How to create a nested function in R?

`HTDrawHomeFavPotValue <- function(HomeFavorite = "", date = NA, bet = 10) {
  df$NetDollarReturnOnWin <- (((df$`Avg. Draw Odds`)*bet)-bet)/2
  df$DImpPr <- percent((1/df$`Avg. Draw Odds`))
  df$ChosenBets <- ifelse(df$DImpPr >= 30, df$NetDollarReturnOnWin, 0)
  df$ChosenBetsPL <- ifelse(df$ChosenBets > 0 & df$HTDraw == 1, df$ChosenBets, -bet)
  rows <- grep(pattern = tolower(HomeFavorite), 
               x = tolower(df$HomeFavorite), fixed = TRUE)
  df[rows, c("HomeFavorite", "NetDollarReturnOnWin",
             "DImpPr", "AwayUnderdog", "HTDraw", "FTDraw", "ChosenBets", "ChosenBetsPL")]
  df <- df[df$ChosenBets > 0, ]
  df
}

HTDrawHomeFavPotValue("Wolves")

HTDrawHomeDogPotValue <- function(HomeUnderdog = "", date = NA, bet = 10) {
  df$NetDollarReturnOnWin <- (((df$`Avg. Draw Odds`)*bet)-bet)/2
  df$DImpPr <- percent((1/df$`Avg. Draw Odds`))
  df$ChosenBets <- ifelse(df$DImpPr >= 30, df$NetDollarReturnOnWin, 0)
  df$ChosenBetsPL <- ifelse(df$ChosenBets > 0 & df$HTDraw == 1, df$ChosenBets, -bet)
  rows <- grep(pattern = tolower(HomeUnderdog), 
               x = tolower(df$HomeUnderdog), fixed = TRUE)
  df <- df[rows, c("HomeUnderdog", "NetDollarReturnOnWin",
             "DImpPr", "AwayFavorite", "HTDraw", "FTDraw", "ChosenBets", "ChosenBetsPL")]
  df <- df[df$ChosenBets > 0, ]
  sum(df$ChosenBetsPL)
}

tmp <- HTDrawHomeDogPotValue("newcastle")

HTDrawAwayFavPotValue <- function(AwayFavorite = "", date = NA, bet = 10) {
  df$NetDollarReturnOnWin <- (((df$`Avg. Draw Odds`)*bet)-bet)/2
  df$DImpPr <- percent((1/df$`Avg. Draw Odds`))
  df$ChosenBets <- ifelse(df$DImpPr >= 30, df$NetDollarReturnOnWin, 0)
  df$ChosenBetsPL <- ifelse(df$ChosenBets > 0 & df$HTDraw == 1, df$ChosenBets, -bet)
  rows <- grep(pattern = tolower(AwayFavorite), 
               x = tolower(df$AwayFavorite), fixed = TRUE)
  df <- df[rows, c("AwayFavorite", "NetDollarReturnOnWin",
             "DImpPr", "HomeUnderdog", "HTDraw", "FTDraw", "ChosenBets", "ChosenBetsPL")]
  df <- df[df$ChosenBets > 0, ]
  df
}

HTDrawAwayFavPotValue("Wolves")

HTDrawAwayDogPotValue <- function(AwayUnderdog = "", date = NA, bet = 10) {
  df$NetDollarReturnOnWin <- (((df$`Avg. Draw Odds`)*bet)-bet)/2
  df$DImpPr <- percent((1/df$`Avg. Draw Odds`))
  df$ChosenBets <- ifelse(df$DImpPr >= 30, df$NetDollarReturnOnWin, 0)
  df$ChosenBetsPL <- ifelse(df$ChosenBets > 0 & df$HTDraw == 1, df$ChosenBets, -bet)
  rows <- grep(pattern = tolower(AwayUnderdog), 
               x = tolower(df$AwayUnderdog), fixed = TRUE)
  df[rows, c("AwayUnderdog", "NetDollarReturnOnWin",
             "DImpPr", "HomeFavorite", "HTDraw", "FTDraw", "ChosenBets", "ChosenBetsPL")]
}

HTDrawAwayDogPotValue("Arsenal")

`

Question tasked to answer: Were certain teams more susceptible to being tied at half and was it frequent enough to bet on and create value?

The goal I am trying to accomplish would be to have these 4 functions combined into one. The desired calculation I would like for it to compute would be to go through and evaluate all the teams in the league as HomeFav, HomeDog, AwayFav, and AwayDog and see from the parameters set, whether we made or lost money on the bets that were placed. I'm new to R and the specificities with what I'm looking for have given me trouble through internet research. Any assistance would be greatly appreciated.