cfbd_metrics_ppa_players_games: *Get player game averages for predicted points added (PPA)*

In cfbfastR: Access College Football Play by Play Data

Get player game averages for predicted points added (PPA)

Description

Get player game averages for predicted points added (PPA)

Usage

cfbd_metrics_ppa_players_games(
  year = NULL,
  week = NULL,
  team = NULL,
  position = NULL,
  athlete_id = NULL,
  threshold = NULL,
  excl_garbage_time = FALSE
)

Arguments

year	(Integer required): Year, 4 digit format (YYYY)
week	(Integer optional): Week - values range from 1-15, 1-14 for seasons pre-playoff, i.e. 2013 or earlier
team	(String optional): D-I Team. Required if year not provided.
position	(string optional): Position abbreviation of the player you are searching for. Position Group - options include: Offense: QB, RB, FB, TE, OL, G, OT, C, WR Defense: DB, CB, S, LB, DE, DT, NT, DL Special Teams: K, P, LS, PK
athlete_id	(Integer optional): Athlete ID filter for querying a single athlete Can be found using the cfbd_player_info() function.
threshold	(Integer optional): Minimum threshold of plays.
excl_garbage_time	(Logical default FALSE): Select whether to exclude Garbage Time (TRUE or FALSE)

Value

cfbd_metrics_ppa_players_games() - A data frame with 9 variables:

season: integer.

Season of the game.

week: integer.

Game week of the season.

name: character.

Athlete name.

position: character.

Athlete position.

team: character.

Team name.

opponent: character.

Team Opponent name.

avg_PPA_all: double.

Average overall predicted points added (PPA).

avg_PPA_pass: double.

Average passing predicted points added (PPA).

avg_PPA_rush: double.

Average rushing predicted points added (PPA).

Examples

  try(cfbd_metrics_ppa_players_games(year = 2019, week = 3, team = "TCU"))

cfbfastR documentation built on June 14, 2022, 1:05 a.m.