calculate_player_stats_def() no longer errors with small subsets of…

… pbp (#415)

* `calculate_player_stats_def()` no longer errors with small subsets of pbp

* news bullet

* be consistent with counter types

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: nflfastR
 Title: Functions to Efficiently Access NFL Play by Play Data
-Version: 4.5.1.9002
+Version: 4.5.1.9003
 Authors@R: 
     c(person(given = "Sebastian",
              family = "Carl",

NEWS.md

@@ -2,6 +2,7 @@
 
 - internal function `get_pbp_nfl()` now uses `ifelse()` instead of `dplyr::if_else()` to handle some null-checking, fixes bug found in 2022_21_CIN_KC match. (v4.5.1.9001)
 - The function `calculate_player_stats()` now summarises target share and air yards share correctly when called with argument `weekly = FALSE` (#413)
+- The function `calculate_player_stats_def()` no longer errors when small subsets of pbp data are missing stats. (#415)
 
 # nflfastR 4.5.1
 

R/aggregate_game_stats_def.R

@@ -114,6 +114,10 @@ calculate_player_stats_def <- function(pbp, weekly = FALSE) {
       values_fill = 0L,
       values_fn = sum
     ) %>%
+    add_column_if_missing(
+      "solo_tackle", "tackle_with_assist", "tackle_for_loss", "assist_tackle",
+      "forced_fumble_player"
+    ) %>%
     dplyr::mutate(
       tackles = .data$solo_tackle + .data$tackle_with_assist
     ) %>%
@@ -196,8 +200,9 @@ calculate_player_stats_def <- function(pbp, weekly = FALSE) {
       names_from = .data$desc,
       values_from = c(.data$n, .data$sack_yards),
       values_fn = sum,
-      values_fill = 0
+      values_fill = 0L
     ) %>%
+    add_column_if_missing("n_sack", "n_qb_hit", "sack_yards_sack") %>%
     dplyr::select(
       "season",
       "week",
@@ -243,7 +248,10 @@ calculate_player_stats_def <- function(pbp, weekly = FALSE) {
       names_from = "desc",
       values_from = c("n","return_yards"),
       values_fn = sum,
-      values_fill = 0
+      values_fill = 0L
+    ) %>%
+    add_column_if_missing(
+      "n_interception", "n_pass_defense", "return_yards_interception"
     ) %>%
     dplyr::select(
       "season",
@@ -305,7 +313,7 @@ calculate_player_stats_def <- function(pbp, weekly = FALSE) {
       names_from = .data$desc,
       values_from = .data$n,
       values_fn = sum,
-      values_fill = 0
+      values_fill = 0L
     ) %>%
     # Renaming fails if the columns don't exist. So we row bind a dummy tibble
     # including the relevant columns. The row will be filtered after renaming
@@ -334,10 +342,12 @@ calculate_player_stats_def <- function(pbp, weekly = FALSE) {
         .data$defteam == .data$fumble_recovery_2_team
     ) %>%
     dplyr::mutate(
+      # use data.table fifelse because base ifelse changed data type to logical
+      # if there are 0 rows
       fumble_recovery_1_player_id =
-        ifelse(.data$defteam != .data$fumbled_1_team, .data$fumble_recovery_1_player_id, NA),
+        data.table::fifelse(.data$defteam != .data$fumbled_1_team, .data$fumble_recovery_1_player_id, NA_character_),
       fumble_recovery_2_player_id =
-        ifelse(.data$defteam != .data$fumbled_2_team, .data$fumble_recovery_2_player_id, NA)
+        data.table::fifelse(.data$defteam != .data$fumbled_2_team, .data$fumble_recovery_2_player_id, NA_character_)
     ) %>%
     dplyr::select(
       "season", "week",
@@ -357,9 +367,10 @@ calculate_player_stats_def <- function(pbp, weekly = FALSE) {
       names_from = .data$desc,
       values_from = .data$n,
       values_fn = sum,
-      values_fill = 0
+      values_fill = 0L
     ) %>%
     dplyr::filter(!is.na(.data$player_id)) %>%
+    add_column_if_missing("fumble_recovery") %>%
     dplyr::rename("fumble_recovery_opp" = "fumble_recovery") %>%
     dplyr::group_by(.data$season, .data$week, .data$team, .data$player_id) %>%
     dplyr::summarise(
@@ -445,8 +456,9 @@ calculate_player_stats_def <- function(pbp, weekly = FALSE) {
       names_from = .data$desc,
       values_from = c(.data$n, .data$yards),
       values_fn = sum,
-      values_fill = 0
+      values_fill = 0L
     ) %>%
+    add_column_if_missing("n_penalty", "yards_penalty") %>%
     dplyr::select(
       "season", "week", "team", "player_id",
       "penalty" = "n_penalty",
@@ -587,3 +599,14 @@ calculate_player_stats_def <- function(pbp, weekly = FALSE) {
 
   player_df
 }
+
+# This function checks if the variables in ... exists as column
+# names in the argument .data. If not, it adds those columns and assigns
+# them the value in the argument value
+add_column_if_missing <- function(.data, ..., value = 0L){
+  dots <- rlang::list2(...)
+  new_cols <- dots[!dots %in% names(.data)]
+  .data[,unlist(new_cols)] <- value
+  .data
+}
+