", row.names = FALSE)